High-res multi-view results

This table lists the benchmark results for the high-res multi-view scenario. The following metrics are evaluated:

Accuracy [%]: The fraction of the reconstruction which is closer to the ground truth than the evaluation threshold distance (*). Larger is better.
Completeness [%]: The fraction of the ground truth which is closer to the reconstruction than the evaluation threshold distance (*). Larger is better.
F₁ score [%]: The harmonic mean of accuracy and completeness, used to rank methods based on both metrics. Larger is better.
Time [s]: The runtime of the method. Smaller is better.

(*) For exact definitions, detailing how potentially incomplete ground truth is taken into account, see our paper.

The datasets are grouped into different categories, and result averages are computed for a category and method if results of the method are available for all datasets within the category. Note that the category "all" includes both the high-res multi-view and the low-res many-view scenarios.

Methods with suffix _ROB may participate in the Robust Vision Challenge.

Click a dataset result cell to show a visualization of the reconstruction. For training datasets, ground truth and accuracy / completeness visualizations are also available. The visualizations may not work with mobile browsers.

Method	all	high-res multi-view	indoor	outdoor	botani.	boulde.	bridge	door	exhibi.	lectur.	living.	lounge	observ.	old co.	statue	terrac.

xxxxxxxxxxxxxcwj		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

SF-MVS		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

ETH3D cwj APD-0.16		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

ETH3 D test6400		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

ETH3D-3000-0.1		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

save fliter					0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

TEST9					0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

train_agg		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

test_8					0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

agg_prior1		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

agg_prior					0.00 1	0.00 1		0.00 1		0.00 1			0.00 1

HFP-MVS		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

region2R		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

#test#		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

test_prior4						0.00 1	0.00 1

test_prior3		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

test_prior				0.00 1	0.00 1	0.00 1		0.00 1					0.00 1			0.00 1

新几何1				0.00 1	0.00 1	0.00 1		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

旧先验1					0.00 1	0.00 1		0.00 1			0.00 1	0.00 1			0.00 1	0.00 1

原ACMM1				0.00 1	0.00 1	0.00 1		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

test222					0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1			0.00 1	0.00 1

testdata				0.00 1	0.00 1	0.00 1		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

1314		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

1121		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

MVS		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

test12				0.00 1	0.00 1	0.00 1		0.00 1		0.00 1		0.00 1	0.00 1		0.00 1	0.00 1

abl_6		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

QAPM		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

hse-mvs3		0.30 17	0.30 18	0.30 22	0.30 29	0.30 29	0.30 29	0.30 30	0.30 29	0.30 28	0.30 26	0.30 28	0.30 29	0.30 27	0.30 27	0.30 27

hse-mvs2		0.30 17	0.30 18	0.30 22	0.30 29	0.30 29	0.30 29	0.30 30	0.30 29	0.30 28	0.30 26	0.30 28	0.30 29	0.30 27	0.30 27	0.30 27

CL-MVSNet_2432*1600		0.30 17	0.30 18	0.30 22	0.30 29	0.30 29	0.30 29	0.30 30	0.30 29	0.30 28	0.30 26	0.30 28	0.30 29	0.30 27	0.30 27	0.30 27

AUN-MVS		0.30 17	0.30 18	0.30 22	0.30 29	0.30 29	0.30 29	0.30 30	0.30 29	0.30 28	0.30 26	0.30 28	0.30 29	0.30 27	0.30 27	0.30 27

LCM-MVSNet		0.37 21	0.36 22	0.37 26	0.37 33	0.37 33	0.37 33	0.32 34	0.37 33	0.37 32	0.37 30	0.37 32	0.37 33	0.37 31	0.37 31	0.37 31

v144192		0.40 22	0.40 23	0.40 27	0.40 34	0.40 34	0.40 34	0.40 36	0.40 34	0.40 33	0.40 31	0.40 33	0.40 34	0.40 32	0.40 32	0.40 32

v1921920		0.40 22	0.40 23	0.40 27	0.40 34	0.40 34	0.40 34	0.40 36	0.40 34	0.40 33	0.40 31	0.40 33	0.40 34	0.40 32	0.40 32	0.40 32

v1192		0.40 22	0.40 23	0.40 27	0.40 34	0.40 34	0.40 34	0.40 36	0.40 34	0.40 33	0.40 31	0.40 33	0.40 34	0.40 32	0.40 32	0.40 32

v1144		0.40 22	0.40 23	0.40 27	0.40 34	0.40 34	0.40 34	0.40 36	0.40 34	0.40 33	0.40 31	0.40 33	0.40 34	0.40 32	0.40 32	0.40 32

v148		0.40 22	0.40 23	0.40 27	0.40 34	0.40 34	0.40 34	0.40 36	0.40 34	0.40 33	0.40 31	0.40 33	0.40 34	0.40 32	0.40 32	0.40 32

v7n		0.40 22	0.40 23	0.40 27	0.40 34	0.40 34	0.40 34	0.40 36	0.40 34	0.40 33	0.40 31	0.40 33	0.40 34	0.40 32	0.40 32	0.40 32

v1240		0.40 22	0.40 23	0.40 27	0.40 34	0.40 34	0.40 34	0.40 36	0.40 34	0.40 33	0.40 31	0.40 33	0.40 34	0.40 32	0.40 32	0.40 32

v8		0.40 22	0.40 23	0.40 27	0.40 34	0.40 34	0.40 34	0.40 36	0.40 34	0.40 33	0.40 31	0.40 33	0.40 34	0.40 32	0.40 32	0.40 32

v10		0.40 22	0.40 23	0.40 27	0.40 34	0.40 34	0.40 34	0.40 36	0.40 34	0.40 33	0.40 31	0.40 33	0.40 34	0.40 32	0.40 32	0.40 32

v2v482		0.40 22	0.40 23	0.40 27	0.40 34	0.40 34	0.40 34	0.40 36	0.40 34	0.40 33	0.40 31	0.40 33	0.40 34	0.40 32	0.40 32	0.40 32

V42		0.40 22	0.40 23	0.40 27	0.40 34	0.40 34	0.40 34	0.40 36	0.40 34	0.40 33	0.40 31	0.40 33	0.40 34	0.40 32	0.40 32	0.40 32

GA-MVS		0.40 22	0.40 23	0.40 27	0.40 34	0.40 34	0.40 34	0.40 36	0.40 34	0.40 33	0.40 31	0.40 33	0.40 34	0.40 32	0.40 32	0.40 32

Fast-Effi-MVS+		0.41 34	0.40 23	0.41 39	0.41 46	0.41 46	0.41 46	0.35 35	0.41 46	0.41 45	0.41 43	0.41 45	0.41 46	0.41 44	0.41 44	0.41 44

Fast-Effi-MVS+-dtu		0.44 35	0.44 36	0.44 40	0.44 47	0.44 47	0.44 47	0.44 48	0.44 47	0.44 46	0.44 44	0.44 46	0.44 47	0.44 45	0.44 45	0.44 45

Effi-MVS+-dtu		0.59 37	0.61 39	0.53 41	0.68 53	0.53 48	0.53 48	0.68 54	0.68 53	0.53 47	0.53 45	0.68 52	0.53 48	0.68 51	0.53 46	0.53 46

DIV-MVS_2432*1600		0.60 38	0.60 38	0.60 42	0.60 49	0.60 49	0.60 50	0.60 50	0.60 49	0.60 48	0.60 46	0.60 48	0.60 49	0.60 46	0.60 48	0.60 47

EIA-MVS		0.62 39	0.62 40	0.62 43	0.62 50	0.62 50	0.62 51	0.62 51	0.62 50	0.62 49	0.62 47	0.62 49	0.62 50	0.62 47	0.62 49	0.62 48

ETV-MVS		0.62 39	0.62 40	0.62 43	0.62 50	0.62 50	0.62 51	0.62 51	0.62 50	0.62 49	0.62 47	0.62 49	0.62 50	0.62 47	0.62 49	0.62 48

CS-MVS		0.62 39	0.62 40	0.62 43	0.62 50	0.62 50	0.62 51	0.62 51	0.62 50	0.62 49	0.62 47	0.62 49	0.62 50	0.62 47	0.62 49	0.62 48

Effi-MVS+		0.58 36	0.56 37	0.62 43	0.53 48	0.62 50	0.53 48	0.53 49	0.53 48	0.62 49	0.62 47	0.53 47	0.62 50	0.62 47	0.53 46	0.62 48

mvs-test1		0.68 42	0.68 43	0.68 47	0.68 53	0.68 54	0.68 54	0.68 54	0.68 53	0.68 53	0.68 51	0.68 52	0.68 54	0.68 51	0.68 52	0.68 52

CDS-MVSNet		0.88 43	0.88 44	0.88 48	0.88 55	0.88 55	0.88 55	0.88 56	0.88 55	0.88 54	0.88 52	0.88 54	0.88 55	0.88 53	0.88 53	0.88 53
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
TAMVS		0.88 43	0.88 44	0.88 48	0.88 55	0.88 55	0.88 55	0.88 56	0.88 55	0.88 54	0.88 52	0.88 54	0.88 55	0.88 53	0.88 53	0.88 53

LCM-MVSNet-Re		0.89 45	0.89 46	0.89 50	0.89 57	0.89 57	0.89 57	0.89 58	0.89 57	0.89 56	0.89 54	0.89 56	0.89 57	0.89 55	0.89 55	0.89 55

plane_prior						1.00 58	2.00 90		2.00 91						2.00 89

DeepMVS_CX				1.00 51	1.00 58	1.00 58		1.00 59	1.00 58	1.00 57	1.00 55	1.00 57	1.00 58	1.00 56	1.00 56	1.00 56

MDA-MVSNet-bldmvs		1.20 46	1.20 47	1.20 52	1.20 59	1.20 60	1.20 58	1.20 61	1.20 59	1.20 58	1.20 56	1.20 58	1.20 59	1.20 57	1.20 57	1.20 57

YYNet1		1.20 46	1.20 47	1.20 52	1.20 59	1.20 60	1.20 58	1.20 61	1.20 59	1.20 58	1.20 56	1.20 58	1.20 59	1.20 57	1.20 57	1.20 57

MDA-MVSNet_test_wron		1.20 46	1.20 47	1.20 52	1.20 59	1.20 60	1.20 58	1.20 61	1.20 59	1.20 58	1.20 56	1.20 58	1.20 59	1.20 57	1.20 57	1.20 57

KD-MVS_2432*1600		1.30 49	1.30 50	1.30 55	1.30 62	1.30 63	1.30 61	1.30 64	1.30 62	1.30 61	1.30 59	1.30 61	1.30 62	1.30 60	1.30 60	1.30 60

miper_refine_blended		1.30 49	1.30 50	1.30 55	1.30 62	1.30 63	1.30 61	1.30 64	1.30 62	1.30 61	1.30 59	1.30 61	1.30 62	1.30 60	1.30 60	1.30 60

EI-MVSNet-UG-set		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

EI-MVSNet-Vis-set		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

Regformer-3		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

Regformer-4		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

Regformer-1		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

Regformer-2		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

EI-MVSNet		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

Regformer		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

CVMVSNet		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

EU-MVSNet		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

PS-CasMVS		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

UniMVSNet_NR-MVSNet		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

PEN-MVS		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

TransMVSNet (Re)		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

DTE-MVSNet		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

DU-MVS		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

UniMVSNet (Re)		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

CP-MVSNet		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

WR-MVS_H		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

WR-MVS		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

NR-MVSNet		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

Baseline_NR-MVSNet		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

TranMVSNet+NR-MVSNet		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

MVSFormer		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

jason		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62
jason: jason.
lupinMVS		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

test_djsdf		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

alignmvs		2.00 78	2.00 79	2.00 84	2.00 91	2.00 92	2.00 90	2.00 95	2.00 91	2.00 90	2.00 88	2.00 90	2.00 91	2.00 89	2.00 89	2.00 89

nrg030		2.00 78	2.00 79	2.00 84	2.00 91	2.00 92	2.00 90	2.00 95	2.00 91	2.00 90	2.00 88	2.00 90	2.00 91	2.00 89	2.00 89	2.00 89

LFMVS		2.00 78	2.00 79	2.00 84	2.00 91	2.00 92	2.00 90	2.00 95	2.00 91	2.00 90	2.00 88	2.00 90	2.00 91	2.00 89	2.00 89	2.00 89

VDD-MVS		2.00 78	2.00 79	2.00 84	2.00 91	2.00 92	2.00 90	2.00 95	2.00 91	2.00 90	2.00 88	2.00 90	2.00 91	2.00 89	2.00 89	2.00 89

VDDNet		2.00 78	2.00 79	2.00 84	2.00 91	2.00 92	2.00 90	2.00 95	2.00 91	2.00 90	2.00 88	2.00 90	2.00 91	2.00 89	2.00 89	2.00 89

VPNet		2.00 78	2.00 79	2.00 84	2.00 91	2.00 92	2.00 90	2.00 95	2.00 91	2.00 90	2.00 88	2.00 90	2.00 91	2.00 89	2.00 89	2.00 89

VNet		2.00 78	2.00 79	2.00 84	2.00 91	2.00 92	2.00 90	2.00 95	2.00 91	2.00 90	2.00 88	2.00 90	2.00 91	2.00 89	2.00 89	2.00 89

VPA-MVSNet		2.00 78	2.00 79	2.00 84	2.00 91	2.00 92	2.00 90	2.00 95	2.00 91	2.00 90	2.00 88	2.00 90	2.00 91	2.00 89	2.00 89	2.00 89

cascas		2.00 78	2.00 79	2.00 84	2.00 91	2.00 92	2.00 90	2.00 95	2.00 91	2.00 90	2.00 88	2.00 90	2.00 91	2.00 89	2.00 89	2.00 89

UnsupCasMVSNet_eth		5.90 87	5.90 88	5.90 93	5.90 100	5.90 101	5.90 100	5.90 105	5.90 101	5.90 99	5.90 97	5.90 100	5.90 100	5.90 98	5.90 100	5.90 99

UnsupCasMVSNet_bld		5.90 87	5.90 88	5.90 93	5.90 100	5.90 101	5.90 100	5.90 105	5.90 101	5.90 99	5.90 97	5.90 100	5.90 100	5.90 98	5.90 100	5.90 99

WTY-MVS		5.90 87	5.90 88	5.90 93	5.90 100	5.90 101	5.90 100	5.90 105	5.90 101	5.90 99	5.90 97	5.90 100	5.90 100	5.90 98	5.90 100	5.90 99

HY-MVS	5.90 1	5.90 87	5.90 88	5.90 93	5.90 100	5.90 101	5.90 100	5.90 105	5.90 101	5.90 99	5.90 97	5.90 100	5.90 100	5.90 98	5.90 100	5.90 99

sss		5.90 87	5.90 88	5.90 93	5.90 100	5.90 101	5.90 100	5.90 105	5.90 101	5.90 99	5.90 97	5.90 100	5.90 100	5.90 98	5.90 100	5.90 99

Test_1112_low_res		5.90 87	5.90 88	5.90 93	5.90 100	5.90 101	5.90 100	5.90 105	5.90 101	5.90 99	5.90 97	5.90 100	5.90 100	5.90 98	5.90 100	5.90 99

1112_ss		5.90 87	5.90 88	5.90 93	5.90 100	5.90 101	5.90 100	5.90 105	5.90 101	5.90 99	5.90 97	5.90 100	5.90 100	5.90 98	5.90 100	5.90 99

ab-mvs-re		5.90 87	5.90 88	5.90 93	5.90 100	5.90 101	5.90 100	5.90 105	5.90 101	5.90 99	5.90 97	5.90 100	5.90 100	5.90 98	5.90 100	5.90 99

ab-mvs		5.90 87	5.90 88	5.90 93	5.90 100	5.90 101	5.90 100	5.90 105	5.90 101	5.90 99	5.90 97	5.90 100	5.90 100	5.90 98	5.90 100	5.90 99

CDPH-MVS		6.66 96	6.66 97	6.66 102	6.66 109	6.66 110	6.66 109	6.66 114	6.66 110	6.66 108	6.66 106	6.66 109	6.66 109	6.66 107	6.66 109	6.66 108

dp		87.20 114	113.80 118	7.42 103	10.50 121	8.88 111	298.82 137	2.70 104	510.35 153	7.79 109	172.93 128	3.37 99	9.16 110	14.00 121	3.71 99	4.23 98

MDTV_nov1_ep13_2view						9.99 112	9.99 110		9.99 111	9.99 110		9.99 110		9.99 108		9.99 109

MDTV_nov1_ep13			9.99 98		9.99 110	9.99 112	9.99 110	9.99 116	9.99 111	9.99 110	9.99 107	9.99 110	9.99 111	9.99 108	9.99 110

xiu_mvs_v1_base_debu		10.28 97	10.28 99	10.28 104	10.28 111	10.28 114	10.28 112	10.28 117	10.28 113	10.28 112	10.28 108	10.28 112	10.28 112	10.28 110	10.28 111	10.28 110

xiu_mvs_v2_base		10.28 97	10.28 99	10.28 104	10.28 111	10.28 114	10.28 112	10.28 117	10.28 113	10.28 112	10.28 108	10.28 112	10.28 112	10.28 110	10.28 111	10.28 110

xiu_mvs_v1_base		10.28 97	10.28 99	10.28 104	10.28 111	10.28 114	10.28 112	10.28 117	10.28 113	10.28 112	10.28 108	10.28 112	10.28 112	10.28 110	10.28 111	10.28 110

xiu_mvs_v1_base_debi		10.28 97	10.28 99	10.28 104	10.28 111	10.28 114	10.28 112	10.28 117	10.28 113	10.28 112	10.28 108	10.28 112	10.28 112	10.28 110	10.28 111	10.28 110

cdsmvs_eth3d_5k		10.28 97	10.28 99	10.28 104	10.28 111	10.28 114	10.28 112	10.28 117	10.28 113	10.28 112	10.28 108	10.28 112	10.28 112	10.28 110	10.28 111	10.28 110

pcd_1.5k_mvsjas		10.28 97	10.28 99	10.28 104	10.28 111	10.28 114	10.28 112	10.28 117	10.28 113	10.28 112	10.28 108	10.28 112	10.28 112	10.28 110	10.28 111	10.28 110

PS-MVSNAJss		10.28 97	10.28 99	10.28 104	10.28 111	10.28 114	10.28 112	10.28 117	10.28 113	10.28 112	10.28 108	10.28 112	10.28 112	10.28 110	10.28 111	10.28 110

PS-MVSNAJ		10.28 97	10.28 99	10.28 104	10.28 111	10.28 114	10.28 112	10.28 117	10.28 113	10.28 112	10.28 108	10.28 112	10.28 112	10.28 110	10.28 111	10.28 110

jajsoiax		10.28 97	10.28 99	10.28 104	10.28 111	10.28 114	10.28 112	10.28 117	10.28 113	10.28 112	10.28 108	10.28 112	10.28 112	10.28 110	10.28 111	10.28 110

mvs_tets		10.28 97	10.28 99	10.28 104	10.28 111	10.28 114	10.28 112	10.28 117	10.28 113	10.28 112	10.28 108	10.28 112	10.28 112	10.28 110	10.28 111	10.28 110

SR-MVS-dyc-post		11.55 107	11.55 109	11.55 114	11.55 122	11.55 124	11.55 122	11.55 129	11.55 123	11.55 122	11.55 118	11.55 123	11.55 122	11.55 120	11.55 121	11.55 120

XXY-MVS		15.00 108	15.00 110	15.00 115	15.00 123	15.00 125	15.00 123	15.00 131	15.00 124	15.00 123	15.00 119	15.00 128	15.00 123	15.00 122	15.00 123	15.00 122

BH-w/o		40.00 109	40.00 111	40.00 117	40.00 124	40.00 126	40.00 125	40.00 148	40.00 125	40.00 125	40.00 120	40.00 146	40.00 125	40.00 123	40.00 139	40.00 134

BH-untuned		40.00 109	40.00 111	40.00 117	40.00 124	40.00 126	40.00 125	40.00 148	40.00 125	40.00 125	40.00 120	40.00 146	40.00 125	40.00 123	40.00 139	40.00 134

BH-RMVSNet		40.00 109	40.00 111	40.00 117	40.00 124	40.00 126	40.00 125	40.00 148	40.00 125	40.00 125	40.00 120	40.00 146	40.00 125	40.00 123	40.00 139	40.00 134

TR-MVS		40.00 109	40.00 111	40.00 117	40.00 124	40.00 126	40.00 125	40.00 148	40.00 125	40.00 125	40.00 120	40.00 146	40.00 125	40.00 123	40.00 139	40.00 134

GBi-Net		44.67 113	49.24 115	30.96 116	47.53 128	47.57 130	126.09 129	8.00 115	76.99 129	26.09 124	73.50 125	11.27 122	30.55 124	61.12 127	12.58 122	14.75 121

new_pmnet		88.14 115	98.62 116	56.70 121	98.14 137	56.07 131	246.79 131	15.37 132	148.06 130	50.77 129	143.13 126	23.35 129	62.65 129	93.26 128	68.71 146	51.38 145

N_pmnet		88.14 115	98.62 116	56.70 121	98.14 137	56.07 131	246.79 131	15.37 132	148.06 130	50.77 129	143.13 126	23.35 129	62.65 129	93.26 128	68.71 146	51.38 145

zzz-MVS		833442.10 239	1111233.77 245	67.09 123	65.59 129	64.81 133	284.50 133	10000000.00 273	219.97 137	59.62 131	229.89 140	12.72 124	103.00 146	203.67 146	27.93 124	33.46 123

MTAPA		833442.10 239	1111233.77 245	67.09 123	65.59 129	64.81 133	284.50 133	10000000.00 273	219.97 137	59.62 131	229.89 140	12.72 124	103.00 146	203.67 146	27.93 124	33.46 123

MP-MVS-pluss		833433.63 238	1111219.60 244	75.70 129	74.28 131	73.29 135	284.50 133	11.35 127	238.58 139	65.86 133	255.35 146	14.55 126	115.69 149	10000000.00 268	31.94 126	38.12 132
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
ACMMP_NAP		118.81 121	133.18 123	75.70 129	74.28 131	73.29 135	284.50 133	11.35 127	238.58 139	65.86 133	255.35 146	14.55 126	115.69 149	222.18 148	31.94 126	38.12 132

CANet		110.62 117	124.04 119	70.34 125	82.03 133	74.27 137	325.54 138	25.25 134	207.16 133	69.28 135	194.38 129	27.53 131	95.79 139	147.76 132	37.43 128	40.97 138

CANet_DTU		110.62 117	124.04 119	70.34 125	82.03 133	74.27 137	325.54 138	25.25 134	207.16 133	69.28 135	194.38 129	27.53 131	95.79 139	147.76 132	37.43 128	40.97 138

MVS_0304		110.62 117	124.04 119	70.34 125	82.03 133	74.27 137	325.54 138	25.25 134	207.16 133	69.28 135	194.38 129	27.53 131	95.79 139	147.76 132	37.43 128	40.97 138

UGNet		110.62 117	124.04 119	70.34 125	82.03 133	74.27 137	325.54 138	25.25 134	207.16 133	69.28 135	194.38 129	27.53 131	95.79 139	147.76 132	37.43 128	40.97 138
Wanjuan Su, Qingshan Xu, Wenbing Tao: Uncertainty-guided Multi-view Stereo Network for Depth Estimation. IEEE Transactions on Circuits and Systems for Video Technology, 2022
DSMNet-mixed		131.33 129	143.00 131	96.33 142	99.00 139	81.00 141	201.00 130	45.00 152	335.00 151	99.00 149	251.00 145	38.00 145	110.00 148	120.00 131	99.00 149	98.00 148

PVSNet_Blended_VisFu		136.90 130	155.40 132	81.40 138	111.00 147	96.20 142	407.00 149	25.90 138	251.60 141	85.10 146	240.50 142	37.00 142	99.90 143	199.80 143	40.70 143	48.10 142

PVSNet_BlendedMVS		136.90 130	155.40 132	81.40 138	111.00 147	96.20 142	407.00 149	25.90 138	251.60 141	85.10 146	240.50 142	37.00 142	99.90 143	199.80 143	40.70 143	48.10 142

PVSNet_Blended		136.90 130	155.40 132	81.40 138	111.00 147	96.20 142	407.00 149	25.90 138	251.60 141	85.10 146	240.50 142	37.00 142	99.90 143	199.80 143	40.70 143	48.10 142

FMVSNet5		124.76 122	140.93 124	76.26 131	107.44 140	100.17 145	329.88 142	27.12 141	259.44 144	74.30 139	204.34 133	30.74 135	92.41 132	196.98 136	38.15 132	36.19 125

test1		124.76 122	140.93 124	76.26 131	107.44 140	100.17 145	329.88 142	27.12 141	259.44 144	74.30 139	204.34 133	30.74 135	92.41 132	196.98 136	38.15 132	36.19 125

FMVSNet3		124.76 122	140.93 124	76.26 131	107.44 140	100.17 145	329.88 142	27.12 141	259.44 144	74.30 139	204.34 133	30.74 135	92.41 132	196.98 136	38.15 132	36.19 125

FMVSNet2		124.76 122	140.93 124	76.26 131	107.44 140	100.17 145	329.88 142	27.12 141	259.44 144	74.30 139	204.34 133	30.74 135	92.41 132	196.98 136	38.15 132	36.19 125

FMVSNet1		124.76 122	140.93 124	76.26 131	107.44 140	100.17 145	329.88 142	27.12 141	259.44 144	74.30 139	204.34 133	30.74 135	92.41 132	196.98 136	38.15 132	36.19 125

MIMVSNet1		124.76 122	140.93 124	76.26 131	107.44 140	100.17 145	329.88 142	27.12 141	259.44 144	74.30 139	204.34 133	30.74 135	92.41 132	196.98 136	38.15 132	36.19 125

MIMVSNet		124.76 122	140.93 124	76.26 131	107.44 140	100.17 145	329.88 142	27.12 141	259.44 144	74.30 139	204.34 133	30.74 135	92.41 132	196.98 136	38.15 132	36.19 125

test1172		216.26 133	257.16 135	93.57 141	310.10 154	111.10 152	31.10 124	45.10 153	192.73 132	176.39 150	512.31 149	66.33 152	78.35 131	891.20 173	89.18 148	91.27 147

DP-MVS		264.78 134	296.02 136	171.04 143	191.70 150	183.96 153	827.10 160	78.36 154	438.24 152	176.64 151	435.12 148	65.04 151	230.52 153	334.02 149	117.96 150	98.64 149

tmp_tt		371.08 135	412.78 137	246.00 145	231.00 151	197.00 154	1293.00 172	376.00 206	756.00 162	609.00 186	71.00 124	106.00 161	195.00 151	102.00 130	171.00 159	346.00 182

RPSCF		394.81 136	445.63 138	242.35 144	276.55 153	253.63 155	1207.27 170	90.69 159	715.56 160	241.57 153	684.87 157	111.96 162	320.02 154	548.38 156	133.81 151	153.39 151

EG-PatchMatch MVS		437.03 137	493.12 141	268.77 146	264.80 152	260.20 156	1491.80 175	98.00 163	723.20 161	238.80 152	722.40 158	63.10 150	382.00 157	629.00 160	207.00 166	164.10 154

MVP-Stereo		473.58 140	533.67 142	293.33 147	376.00 158	318.00 157	1461.00 173	96.00 160	835.00 164	290.00 157	804.00 162	97.00 157	383.00 159	688.00 167	156.00 152	179.00 156
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
MS-PatchMatch		473.58 140	533.67 142	293.33 147	376.00 158	318.00 157	1461.00 173	96.00 160	835.00 164	290.00 157	804.00 162	97.00 157	383.00 159	688.00 167	156.00 152	179.00 156

DELS-MVS		514.57 144	587.73 147	295.12 149	343.03 155	328.09 159	1540.48 177	116.22 169	988.59 168	325.44 160	906.22 166	119.86 164	365.72 155	788.60 169	161.09 156	191.55 159
Christian Sormann, Emanuele Santellani, Mattia Rossi, Andreas Kuhn, Friedrich Fraundorfer: DELS-MVS: Deep Epipolar Line Search for Multi-View Stereo. Winter Conference on Applications of Computer Vision (WACV), 2023
tpmvs		501.65 143	567.42 145	304.33 150	395.39 160	356.32 160	1512.04 176	216.53 194	994.15 169	350.16 162	804.16 164	119.38 163	380.98 156	555.14 157	159.87 155	175.69 155

PatchmatchNet		492.52 142	551.22 144	316.40 151	400.20 161	357.90 161	1277.10 171	115.80 168	1034.60 176	315.90 159	874.00 165	155.10 167	402.20 161	629.50 161	158.80 154	189.10 158
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
ACMH+	729.97 2	661.38 151	754.00 154	383.51 156	368.96 157	376.38 162	2483.74 193	82.42 156	1089.25 177	333.39 161	1219.68 181	66.53 153	573.60 178	957.86 176	184.14 162	200.56 160

ADS-MVSNet2		443.33 138	482.84 139	324.79 153	434.94 165	387.73 163	1110.57 168	87.69 157	887.02 166	282.92 154	779.29 159	98.57 159	422.76 162	502.40 150	162.19 157	163.87 152

ADS-MVSNet		443.33 138	482.84 139	324.79 153	434.94 165	387.73 163	1110.57 168	87.69 157	887.02 166	282.92 154	779.29 159	98.57 159	422.76 162	502.40 150	162.19 157	163.87 152

IB-MVS	872.44 4	616.41 150	700.96 153	362.78 155	426.10 164	409.25 165	1822.69 178	124.42 177	1186.23 179	366.85 164	1079.42 178	190.60 180	451.78 164	930.72 175	181.59 161	227.30 162
Christian Sormann, Mattia Rossi, Andreas Kuhn and Friedrich Fraundorfer: IB-MVS: An Iterative Algorithm for Deep Multi-View Stereo based on Binary Decisions. BMVC 2021
CSCG		826.03 164	963.29 169	414.24 158	421.52 163	426.11 166	2230.35 182	179.52 190	1827.44 198	733.43 197	933.12 168	281.25 193	545.23 170	1800.35 204	262.64 179	271.38 170

DP-MVS Recon		516.25 145	581.17 146	321.48 152	361.02 156	429.00 167	1995.36 181	78.48 155	796.20 163	283.32 156	796.02 161	96.78 156	382.98 158	636.72 162	186.66 163	152.46 150

IterMVS		615.05 149	691.66 152	385.23 157	516.40 168	454.80 168	1863.80 179	102.10 165	1142.20 178	364.10 163	1093.20 180	135.00 165	480.40 165	826.90 170	181.20 160	220.50 161
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
Patchmtry		1090.75 179	1198.88 181	766.38 191	1290.90 211	485.90 169	2423.98 191	1267.30 256	1297.17 181	923.90 199	923.40 167	1215.54 252	990.23 196	667.90 164	779.80 212	823.02 210

PMVS	863.65 3	957.08 169	1054.11 178	666.00 184	401.00 162	495.00 170	3790.00 201	279.00 196	1607.00 196	521.00 178	1745.00 196	90.00 154	1105.00 207	639.00 163	415.00 192	398.00 189
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
gg-mvs-nofinetune		594.69 146	605.37 148	562.67 173	617.29 181	500.33 171	772.30 156	413.12 214	579.21 154	552.71 180	567.40 150	662.54 231	531.67 166	503.93 152	779.80 212	656.02 197

ACMH	993.80 5	967.92 170	1106.11 180	553.33 172	494.00 167	534.00 172	3581.00 199	136.00 179	1585.00 195	478.00 175	1871.00 198	90.00 154	839.00 190	1460.00 198	260.00 178	287.00 173
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
new-patchmatchnet		766.12 154	859.03 159	487.38 169	595.68 170	536.14 173	2346.27 184	142.51 182	1488.08 186	422.43 165	1361.32 185	163.65 170	628.60 183	1003.74 185	207.61 167	297.41 175

mvs_anonymous		774.90 156	882.28 162	452.77 159	636.50 182	537.20 174	2348.80 185	120.30 170	1504.30 187	474.40 169	1371.10 186	186.90 173	564.70 172	1078.90 188	219.30 169	256.40 163

casdiffmvs		774.90 156	882.28 162	452.77 159	636.50 182	537.20 174	2348.80 185	120.30 170	1504.30 187	474.40 169	1371.10 186	186.90 173	564.70 172	1078.90 188	219.30 169	256.40 163

diffmvs		774.90 156	882.28 162	452.77 159	636.50 182	537.20 174	2348.80 185	120.30 170	1504.30 187	474.40 169	1371.10 186	186.90 173	564.70 172	1078.90 188	219.30 169	256.40 163

baseline2		774.90 156	882.28 162	452.77 159	636.50 182	537.20 174	2348.80 185	120.30 170	1504.30 187	474.40 169	1371.10 186	186.90 173	564.70 172	1078.90 188	219.30 169	256.40 163

baseline1		774.90 156	882.28 162	452.77 159	636.50 182	537.20 174	2348.80 185	120.30 170	1504.30 187	474.40 169	1371.10 186	186.90 173	564.70 172	1078.90 188	219.30 169	256.40 163

baseline		774.90 156	882.28 162	452.77 159	636.50 182	537.20 174	2348.80 185	120.30 170	1504.30 187	474.40 169	1371.10 186	186.90 173	564.70 172	1078.90 188	219.30 169	256.40 163

IterMVS-LS		758.94 153	856.56 158	466.10 166	606.60 173	546.80 180	2309.90 183	122.20 176	1402.80 184	463.50 168	1348.20 183	192.60 181	574.60 179	1028.60 186	234.60 177	276.90 171
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
SixPastTwentyTwo		773.62 155	869.37 161	486.35 168	603.45 172	547.15 181	2532.14 194	106.92 167	1434.95 185	428.08 166	1360.56 184	165.15 171	628.96 184	984.09 177	209.01 168	282.94 172

Gipuma		689.75 152	767.00 155	458.00 165	613.00 180	549.00 182	1943.00 180	187.00 191	1230.00 180	518.00 177	1092.00 179	203.00 186	564.00 171	892.00 174	225.00 175	261.00 169
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
PVSNet	1207.94 6	829.56 165	937.18 168	506.69 170	645.55 188	585.72 183	2477.98 192	130.52 178	1578.29 194	509.50 176	1460.01 192	194.90 182	637.19 185	1170.78 195	267.07 181	297.17 174

GG-mvs-BLEND				596.01 176	611.29 177	600.33 184	790.30 157	513.12 225		552.71 180	567.40 150	662.54 231	531.67 166	503.93 152	779.80 212	656.02 197

gm-plane-assit					611.29 177	600.33 184			579.21 154		567.40 150		531.67 166	503.93 152

CR-MVSNet		612.36 148	617.81 151	596.01 176	611.29 177	600.33 184	790.30 157	513.12 225	579.21 154	552.71 180	567.40 150	662.54 231	531.67 166	503.93 152	779.80 212	656.02 197

RE-MVS-def			610.10 149		610.10 175	610.10 187	610.10 154	610.10 234	610.10 158	610.10 187	610.10 155	610.10 221		610.10 158	610.10 196	610.10 194

SR-MVS		610.10 147	610.10 149	610.10 178	610.10 175	610.10 187	610.10 154	610.10 234	610.10 158	610.10 187	610.10 155	610.10 221	610.10 181	610.10 158	610.10 196	610.10 194

ACMP	1246.57 7	1086.24 178	1235.17 182	639.45 179	596.53 171	639.91 189	3904.24 202	152.04 185	1851.54 199	566.58 184	1997.95 200	138.50 166	938.30 194	1605.46 200	303.70 187	340.14 180
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
lessismore_v0				569.20 174	667.25 190	644.68 190		96.45 162		428.86 167	1514.17 193	204.21 187	756.58 187	1061.60 187	197.79 165	306.34 176

MVSTER		890.06 168	1005.91 177	542.52 171	736.13 193	653.90 191	2616.56 196	145.22 184	1692.10 197	555.69 183	1554.72 194	266.25 192	660.02 186	1219.66 196	266.84 180	313.64 178

PVSNet_0	1661.03 9	968.54 171	1066.82 179	673.70 185	706.94 191	695.69 192	2669.02 197	153.52 186	2108.17 203	605.54 185	1679.14 195	213.26 190	886.75 193	1236.76 197	229.01 176	438.67 190

MSLP-MVS++		1242.93 183	1411.08 186	738.48 189	712.71 192	712.68 193	4168.17 204	136.50 180	2276.40 205	613.28 189	2368.60 205	161.61 169	1130.38 208	1964.54 207	297.88 184	372.39 185

ACMM	1311.08 8	1165.06 182	1332.72 185	662.07 183	584.90 169	715.99 194	4373.59 206	153.99 187	1880.27 200	709.02 194	2316.97 202	188.63 179	939.89 195	1484.30 199	302.78 186	330.34 179
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
MVS_111021_LR		1136.45 181	1298.72 184	649.64 180	756.17 194	726.26 195	3785.94 200	138.15 181	2190.64 204	629.63 190	2064.39 201	165.45 172	874.83 192	1678.43 203	279.70 182	347.82 183

MG-MVS		1256.50 184	1432.00 187	730.00 188	610.00 174	760.00 196	4720.00 207	169.00 188	1920.00 201	723.00 196	2510.00 208	201.00 184	1050.00 205	1645.00 202	390.00 191	380.00 186

ACMMPR		1296.60 185	1480.82 188	743.96 190	899.25 198	763.47 197	4305.47 205	143.90 183	2530.94 208	683.99 191	2346.34 204	201.65 185	1098.25 206	1920.59 206	295.21 183	370.16 184

test_0402		1110.00 180	1260.00 183	660.00 181	900.00 199	780.00 198	3300.00 198	210.00 193	2040.00 202	690.00 192	1950.00 199	300.00 196	810.00 189	1620.00 201	330.00 188	390.00 188

K. test v3		877.74 167	980.16 170	570.46 175	1316.85 213	813.15 199	2565.52 195	103.78 166	1509.49 193	548.33 179	1258.90 182	219.93 191	587.82 180	1102.37 194	196.30 164	310.42 177

DeepC-MVS_fast	2190.19 12	1535.59 188	1886.82 192	481.89 167	847.73 195	830.16 200	7943.84 226	189.23 192	2398.83 206	691.73 193	2341.13 203	209.16 188	230.25 152	1999.25 208	360.46 189	385.25 187
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
TSAR-MVS + GP.		1386.84 186	1622.84 190	678.81 186	952.13 200	840.17 201	5358.21 210	170.75 189	2650.47 209	713.54 195	2394.28 206	209.42 189	855.56 191	1854.36 205	302.42 185	340.71 181

PatchT		856.34 166	860.99 160	842.38 192	1290.90 211	880.90 202	790.30 157	1267.30 256	579.21 154	923.90 199	567.40 150	662.54 231	990.23 196	887.56 172	779.80 212	656.02 197

FPMVS		1407.00 187	1495.59 189	1141.23 201	648.01 189	893.85 203	4124.00 203	503.81 224	3219.04 211	742.72 198	2498.84 207	157.98 168	1727.83 214	832.93 171	732.98 211	802.00 206

JIA-IIPM		804.30 163	835.64 157	710.26 187	885.90 196	895.90 204	455.98 152	668.73 238	1297.17 181	1002.26 209	1001.67 176	655.98 229	756.98 188	667.90 164	885.21 224	477.90 191

RPMNet		787.26 162	829.13 156	661.63 182	885.90 196	895.90 204	455.98 152	610.10 234	1297.17 181	1002.26 209	1001.67 176	655.98 229	611.10 182	667.90 164	885.21 224	477.90 191

ambc				999.00 193	999.00 201	999.00 206	999.00 161	999.00 249		999.00 202	999.00 169	999.00 244	999.00 198	999.00 178	999.00 230	999.00 227

OurMVSNet-221017-0		999.00 172	999.00 171	999.00 193	999.00 201	999.00 206	999.00 161	999.00 249	999.00 170	999.00 202	999.00 169	999.00 244	999.00 198	999.00 178	999.00 230	999.00 227

EPMVS		999.00 172	999.00 171	999.00 193	999.00 201	999.00 206	999.00 161	999.00 249	999.00 170	999.00 202	999.00 169	999.00 244	999.00 198	999.00 178	999.00 230	999.00 227

uanet_test		1000.00 174	1000.00 173	1000.00 196	1000.00 204	1000.00 209	1000.00 164	1000.00 252	1000.00 172	1000.00 205	1000.00 172	1000.00 247	1000.00 201	1000.00 181	1000.00 233	1000.00 230

sosnet		1000.00 174	1000.00 173	1000.00 196	1000.00 204	1000.00 209	1000.00 164	1000.00 252	1000.00 172	1000.00 205	1000.00 172	1000.00 247	1000.00 201	1000.00 181	1000.00 233	1000.00 230

USDC		1000.00 174	1000.00 173	1000.00 196	1000.00 204	1000.00 209	1000.00 164	1000.00 252	1000.00 172	1000.00 205	1000.00 172	1000.00 247	1000.00 201	1000.00 181	1000.00 233	1000.00 230

TinyColmap		1000.00 174	1000.00 173	1000.00 196	1000.00 204	1000.00 209	1000.00 164	1000.00 252	1000.00 172	1000.00 205	1000.00 172	1000.00 247	1000.00 201	1000.00 181	1000.00 233	1000.00 230

COLMAP_ROB	2144.59 11	1658.33 189	1869.33 191	1025.33 200	1030.00 208	1023.00 213	5311.00 209	359.00 204	3044.00 210	937.00 201	2892.00 209	332.00 200	1440.00 211	2312.00 210	607.00 195	613.00 196
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
F-COLMAP		1878.17 190	2113.11 193	1173.33 204	1231.00 209	1174.00 214	6297.00 212	392.00 209	3356.00 213	1087.00 211	3082.00 210	361.00 204	1670.00 213	2523.00 212	689.00 202	676.00 201

PCF-MVS	4335.85 20	2272.23 196	2597.03 199	1297.84 205	1701.20 218	1332.37 215	8105.11 227	451.45 217	4031.84 218	1099.10 212	3966.50 217	467.45 211	1734.05 215	2701.68 214	848.94 221	827.11 211
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
PLC	2858.82 16	2192.92 194	2474.00 197	1349.67 206	1407.00 214	1356.00 216	7164.00 217	475.00 221	3970.00 217	1237.00 218	3765.00 216	451.00 210	1891.00 219	3006.00 215	791.00 217	802.00 206
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
OpenMVS_ROB	1936.51 10	1959.51 191	2224.88 195	1163.39 203	1253.91 210	1434.22 217	7065.71 216	272.76 195	2472.29 207	1647.54 239	3538.72 213	200.37 183	1496.48 212	2575.17 213	997.45 229	559.48 193

MVS-HIRNet		2125.39 193	2452.68 196	1143.53 202	2938.33 251	1446.92 218	6083.19 211	391.74 208	3801.71 216	1202.10 215	3439.72 211	492.73 213	1304.35 210	3048.25 216	676.32 201	679.32 202

CMPMVS	2623.62 15	1983.08 192	2156.14 194	1463.89 214	1414.80 215	1517.00 219	5239.20 208	867.40 243	3310.30 212	1128.70 213	3489.90 212	366.75 205	2030.20 225	2427.60 211	1160.60 239	844.46 213
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
AdaColmap		2570.77 202	2948.61 205	1437.24 210	1873.64 228	1526.60 220	7819.77 224	373.97 205	4970.45 226	1479.29 226	4648.46 224	525.80 216	1904.97 220	4150.42 229	695.69 207	880.14 218

3Dnovator	2482.06 14	2531.17 200	2839.56 203	1606.00 215	1732.00 222	1557.00 221	8375.00 229	483.00 222	4370.00 222	1371.00 224	4200.00 218	350.00 202	2207.00 226	3877.00 224	798.00 218	1054.00 234

OpenMVS	2352.88 13	2263.08 195	2530.89 198	1459.67 213	1767.00 226	1591.00 222	7932.00 225	399.00 210	3643.00 214	1176.00 214	3569.00 214	297.00 195	1927.00 221	3302.00 217	693.00 206	861.00 214

test_0728_SECOND				1451.45 211	1725.60 219	1598.35 223	9203.30 233	315.86 199					2023.43 222	3973.88 225	620.04 198	732.56 203

test0726					1725.60 219	1598.35 223	9203.30 233	315.86 199	5016.02 228	1363.85 221	4894.28 226	387.23 206

SD-MVS		2654.53 203	3055.56 208	1451.45 211	1725.60 219	1598.35 223	9203.30 233	315.86 199	5016.02 228	1363.85 221	4894.28 226	387.23 206	2023.43 222	3973.88 225	620.04 198	732.56 203
Zhenlong Yuan, Jiakai Cao, Zhaoxin Li, Hao Jiang and Zhaoqi Wang: SD-MVS: Segmentation-driven Deformation Multi-View Stereo with Spherical Refinement and EM optimization. AAAI2024
CHOSEN 280x420		2340.81 197	2643.03 200	1434.14 207	2025.55 235	1629.36 226	6542.40 213	412.49 211	4219.70 219	1547.02 229	4328.52 219	650.74 226	1798.26 216	3333.17 218	727.72 208	874.79 215

CHOSEN 1792x2688		2340.81 197	2643.03 200	1434.14 207	2025.55 235	1629.36 226	6542.40 213	412.49 211	4219.70 219	1547.02 229	4328.52 219	650.74 226	1798.26 216	3333.17 218	727.72 208	874.79 215

HyFIR lowres test		2340.81 197	2643.03 200	1434.14 207	2025.55 235	1629.36 226	6542.40 213	412.49 211	4219.70 219	1547.02 229	4328.52 219	650.74 226	1798.26 216	3333.17 218	727.72 208	874.79 215

SteuartSystems-ACMMP		2891.50 207	3284.78 210	1711.67 219	1954.00 229	1655.00 229	10117.00 242	445.00 216	5102.00 231	1375.00 225	5126.00 230	351.00 203	2638.00 238	4402.00 232	691.00 204	842.00 212
Skip Steuart: Steuart Systems R&D Blog.
LF4IMVS		2699.50 205	3049.67 207	1649.00 217	1755.00 223	1689.00 230	8330.00 228	464.00 219	4997.00 227	1528.00 227	4763.00 225	568.00 219	2296.00 228	4215.00 230	827.00 220	962.00 224

tpm2		3617.85 214	4007.23 216	2449.73 232	2012.71 231	1698.05 231	7351.19 219	869.29 244	6132.06 234	1588.28 234	8007.42 247	1281.09 253	3888.11 250	7472.04 250	1351.00 241	1763.02 247

tpm cat1		3617.85 214	4007.23 216	2449.73 232	2012.71 231	1698.05 231	7351.19 219	869.29 244	6132.06 234	1588.28 234	8007.42 247	1281.09 253	3888.11 250	7472.04 250	1351.00 241	1763.02 247

CostFormer		3617.85 214	4007.23 216	2449.73 232	2012.71 231	1698.05 231	7351.19 219	869.29 244	6132.06 234	1588.28 234	8007.42 247	1281.09 253	3888.11 250	7472.04 250	1351.00 241	1763.02 247

tpm		3617.85 214	4007.23 216	2449.73 232	2012.71 231	1698.05 231	7351.19 219	869.29 244	6132.06 234	1588.28 234	8007.42 247	1281.09 253	3888.11 250	7472.04 250	1351.00 241	1763.02 247

DeepPCF-MVS	3452.42 18	2670.71 204	3021.57 206	1618.12 216	2377.67 241	1751.39 235	8915.70 232	567.44 232	4569.74 224	1236.84 217	4615.63 223	513.23 214	2291.32 227	3515.48 221	882.39 223	811.66 208

tpmrst		2557.50 201	2847.12 204	1688.66 218	1784.08 227	1778.25 236	7445.50 223	342.14 202	4471.54 223	1534.55 228	4382.10 222	530.10 217	2361.21 229	4142.81 228	991.22 228	926.51 220

DPM-MVS		3268.00 210	3762.89 213	1783.33 221	1756.00 224	1806.00 237	12319.00 245	307.00 197	6319.00 239	1557.00 232	5763.00 232	302.00 197	2609.00 234	5061.00 236	482.00 193	935.00 221

OPM-MVS		3268.00 210	3762.89 213	1783.33 221	1756.00 224	1806.00 237	12319.00 245	307.00 197	6319.00 239	1557.00 232	5763.00 232	302.00 197	2609.00 234	5061.00 236	482.00 193	935.00 221

ZD-MVS					1584.00 216	1821.00 239		378.00 207	3721.00 215	1231.00 216	1833.00 197	321.00 199	1224.00 209	2103.00 209	692.00 205

DeepC-MVS	3917.13 19	3155.06 209	3601.83 212	1814.72 223	2515.52 244	1941.53 240	10432.50 243	589.42 233	4789.45 225	1298.65 220	7677.31 245	578.35 220	2589.53 232	3611.78 223	923.52 226	913.10 219
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
DVP-MVS		3981.10 220	4731.32 225	1730.42 220	2191.51 238	1949.98 241	16473.90 253	355.33 203	7172.90 250	1622.98 238	7879.79 246	434.33 209	2428.11 231	5762.12 239	689.04 203	813.18 209
Zhenlong Yuan, Jinguo Luo, Fei Shen, Zhaoxin Li, Cong Liu, Tianlu Mao, Zhaoqi Wang: DVP-MVS: Synergize Depth-Edge and Visibility Prior for Multi-View Stereo. AAAI2025
ITE_SJBPF				2014.00 228	1998.00 230	1992.00 242		701.00 239	5989.00 233	1812.00 243	3612.00 215	650.00 225	2852.00 240	4601.00 234	1195.00 240	1198.00 237

3Dnovator+	3414.41 17	3146.67 208	3537.00 211	1975.67 225	2310.00 239	2005.00 243	10100.00 241	626.00 237	5753.00 232	1803.00 242	5179.00 231	487.00 212	2622.00 236	4550.00 233	1025.00 237	1300.00 238

Vis-MVSNet		2877.42 206	3170.00 209	1999.67 227	1673.00 217	2042.00 244	8593.00 230	474.00 220	6452.00 241	1268.00 219	5125.00 229	339.00 201	3004.00 241	4222.00 231	384.00 190	953.00 223
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
TSAR-MVS + MP.		3528.01 213	4065.89 220	1914.35 224	2349.10 240	2141.30 245	12362.70 247	417.60 215	6717.80 245	1759.40 241	6497.50 235	518.18 215	2629.38 237	5164.32 238	806.40 219	972.38 226
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
MVS_111021_HR		3742.80 218	4330.34 221	1980.20 226	2484.31 243	2259.52 246	14973.80 251	515.90 231	6500.13 242	1949.21 244	6146.89 234	535.66 218	2593.66 233	4880.76 235	986.37 227	1087.43 235

GST-MVS		4000.00 221	4533.33 223	2400.00 231	2400.00 242	2400.00 247	7200.00 218	2400.00 260	7200.00 251	2400.00 250	7200.00 242	2400.00 257	2400.00 230	7200.00 248	2400.00 253	2400.00 252

SED-MVS		4062.74 222	4671.13 224	2237.56 230	2643.17 246	2465.14 248	13996.40 249	493.26 223	7619.38 252	2107.24 245	7416.93 244	610.24 223	3088.29 246	6075.14 245	1078.39 238	1159.26 236

TAPA-MVS	6309.84 21	3374.90 212	3806.99 215	2078.63 229	2535.47 245	2499.25 249	8816.16 231	456.05 218	6255.60 238	1664.52 240	6704.88 237	629.95 224	2768.38 239	6343.93 246	856.35 222	968.25 225
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
IU-MVS					2725.60 247	2598.35 250		515.86 227	7016.02 246	2363.85 246				5973.88 241	1620.04 247	1732.56 243

OPU-MVS				2451.45 236	2725.60 247	2598.35 250	9203.30 233				6894.28 238	887.23 239	3023.43 242	5973.88 241	1620.04 247	1732.56 243

test_241102_ONE					2725.60 247	2598.35 250		515.86 227	7016.02 246	2363.85 246	6894.28 238	887.23 239	3023.43 242

MSP-MVS		4296.20 223	4911.12 227	2451.45 236	2725.60 247	2598.35 250	16203.30 252	515.86 227	7016.02 246	2363.85 246	6894.28 238	887.23 239	3023.43 242	5973.88 241	1620.04 247	1732.56 243
Zhenlong Yuan, Cong Liu, Fei Shen, Zhaoxin Li, Jingguo luo, Tianlu Mao and Zhaoqi Wang: MSP-MVS: Multi-granularity Segmentation Prior Guided Multi-View Stereo. AAAI2025
OMC-MVS		5022.26 225	5748.82 228	2842.58 240	4905.27 255	3101.27 254	14933.60 250	812.24 242	9278.40 253	2959.29 253	8800.17 251	1092.24 251	3806.30 249	7568.54 254	1389.60 245	1620.18 241

API-MVS		4380.83 224	4906.56 226	2803.67 239	3844.00 253	3116.00 255	13454.00 248	901.00 248	6511.00 243	2794.00 252	7365.00 243	754.00 235	3634.00 248	6622.00 247	1914.00 252	1661.00 242

MAR-MVS		3973.16 219	4387.92 222	2728.86 238	3345.27 252	3341.39 256	11403.90 244	798.76 241	6555.62 244	2569.29 251	6514.86 236	834.97 238	3237.43 247	5891.08 240	1577.54 246	1607.76 239
Zhenyu Xu, Yiguang Liu, Xuelei Shi, Ying Wang, Yunan Zheng: MARMVS: Matching Ambiguity Reduced Multiple View Stereo for Efficient Large Scale Scene Reconstruction. CVPR 2020
CLD-MVS		7338.25 226	8341.00 229	4330.00 241	4902.00 254	4991.00 257	23318.00 255	728.00 240	14437.00 260	4378.00 255	13379.00 256	824.00 237	5708.00 254	11429.00 260	1674.00 251	2291.00 251
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
LS3D		7684.71 227	8776.23 230	4410.16 242	5298.55 256	5631.53 258	34329.90 257	1504.57 258	11554.00 259	3896.41 254	15111.00 257	812.19 236	5985.63 255	3516.20 222	2963.23 254	1613.31 240

CNLPA		10738.67 233	11772.44 236	7637.33 243	9120.00 258	8206.00 259	22252.00 254	2010.00 259	24984.00 261	7458.00 257	22596.00 259	2940.00 258	10260.00 260	11100.00 259	3492.00 255	4446.00 253

MVE	10021.00 22	10550.67 232	10002.44 235	12195.33 248	6242.00 257	8768.00 260	30896.00 256	4451.00 261	10331.00 258	6247.00 256	18296.00 258	283.00 194	21484.00 261	7364.00 249	5912.00 256	6334.00 254
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
ZNCC-MVS		9999.00 228	9999.00 231	9999.00 244	9999.00 259	9999.00 261	9999.00 237	9999.00 264	9999.00 254	9999.00 258	9999.00 252	9999.00 260	9999.00 256	9999.00 255	9999.00 257	9999.00 255

UA-Net		10000.00 229	10000.00 232	10000.00 245	10000.00 260	10000.00 262	10000.00 238	10000.00 265	10000.00 255	10000.00 259	10000.00 253	10000.00 261	10000.00 257	10000.00 256	10000.00 258	10000.00 256

uncertanet		10000.00 229	10000.00 232	10000.00 245	10000.00 260	10000.00 262	10000.00 238	10000.00 265	10000.00 255	10000.00 259	10000.00 253	10000.00 261	10000.00 257	10000.00 256	10000.00 258	10000.00 256

uanet		10000.00 229	10000.00 232	10000.00 245	10000.00 260	10000.00 262	10000.00 238	10000.00 265	10000.00 255	10000.00 259	10000.00 253	10000.00 261	10000.00 257	10000.00 256	10000.00 258	10000.00 256

LTVRE_ROB	20565.47 23	23378.08 234	22805.00 237	25097.33 249	15500.00 263	19201.00 265	42712.00 258	6055.00 262	38388.00 262	16926.00 262	38534.00 260	7071.00 259	35653.00 262	29475.00 261	10584.00 261	20438.00 260
Andreas Kuhn, Heiko HirschmÃ¼ller, Daniel Scharstein, Helmut Mayer: A TV Prior for High-Quality Scalable Multi-View Stereo Reconstruction. International Journal of Computer Vision 2016
MSDG		32606.17 235	34443.44 238	27094.33 250	29249.00 264	25246.00 266	51144.00 259	6705.00 263	42886.00 263	22888.00 263	48534.00 261	13263.00 264	37507.00 263	79298.00 262	16024.00 262	18530.00 259

114514_t		99999.00 236	99999.00 239	99999.00 251	99999.00 265	99999.00 267	99999.00 260	99999.00 268	99999.00 264	99999.00 264	99999.00 262	99999.00 265	99999.00 264	99999.00 263	99999.00 263	99999.00 261

PHI-MVS		99999.00 236	99999.00 239	99999.00 251	99999.00 265	99999.00 267	99999.00 260	99999.00 268	99999.00 264	99999.00 264	99999.00 262	99999.00 265	99999.00 264	99999.00 263	99999.00 263	99999.00 261

XVG-OURS-SEG-HR		999999.00 241	999999.00 241	999999.00 253	999999.00 267	999999.00 269	999999.00 262	999999.00 270	999999.00 266	999999.00 266	999999.00 264	999999.00 267	999999.00 266	999999.00 265	999999.00 265	999999.00 263

XVG-OURS		999999.00 241	999999.00 241	999999.00 253	999999.00 267	999999.00 269	999999.00 262	999999.00 270	999999.00 266	999999.00 266	999999.00 264	999999.00 267	999999.00 266	999999.00 265	999999.00 265	999999.00 263

XVG-ACMP-BASELINE		999999.00 241	999999.00 241	999999.00 253	999999.00 267	999999.00 269	999999.00 262	999999.00 270	999999.00 266	999999.00 266	999999.00 264	999999.00 267	999999.00 266	999999.00 265	999999.00 265	999999.00 263

Anonymous20240521		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

cl-mvsnet2		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

miper_ehance_all_eth		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

miper_enhance_ethall		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

cl-mvsnet_		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

cl-mvsnet1		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

eth_miper_zixun_eth		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

testtj		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

ET-MVSNet_ETH3D		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

UniMVSNet_ETH3D		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

miper_lstm_enhance		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

D2MVS		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

test_yl		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

thisisatest0530		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

Anonymous20240529		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

Anonymous202405211		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

DCV-MVSNet		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

tttt0517		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

our_test_3		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

thisisatest0515		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

ppachtmachnet_test		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

SMA-MVS		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266
Yufeng Yin; Xiaoyan Liu; Zichao Zhang: SMA-MVS: Segmentation-Guided Multi-Scale Anchor Deformation Patch Multi-View Stereo. IEEE Transactions on Circuits and Systems for Video Technology
DPE-MVS		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
test_part2					10000000.00 270	10000000.00 272				10000000.00 269

test_part1		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

thres100view900		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

tfpnnormal		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

tfpn200view9		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

cl_fuxian		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

IterMVS-SCA-FT		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

pmmvs6		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

pmmvs5		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

Anonymous20231211		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

pmmvs-eth3d		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

Anonymous20231206		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

SCA		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

Patchmatch-test		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

Patchmatch-RL test		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

canonicalmvs		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

anonymousdsp		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

FIs		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

FC-MVSNet-test		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

sosnet-low-res		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

AllTest		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

TestCases				10000000.00 256	10000000.00 270	10000000.00 272		10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

bset_n11_16_dypcd		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

RRT_MVS		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

HPM-MVS++		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

XVS		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

pm-mvs1		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

X-MVStestdata		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

APDe-MVS		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

APD-MVS_3200maxsize		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

pmmvs4		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

test-LLR		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

TESTMET0.1,1		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

test-mter		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

testgi		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

test20.03		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

thres600view7		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

MP-MVS		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
testmvs		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

thres400		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

test123		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

thres200		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

test0.0.03 1		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

pmmvs3		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

EMVS		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

E-PMN		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

PGM-MVS		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

MCST-MVS		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

MVS_Test		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

PMMVS2		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

PM-MVS		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

HQP_MVS		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

plane_prior7					10000000.00 270	10000000.00 272

plane_prior6					10000000.00 270	10000000.00 272						10000000.00 270

plane_prior3						10000000.00 272			10000000.00 269	10000000.00 269

mPP-MVS		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

DWT-MVSNet_test		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

HPM-MVS_fast		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

RRT_test8_iter05		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

HPM-MVS		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
LPG-MVS_test		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

LGP-MVS_train				10000000.00 256	10000000.00 270	10000000.00 272		10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

EPNet_dtu		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
EPNet		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
HQP5-MVS						10000000.00 272

CNVR-MVS		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

NCCC		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

CP-MVS		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

NP-MVS					10000000.00 270	10000000.00 272					10000000.00 267

CPTT-MVS		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

HQP-MVS		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

IS-MVSNet		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

PAPM_NR		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

PAPR		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

Vis-MVSNet (Re-imp)		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

PatchMatch-RL		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

TDRefinement		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

EPP-MVSNet		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

PMMVS		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

PAPM		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

ACMMP		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266
Qingshan Xu, Weihang Kong, Wenbing Tao, Marc Pollefeys: Multi-Scale Geometric Consistency Guided and Planar Prior Assisted Multi-View Stereo. IEEE Transactions on Pattern Analysis and Machine Intelligence
ANet_high		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

wuyk23d		10000000.00 244	10000000.00 247	10000000.00 256	10000000.00 270	10000000.00 272	10000000.00 265	10000000.00 273	10000000.00 269	10000000.00 269	10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

APD-MVS		1000000000.00 342	1000000000.00 345	1000000000.00 356	1000000000.00 377	1000000000.00 378	1000000000.00 368	1000000000.00 379	1000000000.00 373	1000000000.00 374	1000000000.00 372	1000000000.00 377	1000000000.00 374	1000000000.00 372	1000000000.00 372	1000000000.00 370
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
test_241102_TWO								515.86 227	7016.02 246	2363.85 246	6894.28 238	887.23 239	3023.43 242	5973.88 241	1620.04 247	1732.56 243

9.14			0.00 1		0.00 1		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

test_0728_THIRD									5016.02 228	1363.85 221	4894.28 226	387.23 206	2023.43 222	3973.88 225	620.04 198	732.56 203

GSMVS																10000000.00 266

sam_mvs1												10000000.00 270				10000000.00 266

sam_mvs												10000000.00 270

MTGPA								10000000.00 273

test_post1							10000000.00 265				10000000.00 267	10000000.00 270	10000000.00 269	10000000.00 268

test_post											10000000.00 267	10000000.00 270	10000000.00 269

patchmatchnet-post											10000000.00 267	10000000.00 270	10000000.00 269

MTMP							10000000.00 265	10000000.00 273

test9_res														0.00 1	0.00 1	0.00 1

agg_prior2														0.00 1	0.00 1	0.00 1

test_prior2							0.00 1		0.00 1	0.00 1	0.00 1	0.00 1		0.00 1	0.00 1

旧先验2							0.00 1		0.00 1	0.00 1			0.00 1	0.00 1

新几何2							0.00 1

无先验							0.00 1	0.00 1	0.00 1				0.00 1	0.00 1		0.00 1

原ACMM2							0.00 1

testdata2													0.00 1	0.00 1

segment_acmp												0.00 1

testdata1							0.00 1		0.00 1

plane_prior5								10000000.00 273					10000000.00 269	10000000.00 268	10000000.00 268	10000000.00 266

plane_prior4											10000000.00 267

plane_prior2							10000000.00 265		10000000.00 269

plane_prior1					10000000.00 270

n2								14.20 130

nn								1.42 66

door-mid								1.42 66

test11								1.00 59

door								99.00 164

HQP-NCC					10000000.00 270		10000000.00 265		10000000.00 269	10000000.00 269

ACMP_Plane					10000000.00 270		10000000.00 265		10000000.00 269	10000000.00 269

BP-MVS														10000000.00 268

HQP4-MVS										10000000.00 269			10000000.00 269			10000000.00 266

HQP3-MVS								10000000.00 273							10000000.00 268

HQP2-MVS												10000000.00 270

ACMMP++_ref															10000000.00 268

ACMMP++															10000000.00 268

Test By Simon												990.00 243

High-resolution multi-view benchmark