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.

GG-mvs-BLEND				99.59 133	99.54 201	99.49 133	99.17 337	99.52 72		99.96 118	99.68 252	100.00 1	99.33 244	99.71 131	99.99 113	99.96 120

gg-mvs-nofinetune		96.95 239	96.10 259	99.50 144	99.41 233	99.36 147	99.07 350	99.52 72	83.69 360	99.96 118	83.60 374	100.00 1	99.20 248	99.68 140	99.99 113	99.96 120

CHOSEN 280x420		99.85 3	99.87 1	99.80 107	99.99 59	99.97 22	99.97 221	99.98 16	98.96 28	100.00 1	100.00 1	99.96 3	99.42 238	100.00 1	100.00 1	100.00 1

test_yl		99.51 76	99.37 86	99.95 61	99.82 130	99.90 65	100.00 1	99.47 80	97.48 157	100.00 1	100.00 1	99.80 4	100.00 1	99.98 81	97.75 218	99.94 130

DCV-MVSNet		99.51 76	99.37 86	99.95 61	99.82 130	99.90 65	100.00 1	99.47 80	97.48 157	100.00 1	100.00 1	99.80 4	100.00 1	99.98 81	97.75 218	99.94 130

patch_mono-2		99.04 124	99.79 6	96.81 306	99.92 118	90.47 353	100.00 1	99.41 182	98.95 31	100.00 1	100.00 1	99.78 6	100.00 1	100.00 1	100.00 1	99.95 125

MVSTER		98.58 164	98.52 164	98.77 202	99.65 172	99.68 118	100.00 1	99.29 239	95.63 254	98.65 241	99.80 233	99.78 6	98.88 272	98.59 216	95.31 246	97.73 284

CDS-MVSNet		98.96 138	98.95 128	99.01 187	99.48 222	98.36 211	99.93 236	99.37 203	96.79 203	99.31 200	99.83 224	99.77 8	98.91 266	98.07 237	97.98 205	99.77 206
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
PAPM		99.78 17	99.76 13	99.85 96	99.01 266	99.95 34	100.00 1	99.75 52	99.37 3	99.99 105	100.00 1	99.76 9	99.60 199	100.00 1	100.00 1	100.00 1

DP-MVS Recon		99.76 20	99.69 24	99.98 25	100.00 1	99.95 34	100.00 1	99.52 72	97.99 101	99.99 105	100.00 1	99.72 10	100.00 1	99.96 90	100.00 1	100.00 1

TESTMET0.1,1		99.08 120	98.96 124	99.44 150	99.63 179	99.38 143	100.00 1	99.45 102	95.53 258	99.48 189	100.00 1	99.71 11	99.02 255	96.84 275	99.99 113	99.91 144

test-mter		98.96 138	98.82 139	99.40 157	99.40 238	99.28 152	100.00 1	99.45 102	95.44 267	99.42 193	99.12 301	99.70 12	99.01 257	96.82 276	99.99 113	99.91 144

MSP-MVS		99.81 11	99.77 10	99.94 76	100.00 1	99.86 89	100.00 1	99.42 130	98.87 40	100.00 1	100.00 1	99.65 13	99.96 137	100.00 1	100.00 1	100.00 1
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
test_0728_THIRD									98.79 48	100.00 1	100.00 1	99.61 14	100.00 1	100.00 1	100.00 1	100.00 1

test_one_0601					100.00 1	99.99 5		99.42 130	98.72 52	100.00 1	100.00 1	99.60 15

MSLP-MVS++		99.89 1	99.85 2	99.99 12	100.00 1	99.96 25	100.00 1	99.95 18	99.11 7	100.00 1	100.00 1	99.60 15	100.00 1	100.00 1	100.00 1	100.00 1

PAPM_NR		99.74 27	99.66 35	99.99 12	100.00 1	99.96 25	100.00 1	99.47 80	97.87 116	100.00 1	100.00 1	99.60 15	100.00 1	100.00 1	100.00 1	100.00 1

NCCC		99.86 2	99.82 3	100.00 1	100.00 1	99.99 5	100.00 1	99.71 63	99.07 9	100.00 1	100.00 1	99.59 18	100.00 1	100.00 1	100.00 1	100.00 1

PLC	98.56 2	99.70 40	99.74 17	99.58 137	100.00 1	98.79 187	100.00 1	99.54 70	98.58 60	99.96 118	100.00 1	99.59 18	100.00 1	100.00 1	100.00 1	99.94 130
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
DPM-MVS		99.63 63	99.51 73	100.00 1	99.90 122	100.00 1	100.00 1	99.43 122	99.00 25	100.00 1	100.00 1	99.58 20	100.00 1	97.64 252	100.00 1	100.00 1

test_241102_TWO								99.42 130	99.03 19	100.00 1	100.00 1	99.56 21	100.00 1	100.00 1	100.00 1	100.00 1

APDe-MVS		99.84 6	99.78 7	99.99 12	100.00 1	99.98 17	100.00 1	99.44 112	99.06 11	100.00 1	100.00 1	99.56 21	99.99 94	100.00 1	100.00 1	100.00 1

segment_acmp												99.55 23

DVP-MVS++		99.81 11	99.75 15	100.00 1	100.00 1	99.99 5	100.00 1	99.42 130	98.79 48	100.00 1	100.00 1	99.54 24	100.00 1	100.00 1	100.00 1	100.00 1

PC_three_1452									98.80 46	100.00 1	100.00 1	99.54 24	100.00 1	100.00 1	100.00 1	100.00 1

OPU-MVS				100.00 1	100.00 1	100.00 1	100.00 1				100.00 1	99.54 24	100.00 1	100.00 1	100.00 1	100.00 1

DVP-MVS		99.83 7	99.78 7	100.00 1	100.00 1	99.99 5	100.00 1	99.42 130	99.04 14	100.00 1	100.00 1	99.53 27	100.00 1	100.00 1	100.00 1	100.00 1
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
test0726					100.00 1	99.99 5	100.00 1	99.42 130	99.04 14	100.00 1	100.00 1	99.53 27

TEST9					100.00 1	99.95 34	100.00 1	99.42 130	97.65 134	100.00 1	100.00 1	99.53 27	99.97 123

DWT-MVSNet_test		99.22 114	99.22 104	99.22 177	99.56 200	97.98 236	99.89 243	99.39 198	97.20 182	99.96 118	100.00 1	99.52 30	99.82 176	99.11 188	98.34 187	99.87 177

SteuartSystems-ACMMP		99.78 17	99.71 21	99.98 25	99.76 154	99.95 34	100.00 1	99.42 130	98.69 53	100.00 1	100.00 1	99.52 30	99.99 94	100.00 1	100.00 1	100.00 1
Skip Steuart: Steuart Systems R&D Blog.
train_agg		99.71 36	99.63 44	99.97 34	100.00 1	99.95 34	100.00 1	99.42 130	97.70 129	100.00 1	100.00 1	99.51 32	99.97 123	100.00 1	100.00 1	100.00 1

test_8					100.00 1	99.91 57	100.00 1	99.42 130	97.70 129	100.00 1	100.00 1	99.51 32	99.98 118

agg_prior1		99.71 36	99.63 44	99.95 61	100.00 1	99.88 83	100.00 1	99.42 130	97.72 125	100.00 1	100.00 1	99.51 32	99.97 123	100.00 1	100.00 1	100.00 1

PAPR		99.76 20	99.68 27	99.99 12	100.00 1	99.96 25	100.00 1	99.47 80	98.16 86	100.00 1	100.00 1	99.51 32	100.00 1	100.00 1	100.00 1	100.00 1

EPP-MVSNet		99.10 119	99.00 120	99.40 157	99.51 216	98.68 195	99.92 237	99.43 122	95.47 264	99.65 182	100.00 1	99.51 32	99.76 187	99.53 162	98.00 204	99.75 209

SED-MVS		99.83 7	99.77 10	100.00 1	100.00 1	99.99 5	100.00 1	99.42 130	99.03 19	100.00 1	100.00 1	99.50 37	100.00 1	100.00 1	100.00 1	100.00 1

test_241102_ONE					100.00 1	99.99 5		99.42 130	99.03 19	100.00 1	100.00 1	99.50 37	100.00 1

miper_enhance_ethall		98.33 181	98.27 177	98.51 214	99.66 171	99.04 172	100.00 1	99.22 268	97.53 152	98.51 252	99.38 291	99.49 39	98.75 284	98.02 239	92.61 286	97.76 243

test_post											89.05 368	99.49 39	99.59 201

HyFIR lowres test		99.32 100	99.24 100	99.58 137	99.95 110	99.26 154	100.00 1	99.99 13	96.72 209	99.29 201	99.91 213	99.49 39	99.47 230	99.74 126	98.08 203	100.00 1

PatchmatchNet		99.03 126	98.96 124	99.26 173	99.49 220	98.33 213	99.38 312	99.45 102	96.64 217	99.96 118	99.58 274	99.49 39	99.50 226	97.63 253	99.00 162	99.93 140
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
Patchmatch-test		97.83 200	97.42 211	99.06 181	99.08 257	97.66 253	98.66 356	99.21 273	93.65 307	98.25 270	99.58 274	99.47 43	99.57 205	90.25 342	98.59 172	99.95 125

test_prior3		99.81 11	99.78 7	99.90 85	100.00 1	99.75 106	100.00 1	99.73 57	98.82 44	100.00 1	100.00 1	99.47 43	99.97 123	100.00 1	100.00 1	100.00 1

test_prior2							100.00 1		98.82 44	100.00 1	100.00 1	99.47 43		100.00 1	100.00 1

TSAR-MVS + MP.		99.82 9	99.77 10	99.99 12	100.00 1	99.96 25	100.00 1	99.43 122	99.05 13	100.00 1	100.00 1	99.45 46	99.99 94	100.00 1	100.00 1	100.00 1
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
thisisatest0530		99.37 92	99.27 94	99.69 121	99.59 189	99.41 141	100.00 1	99.46 95	96.46 226	99.90 152	100.00 1	99.44 47	99.85 170	98.97 192	99.58 152	99.80 203

tttt0517		99.34 96	99.23 103	99.67 123	99.57 197	99.38 143	100.00 1	99.46 95	96.33 234	99.89 155	100.00 1	99.44 47	99.84 172	98.93 194	99.46 155	99.78 205

thisisatest0515		99.42 87	99.31 93	99.74 117	99.59 189	99.55 126	100.00 1	99.46 95	96.65 216	99.92 149	100.00 1	99.44 47	99.85 170	99.09 189	99.63 150	99.81 193

PGM-MVS		99.69 44	99.61 49	99.95 61	99.99 59	99.85 92	100.00 1	99.58 68	97.69 131	100.00 1	100.00 1	99.44 47	100.00 1	99.79 118	100.00 1	100.00 1

SMA-MVS		99.69 44	99.59 52	99.98 25	99.99 59	99.93 47	100.00 1	99.43 122	97.50 156	100.00 1	100.00 1	99.43 51	100.00 1	100.00 1	100.00 1	100.00 1
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
原ACMM1				99.93 79	100.00 1	99.80 100		99.66 65	98.18 85	100.00 1	100.00 1	99.43 51	100.00 1	99.50 164	100.00 1	100.00 1

testdata				99.66 125	99.99 59	98.97 182		99.73 57	97.96 109	100.00 1	100.00 1	99.42 53	100.00 1	99.28 179	100.00 1	100.00 1

baseline2		98.99 134	98.93 130	99.18 179	99.26 250	99.15 165	100.00 1	99.46 95	96.71 210	96.79 319	100.00 1	99.42 53	99.25 247	98.75 205	99.94 129	99.15 231

patchmatchnet-post											97.79 348	99.41 55	99.54 217

Patchmatch-RL test		93.49 310	93.63 307	93.05 340	91.78 365	83.41 365	98.21 361	96.95 369	91.58 334	91.05 355	97.64 351	99.40 56	95.83 359	94.11 314	81.95 353	99.91 144

1121		99.63 63	99.51 73	99.99 12	99.99 59	99.96 25	99.24 323	99.74 55	97.89 113	100.00 1	100.00 1	99.39 57	100.00 1	99.33 174	100.00 1	100.00 1

CNVR-MVS		99.85 3	99.80 4	100.00 1	100.00 1	99.99 5	100.00 1	99.77 47	99.07 9	100.00 1	100.00 1	99.39 57	100.00 1	100.00 1	100.00 1	100.00 1

sam_mvs												99.33 59

test_post1							99.32 317				88.24 370	99.33 59	99.59 201	98.31 227

SD-MVS		99.81 11	99.75 15	99.99 12	99.99 59	99.96 25	100.00 1	99.42 130	99.01 24	100.00 1	100.00 1	99.33 59	100.00 1	100.00 1	100.00 1	100.00 1
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
ZD-MVS					100.00 1	99.98 17		99.80 42	97.31 173	100.00 1	100.00 1	99.32 62	99.99 94	100.00 1	100.00 1

CDPH-MVS		99.73 30	99.64 40	99.99 12	100.00 1	99.97 22	100.00 1	99.42 130	98.02 99	100.00 1	100.00 1	99.32 62	99.99 94	100.00 1	100.00 1	100.00 1

HFP-MVS		99.74 27	99.67 32	99.96 49	100.00 1	99.89 73	100.00 1	99.76 48	97.95 110	100.00 1	100.00 1	99.31 64	100.00 1	99.99 64	100.00 1	100.00 1

#test#		99.75 22	99.68 27	99.96 49	100.00 1	99.89 73	100.00 1	99.76 48	98.07 96	100.00 1	100.00 1	99.31 64	100.00 1	99.99 64	100.00 1	100.00 1

test-LLR		99.03 126	98.91 132	99.40 157	99.40 238	99.28 152	100.00 1	99.45 102	96.70 211	99.42 193	99.12 301	99.31 64	99.01 257	96.82 276	99.99 113	99.91 144

test0.0.03 1		98.12 191	98.03 192	98.39 220	99.11 254	98.07 230	100.00 1	99.93 29	96.70 211	96.91 315	99.95 204	99.31 64	98.19 319	91.93 329	98.44 179	98.91 234

MCST-MVS		99.85 3	99.80 4	100.00 1	100.00 1	99.99 5	100.00 1	99.73 57	99.19 5	100.00 1	100.00 1	99.31 64	100.00 1	100.00 1	100.00 1	100.00 1

TAPA-MVS	96.40 10	97.64 206	97.37 215	98.45 217	99.94 113	95.70 294	100.00 1	99.40 185	97.65 134	99.53 186	100.00 1	99.31 64	99.66 197	80.48 364	100.00 1	100.00 1
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
test222					99.99 59	99.90 65	100.00 1	99.69 64	97.66 133	100.00 1	100.00 1	99.30 70			100.00 1	100.00 1

sam_mvs1												99.29 71				99.91 144

ACMMPR		99.74 27	99.67 32	99.96 49	100.00 1	99.89 73	100.00 1	99.76 48	97.95 110	100.00 1	100.00 1	99.29 71	100.00 1	99.99 64	100.00 1	100.00 1

CostFormer		98.84 149	98.77 144	99.04 185	99.41 233	97.58 255	99.67 281	99.35 217	94.66 280	99.96 118	99.36 292	99.28 73	99.74 190	99.41 168	97.81 215	99.81 193

旧先验1					99.99 59	99.88 83		99.82 39			100.00 1	99.27 74			100.00 1	100.00 1

APD-MVS		99.68 48	99.58 56	99.97 34	99.99 59	99.96 25	100.00 1	99.42 130	97.53 152	100.00 1	100.00 1	99.27 74	99.97 123	100.00 1	100.00 1	100.00 1
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
RRT_test8_iter05		98.32 182	98.23 181	98.60 209	99.65 172	99.23 161	100.00 1	99.09 315	95.65 252	98.07 276	99.93 211	99.25 76	98.82 275	98.90 196	93.50 276	97.75 254

test12				99.95 61	99.99 59	99.89 73		99.42 130		100.00 1		99.24 77	99.97 123		100.00 1	100.00 1

testtj		99.70 40	99.61 49	99.99 12	100.00 1	99.98 17	100.00 1	99.53 71	97.71 128	100.00 1	100.00 1	99.23 78	100.00 1	100.00 1	100.00 1	100.00 1

Regformer-1		99.75 22	99.68 27	99.98 25	100.00 1	99.94 42	100.00 1	99.44 112	98.43 65	100.00 1	100.00 1	99.23 78	99.99 94	99.99 64	100.00 1	100.00 1

DPE-MVS		99.79 15	99.73 18	99.99 12	99.99 59	99.98 17	100.00 1	99.42 130	98.91 36	100.00 1	100.00 1	99.22 80	100.00 1	100.00 1	100.00 1	100.00 1
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
Regformer-2		99.75 22	99.68 27	99.97 34	100.00 1	99.94 42	100.00 1	99.44 112	98.42 67	100.00 1	100.00 1	99.22 80	99.99 94	99.99 64	100.00 1	100.00 1

HPM-MVS++		99.82 9	99.76 13	99.99 12	99.99 59	99.98 17	100.00 1	99.83 38	98.88 38	99.96 118	100.00 1	99.21 82	100.00 1	100.00 1	100.00 1	99.99 110

新几何1				99.99 12	100.00 1	99.96 25		99.81 41	97.89 113	100.00 1	100.00 1	99.20 83	100.00 1	97.91 245	100.00 1	100.00 1

region2R		99.72 33	99.64 40	99.97 34	100.00 1	99.90 65	100.00 1	99.74 55	97.86 117	100.00 1	100.00 1	99.19 84	100.00 1	99.99 64	100.00 1	100.00 1

F-COLMAP		99.64 59	99.64 40	99.67 123	99.99 59	99.07 168	100.00 1	99.44 112	98.30 81	99.90 152	100.00 1	99.18 85	99.99 94	99.91 101	100.00 1	99.94 130

XVS		99.79 15	99.73 18	99.98 25	100.00 1	99.94 42	100.00 1	99.75 52	98.67 55	100.00 1	100.00 1	99.16 86	100.00 1	100.00 1	100.00 1	100.00 1

X-MVStestdata		97.04 234	96.06 261	99.98 25	100.00 1	99.94 42	100.00 1	99.75 52	98.67 55	100.00 1	66.97 377	99.16 86	100.00 1	100.00 1	100.00 1	100.00 1

9.14			99.57 59		99.99 59		100.00 1	99.42 130	97.54 150	100.00 1	100.00 1	99.15 88	99.99 94	100.00 1	100.00 1

CNLPA		99.72 33	99.65 36	99.91 82	99.97 103	99.72 111	100.00 1	99.47 80	98.43 65	99.88 157	100.00 1	99.14 89	100.00 1	99.97 88	100.00 1	100.00 1

ETH3D-3000-0.1		99.66 55	99.57 59	99.95 61	99.99 59	99.85 92	100.00 1	99.42 130	97.58 146	100.00 1	100.00 1	99.12 90	99.99 94	100.00 1	100.00 1	100.00 1

Test By Simon												99.10 91

CP-MVS		99.67 53	99.58 56	99.95 61	100.00 1	99.84 95	100.00 1	99.42 130	97.77 122	100.00 1	100.00 1	99.07 92	100.00 1	100.00 1	100.00 1	100.00 1

alignmvs		99.38 90	99.21 105	99.91 82	99.73 157	99.92 54	100.00 1	99.51 76	97.61 140	100.00 1	100.00 1	99.06 93	99.93 156	99.83 112	97.12 226	99.90 153

xxxxxxxxxxxxxcwj		99.77 19	99.70 22	99.97 34	99.99 59	99.93 47	100.00 1	99.31 231	98.93 33	100.00 1	100.00 1	99.05 94	99.99 94	100.00 1	100.00 1	100.00 1

SF-MVS		99.66 55	99.57 59	99.95 61	99.99 59	99.85 92	100.00 1	99.42 130	97.67 132	100.00 1	100.00 1	99.05 94	99.99 94	100.00 1	100.00 1	100.00 1

EPMVS		99.25 111	99.13 113	99.60 131	99.60 186	99.20 162	99.60 290	100.00 1	96.93 195	99.92 149	99.36 292	99.05 94	99.71 194	98.77 203	98.94 163	99.90 153

RRT_MVS		98.48 172	98.41 169	98.70 205	99.64 177	99.67 119	100.00 1	99.10 309	96.26 237	98.75 236	99.96 197	99.04 97	98.75 284	98.42 221	94.51 269	97.68 304

EI-MVSNet-Vis-set		99.70 40	99.64 40	99.87 93	100.00 1	99.64 122	99.98 215	99.44 112	98.35 77	99.99 105	100.00 1	99.04 97	99.96 137	99.98 81	100.00 1	100.00 1

mPP-MVS		99.69 44	99.60 51	99.97 34	100.00 1	99.91 57	100.00 1	99.42 130	97.91 112	100.00 1	100.00 1	99.04 97	100.00 1	100.00 1	100.00 1	100.00 1

tpmrst		98.98 137	98.93 130	99.14 180	99.61 184	97.74 250	99.52 298	99.36 209	96.05 241	99.98 110	99.64 261	99.04 97	99.86 165	98.94 193	98.19 198	99.82 188

Regformer-3		99.73 30	99.65 36	99.96 49	100.00 1	99.89 73	100.00 1	99.44 112	98.40 68	100.00 1	100.00 1	99.03 101	99.97 123	99.99 64	100.00 1	100.00 1

Regformer-4		99.73 30	99.65 36	99.95 61	100.00 1	99.89 73	100.00 1	99.44 112	98.40 68	100.00 1	100.00 1	99.03 101	99.97 123	99.99 64	100.00 1	100.00 1

SR-MVS		99.68 48	99.58 56	99.98 25	100.00 1	99.95 34	100.00 1	99.64 66	97.59 144	100.00 1	100.00 1	98.99 103	99.99 94	100.00 1	100.00 1	100.00 1

ETH3D cwj APD-0.16		99.63 63	99.53 68	99.94 76	99.97 103	99.82 97	100.00 1	99.42 130	97.39 164	100.00 1	100.00 1	98.98 104	99.99 94	100.00 1	100.00 1	100.00 1

EI-MVSNet-UG-set		99.69 44	99.63 44	99.87 93	99.99 59	99.64 122	99.95 230	99.44 112	98.35 77	100.00 1	100.00 1	98.98 104	99.97 123	99.98 81	100.00 1	100.00 1

ZNCC-MVS		99.71 36	99.62 48	99.97 34	99.99 59	99.90 65	100.00 1	99.79 44	97.97 105	99.97 114	100.00 1	98.97 106	100.00 1	99.94 98	100.00 1	100.00 1

APD-MVS_3200maxsize		99.65 57	99.55 66	99.97 34	99.99 59	99.91 57	100.00 1	99.48 79	97.54 150	100.00 1	100.00 1	98.97 106	99.99 94	99.98 81	100.00 1	100.00 1

EPNet		99.62 67	99.69 24	99.42 154	99.99 59	98.37 209	100.00 1	99.89 35	98.83 42	100.00 1	100.00 1	98.97 106	100.00 1	99.90 102	99.61 151	99.89 158
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
tpm2		98.64 161	98.58 161	98.81 201	99.42 231	97.12 272	99.69 278	99.37 203	93.63 308	99.94 143	99.67 253	98.96 109	99.47 230	98.62 214	97.95 206	99.83 184

TSAR-MVS + GP.		99.61 69	99.69 24	99.35 162	99.99 59	98.06 231	100.00 1	99.36 209	99.83 2	100.00 1	100.00 1	98.95 110	99.99 94	100.00 1	99.11 158	100.00 1

HPM-MVS_fast		99.60 72	99.49 77	99.91 82	99.99 59	99.78 101	100.00 1	99.42 130	97.09 187	100.00 1	100.00 1	98.95 110	99.96 137	99.98 81	100.00 1	100.00 1

RE-MVS-def			99.55 66		99.99 59	99.91 57	100.00 1	99.42 130	97.62 138	100.00 1	100.00 1	98.94 112		99.99 64	100.00 1	100.00 1

WTY-MVS		99.54 74	99.40 80	99.95 61	99.81 134	99.93 47	100.00 1	100.00 1	97.98 103	99.84 160	100.00 1	98.94 112	99.98 118	99.86 107	98.21 196	99.94 130

HY-MVS	96.53 9	99.50 79	99.35 90	99.96 49	99.81 134	99.93 47	99.64 283	100.00 1	97.97 105	99.84 160	99.85 221	98.94 112	99.99 94	99.86 107	98.23 195	99.95 125

MDTV_nov1_ep13			98.94 129		99.53 204	98.36 211	99.39 311	99.46 95	96.54 222	99.99 105	99.63 265	98.92 115	99.86 165	98.30 229	98.71 170

API-MVS		99.72 33	99.70 22	99.79 109	99.97 103	99.37 146	99.96 225	99.94 21	98.48 63	100.00 1	100.00 1	98.92 115	100.00 1	100.00 1	100.00 1	100.00 1

ETH3 D test6400		99.68 48	99.59 52	99.97 34	99.99 59	99.93 47	100.00 1	99.42 130	97.97 105	100.00 1	100.00 1	98.90 117	99.99 94	100.00 1	100.00 1	100.00 1

ACMMP		99.65 57	99.57 59	99.89 88	99.99 59	99.66 120	99.75 266	99.73 57	98.16 86	99.75 177	100.00 1	98.90 117	100.00 1	99.96 90	99.88 134	100.00 1
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
ACMMP_NAP		99.67 53	99.57 59	99.97 34	99.98 99	99.92 54	100.00 1	99.42 130	97.83 118	100.00 1	100.00 1	98.89 119	100.00 1	99.98 81	100.00 1	100.00 1

test2506		99.48 83	99.38 83	99.75 116	99.89 124	99.51 129	99.45 304	100.00 1	98.38 71	99.83 162	100.00 1	98.86 120	99.81 180	99.25 180	98.78 166	99.94 130

MDTV_nov1_ep13_2view						99.24 158	99.56 293		96.31 235	99.96 118		98.86 120		98.92 195		99.89 158

KD-MVS_2432*1600		94.15 305	93.08 312	97.35 281	99.53 204	97.83 247	99.63 285	99.19 277	92.88 324	96.29 326	97.68 349	98.84 122	96.70 348	89.73 344	63.92 367	97.53 329

miper_refine_blended		94.15 305	93.08 312	97.35 281	99.53 204	97.83 247	99.63 285	99.19 277	92.88 324	96.29 326	97.68 349	98.84 122	96.70 348	89.73 344	63.92 367	97.53 329

dp		98.72 155	98.61 157	99.03 186	99.53 204	97.39 260	99.45 304	99.39 198	95.62 255	99.94 143	99.52 282	98.83 124	99.82 176	96.77 281	98.42 181	99.89 158

TAMVS		98.76 153	98.73 147	98.86 197	99.44 230	97.69 251	99.57 292	99.34 222	96.57 220	99.12 211	99.81 230	98.83 124	99.16 249	97.97 244	97.91 208	99.73 214

IB-MVS	96.24 12	97.54 213	96.95 226	99.33 164	99.67 167	98.10 229	100.00 1	99.47 80	97.42 163	99.26 202	99.69 248	98.83 124	99.89 161	99.43 166	78.77 358	100.00 1
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
DeepC-MVS_fast	98.92 1	99.75 22	99.67 32	99.99 12	99.99 59	99.96 25	99.73 271	99.52 72	99.06 11	100.00 1	100.00 1	98.80 127	100.00 1	99.95 96	100.00 1	100.00 1
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
MP-MVS-pluss		99.61 69	99.50 75	99.97 34	99.98 99	99.92 54	100.00 1	99.42 130	97.53 152	99.77 174	100.00 1	98.77 128	100.00 1	99.99 64	100.00 1	99.99 110
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
pcd_1.5k_mvsjas		8.24 347	10.99 350	0.00 361	0.00 384	0.00 385	0.00 372	0.00 385	0.00 379	0.00 380	0.14 380	98.75 129	0.00 380	0.00 378	0.00 378	0.00 376

PS-MVSNAJss		98.03 194	98.06 191	97.94 262	97.63 328	97.33 265	99.89 243	99.23 266	96.27 236	98.03 278	99.59 273	98.75 129	98.78 279	98.52 218	94.61 267	97.70 298

PS-MVSNAJ		99.64 59	99.57 59	99.85 96	99.78 149	99.81 98	99.95 230	99.42 130	98.38 71	100.00 1	100.00 1	98.75 129	100.00 1	99.88 105	99.99 113	99.74 210

dcpmvs_2		98.87 147	99.53 68	96.90 300	99.87 128	90.88 352	99.94 234	99.07 321	98.20 84	100.00 1	100.00 1	98.69 132	99.86 165	100.00 1	100.00 1	99.95 125

test1172		99.64 59	99.53 68	99.96 49	100.00 1	99.90 65	100.00 1	99.51 76	97.59 144	100.00 1	100.00 1	98.65 133	99.99 94	99.99 64	100.00 1	100.00 1

SR-MVS-dyc-post		99.63 63	99.52 72	99.97 34	99.99 59	99.91 57	100.00 1	99.42 130	97.62 138	100.00 1	100.00 1	98.65 133	99.99 94	99.99 64	100.00 1	100.00 1

zzz-MVS		99.68 48	99.59 52	99.97 34	99.99 59	99.91 57	100.00 1	99.42 130	98.32 79	99.94 143	100.00 1	98.65 133	100.00 1	99.96 90	100.00 1	100.00 1

MTAPA		99.68 48	99.59 52	99.97 34	99.99 59	99.91 57	100.00 1	99.42 130	98.32 79	99.94 143	100.00 1	98.65 133	100.00 1	99.96 90	100.00 1	100.00 1

HPM-MVS		99.59 73	99.50 75	99.89 88	100.00 1	99.70 116	100.00 1	99.42 130	97.46 159	100.00 1	100.00 1	98.60 137	99.96 137	99.99 64	100.00 1	100.00 1
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
MG-MVS		99.75 22	99.68 27	99.97 34	100.00 1	99.91 57	99.98 215	99.47 80	99.09 8	100.00 1	100.00 1	98.59 138	100.00 1	99.95 96	100.00 1	100.00 1

EPNet_dtu		98.53 169	98.23 181	99.43 152	99.92 118	99.01 176	99.96 225	99.47 80	98.80 46	99.96 118	99.96 197	98.56 139	99.30 245	87.78 351	99.68 145	100.00 1
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
JIA-IIPM		97.09 230	96.34 251	99.36 161	98.88 281	98.59 199	99.81 253	99.43 122	84.81 358	99.96 118	90.34 367	98.55 140	99.52 223	97.00 270	98.28 193	99.98 112

xiu_mvs_v2_base		99.51 76	99.41 79	99.82 100	99.70 160	99.73 110	99.92 237	99.40 185	98.15 88	100.00 1	100.00 1	98.50 141	100.00 1	99.85 109	99.13 157	99.74 210

sss		99.45 85	99.34 92	99.80 107	99.76 154	99.50 130	100.00 1	99.91 34	97.72 125	99.98 110	99.94 208	98.45 142	100.00 1	99.53 162	98.75 169	99.89 158

IS-MVSNet		99.08 120	98.91 132	99.59 133	99.65 172	99.38 143	99.78 258	99.24 262	96.70 211	99.51 187	100.00 1	98.44 143	99.52 223	98.47 220	98.39 184	99.88 169

GST-MVS		99.64 59	99.53 68	99.95 61	100.00 1	99.86 89	100.00 1	99.79 44	97.72 125	99.95 141	100.00 1	98.39 144	100.00 1	99.96 90	99.99 113	100.00 1

114514_t		99.39 89	99.25 98	99.81 103	99.97 103	99.48 137	100.00 1	99.42 130	95.53 258	100.00 1	100.00 1	98.37 145	99.95 143	99.97 88	100.00 1	100.00 1

baseline1		98.91 143	98.61 157	99.81 103	99.71 158	99.77 102	99.78 258	99.44 112	97.51 155	98.81 233	99.99 177	98.25 146	99.76 187	98.60 215	95.41 242	99.89 158

MP-MVS		99.61 69	99.49 77	99.98 25	99.99 59	99.94 42	100.00 1	99.42 130	97.82 119	99.99 105	100.00 1	98.20 147	100.00 1	99.99 64	100.00 1	100.00 1
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
miper_ehance_all_eth		97.81 201	97.66 205	98.23 231	99.49 220	98.37 209	99.99 197	99.11 307	94.78 275	98.25 270	99.21 298	98.18 148	98.57 300	97.35 263	92.61 286	97.76 243

PHI-MVS		99.50 79	99.39 82	99.82 100	100.00 1	99.45 138	100.00 1	99.94 21	96.38 231	100.00 1	100.00 1	98.18 148	100.00 1	100.00 1	100.00 1	100.00 1

abl_6		99.53 75	99.40 80	99.92 81	100.00 1	99.76 104	100.00 1	99.42 130	97.21 181	100.00 1	100.00 1	98.12 150	100.00 1	99.82 117	100.00 1	100.00 1

Vis-MVSNet (Re-imp)		98.99 134	98.89 136	99.29 168	99.64 177	98.89 184	99.98 215	99.31 231	96.74 206	99.48 189	100.00 1	98.11 151	99.10 251	98.39 223	98.34 187	99.89 158

DeepPCF-MVS	98.03 4	98.54 168	99.72 20	94.98 326	99.99 59	84.94 363	100.00 1	99.42 130	99.98 1	100.00 1	100.00 1	98.11 151	100.00 1	100.00 1	100.00 1	100.00 1

cl22		98.23 189	98.11 187	98.58 213	99.82 130	99.01 176	100.00 1	99.28 244	96.92 197	98.33 262	99.21 298	98.09 153	98.97 262	98.72 206	92.61 286	97.76 243

PatchT		95.90 288	94.95 300	98.75 203	99.03 264	98.39 206	99.08 348	99.32 226	85.52 356	99.96 118	94.99 361	97.94 154	98.05 335	80.20 365	98.47 178	99.81 193

MVS_111021_LR		99.70 40	99.65 36	99.88 92	99.96 109	99.70 116	100.00 1	99.97 17	98.96 28	100.00 1	100.00 1	97.93 155	99.95 143	99.99 64	100.00 1	100.00 1

c3_l		97.58 210	97.42 211	98.06 249	99.48 222	98.16 223	99.96 225	99.10 309	94.54 284	98.13 274	99.20 300	97.87 156	98.25 318	97.28 264	91.20 309	97.75 254

MVS_111021_HR		99.71 36	99.63 44	99.93 79	99.95 110	99.83 96	100.00 1	100.00 1	98.89 37	100.00 1	100.00 1	97.85 157	99.95 143	100.00 1	100.00 1	100.00 1

CSCG		99.28 105	99.35 90	99.05 183	99.99 59	97.15 271	100.00 1	99.47 80	97.44 161	99.42 193	100.00 1	97.83 158	100.00 1	99.99 64	100.00 1	100.00 1

CS-MVS		99.33 98	99.27 94	99.50 144	99.99 59	99.00 178	100.00 1	99.13 300	97.26 176	99.96 118	100.00 1	97.79 159	99.64 198	99.64 147	99.67 146	99.87 177

ET-MVSNet_ETH3D		96.41 261	95.48 290	99.20 178	99.81 134	99.75 106	100.00 1	99.02 336	97.30 175	78.33 367	100.00 1	97.73 160	97.94 339	99.70 133	87.41 339	99.92 142

tpm cat1		98.05 193	97.76 200	98.92 193	99.50 219	97.10 274	99.77 263	99.30 234	90.20 343	99.72 179	98.71 329	97.71 161	99.86 165	96.75 282	98.20 197	99.81 193

DELS-MVS		99.62 67	99.56 65	99.82 100	99.92 118	99.45 138	100.00 1	99.78 46	98.92 35	99.73 178	100.00 1	97.70 162	100.00 1	99.93 99	100.00 1	100.00 1
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
DIV-MVS_self_test		97.52 215	97.35 216	98.05 253	99.46 227	98.11 227	100.00 1	99.10 309	94.21 295	97.62 296	99.63 265	97.65 163	98.29 316	96.47 283	91.98 297	97.76 243

tpmvs		98.59 163	98.38 172	99.23 175	99.69 161	97.90 241	99.31 318	99.47 80	94.52 285	99.68 181	99.28 296	97.64 164	99.89 161	97.71 250	98.17 200	99.89 158

tpm		98.24 188	98.22 183	98.32 226	99.13 253	95.79 293	99.53 297	99.12 306	95.20 268	99.96 118	99.36 292	97.58 165	99.28 246	97.41 260	96.67 233	99.88 169

ADS-MVSNet2		98.28 186	98.51 165	97.62 273	99.51 216	95.03 302	99.24 323	99.41 182	95.52 260	99.96 118	99.70 246	97.57 166	97.94 339	97.11 267	98.54 173	99.88 169

ADS-MVSNet		98.70 157	98.51 165	99.28 171	99.51 216	98.39 206	99.24 323	99.44 112	95.52 260	99.96 118	99.70 246	97.57 166	99.58 204	97.11 267	98.54 173	99.88 169

CS-MVS-test		99.31 101	99.27 94	99.43 152	99.99 59	98.77 188	100.00 1	99.19 277	97.24 177	99.96 118	100.00 1	97.56 168	99.70 195	99.68 140	99.81 140	99.82 188

cl____		97.54 213	97.32 217	98.18 235	99.47 225	98.14 226	100.00 1	99.10 309	94.16 298	97.60 298	99.63 265	97.52 169	98.65 291	96.47 283	91.97 298	97.76 243

h-mvs33		97.03 235	96.53 239	98.51 214	99.79 147	95.90 292	99.45 304	99.45 102	98.21 82	100.00 1	99.78 236	97.49 170	99.99 94	99.72 129	74.92 360	99.65 222

hse-mvs2		96.79 243	96.38 247	98.04 255	99.68 164	95.54 296	99.81 253	99.42 130	98.21 82	100.00 1	99.80 233	97.49 170	99.46 234	99.72 129	73.27 363	99.12 232

EIA-MVS		99.26 108	99.19 109	99.45 149	99.63 179	98.75 189	100.00 1	99.27 252	96.93 195	99.95 141	100.00 1	97.47 172	99.79 182	99.74 126	99.72 144	99.82 188

Test_1112_low_res		98.83 150	98.60 159	99.51 142	99.69 161	98.75 189	99.99 197	99.14 296	96.81 202	98.84 230	99.06 305	97.45 173	99.89 161	98.66 208	97.75 218	99.89 158

1112_ss		98.91 143	98.71 150	99.51 142	99.69 161	98.75 189	99.99 197	99.15 291	96.82 201	98.84 230	100.00 1	97.45 173	99.89 161	98.66 208	97.75 218	99.89 158

ETV-MVS		99.34 96	99.24 100	99.64 126	99.58 194	99.33 148	100.00 1	99.25 257	97.57 148	99.96 118	100.00 1	97.44 175	99.79 182	99.70 133	99.65 148	99.81 193

CPTT-MVS		99.49 81	99.38 83	99.85 96	100.00 1	99.54 127	100.00 1	99.42 130	97.58 146	99.98 110	100.00 1	97.43 176	100.00 1	99.99 64	100.00 1	100.00 1

miper_lstm_enhance		97.40 218	97.28 219	97.75 270	99.48 222	97.52 256	100.00 1	99.07 321	94.08 299	98.01 281	99.61 271	97.38 177	97.98 337	96.44 286	91.47 306	97.76 243

EI-MVSNet		97.98 196	97.93 196	98.16 238	99.11 254	97.84 246	99.74 267	99.29 239	94.39 291	98.65 241	100.00 1	97.21 178	98.88 272	97.62 254	95.31 246	97.75 254

IterMVS-LS		97.56 211	97.44 210	97.92 265	99.38 242	97.90 241	99.89 243	99.10 309	94.41 290	98.32 263	99.54 281	97.21 178	98.11 326	97.50 256	91.62 302	97.75 254
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
tfpn200view9		99.26 108	99.03 117	99.96 49	99.81 134	99.89 73	100.00 1	99.94 21	97.23 178	99.83 162	99.96 197	97.04 180	100.00 1	99.59 152	97.85 211	99.98 112

thres400		99.26 108	99.03 117	99.95 61	99.81 134	99.89 73	100.00 1	99.94 21	97.23 178	99.83 162	99.96 197	97.04 180	100.00 1	99.59 152	97.85 211	99.97 117

thres200		99.27 106	99.04 116	99.96 49	99.81 134	99.90 65	100.00 1	99.94 21	97.31 173	99.83 162	99.96 197	97.04 180	100.00 1	99.62 151	97.88 209	99.98 112

1314		99.38 90	99.19 109	99.96 49	98.88 281	99.89 73	99.24 323	99.93 29	98.88 38	98.79 235	100.00 1	97.02 183	100.00 1	100.00 1	100.00 1	100.00 1

thres100view900		99.25 111	99.01 119	99.95 61	99.81 134	99.87 86	100.00 1	99.94 21	97.13 185	99.83 162	99.96 197	97.01 184	100.00 1	99.59 152	97.85 211	99.98 112

thres600view7		99.24 113	99.00 120	99.95 61	99.81 134	99.87 86	100.00 1	99.94 21	97.13 185	99.83 162	99.96 197	97.01 184	100.00 1	99.54 160	97.77 217	99.97 117

OMC-MVS		99.27 106	99.38 83	98.96 191	99.95 110	97.06 275	100.00 1	99.40 185	98.83 42	99.88 157	100.00 1	97.01 184	99.86 165	99.47 165	99.84 137	99.97 117

xiu_mvs_v1_base_debu		99.35 93	99.21 105	99.79 109	99.67 167	99.71 112	99.78 258	99.36 209	98.13 90	100.00 1	100.00 1	97.00 187	100.00 1	99.83 112	99.07 159	99.66 219

xiu_mvs_v1_base		99.35 93	99.21 105	99.79 109	99.67 167	99.71 112	99.78 258	99.36 209	98.13 90	100.00 1	100.00 1	97.00 187	100.00 1	99.83 112	99.07 159	99.66 219

xiu_mvs_v1_base_debi		99.35 93	99.21 105	99.79 109	99.67 167	99.71 112	99.78 258	99.36 209	98.13 90	100.00 1	100.00 1	97.00 187	100.00 1	99.83 112	99.07 159	99.66 219

CR-MVSNet		98.02 195	97.71 204	98.93 192	99.31 245	98.86 185	99.13 342	99.00 339	96.53 223	99.96 118	98.98 314	96.94 190	98.10 329	91.18 333	98.40 182	99.84 181

Patchmtry		96.81 242	96.37 248	98.14 239	99.31 245	98.55 200	98.91 353	99.00 339	90.45 340	97.92 284	98.98 314	96.94 190	98.12 324	94.27 310	91.53 303	97.75 254

eth_miper_zixun_eth		97.47 216	97.28 219	98.06 249	99.41 233	97.94 239	99.62 288	99.08 317	94.46 289	98.19 273	99.56 278	96.91 192	98.50 305	96.78 279	91.49 304	97.74 277

DROMVSNet		99.19 116	99.09 115	99.48 147	99.42 231	99.07 168	100.00 1	99.21 273	96.95 194	99.96 118	100.00 1	96.88 193	99.48 228	99.64 147	99.79 142	99.88 169

LS3D		99.31 101	99.13 113	99.87 93	99.99 59	99.71 112	99.55 294	99.46 95	97.32 171	99.82 170	100.00 1	96.85 194	99.97 123	99.14 185	100.00 1	99.92 142

MVSFormer		98.94 141	98.82 139	99.28 171	99.45 228	99.49 133	100.00 1	99.13 300	95.46 265	99.97 114	100.00 1	96.76 195	98.59 297	98.63 212	100.00 1	99.74 210

lupinMVS		99.29 104	99.16 112	99.69 121	99.45 228	99.49 133	100.00 1	99.15 291	97.45 160	99.97 114	100.00 1	96.76 195	99.76 187	99.67 143	100.00 1	99.81 193

MAR-MVS		99.49 81	99.36 88	99.89 88	99.97 103	99.66 120	99.74 267	99.95 18	97.89 113	100.00 1	100.00 1	96.71 197	100.00 1	100.00 1	100.00 1	100.00 1
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
MSDG		98.90 145	98.63 155	99.70 120	99.92 118	99.25 156	100.00 1	99.37 203	95.71 251	99.40 198	100.00 1	96.58 198	99.95 143	96.80 278	99.94 129	99.91 144

PVSNet_BlendedMVS		98.71 156	98.62 156	98.98 190	99.98 99	99.60 124	100.00 1	100.00 1	97.23 178	100.00 1	99.03 310	96.57 199	99.99 94	100.00 1	94.75 264	97.35 338

PVSNet_Blended		99.48 83	99.36 88	99.83 99	99.98 99	99.60 124	100.00 1	100.00 1	97.79 121	100.00 1	100.00 1	96.57 199	99.99 94	100.00 1	99.88 134	99.90 153

MVS_Test		98.93 142	98.65 153	99.77 115	99.62 182	99.50 130	99.99 197	99.19 277	95.52 260	99.96 118	99.86 219	96.54 201	99.98 118	98.65 210	98.48 177	99.82 188

PMMVS		99.12 117	98.97 123	99.58 137	99.57 197	98.98 180	100.00 1	99.30 234	97.14 184	99.96 118	100.00 1	96.53 202	99.82 176	99.70 133	98.49 176	99.94 130

PVSNet_Blended_VisFu		99.33 98	99.18 111	99.78 113	99.82 130	99.49 133	100.00 1	99.95 18	97.36 166	99.63 183	100.00 1	96.45 203	99.95 143	99.79 118	99.65 148	99.89 158

mvs_anonymous		98.80 152	98.60 159	99.38 160	99.57 197	99.24 158	100.00 1	99.21 273	95.87 244	98.92 222	99.82 227	96.39 204	99.03 254	99.13 186	98.50 175	99.88 169

bset_n11_16_dypcd		97.66 205	97.54 208	98.04 255	96.88 347	98.04 233	100.00 1	99.25 257	95.72 250	98.47 255	99.73 239	96.23 205	98.34 314	98.18 233	93.37 279	97.74 277

DP-MVS		98.86 148	98.54 163	99.81 103	99.97 103	99.45 138	99.52 298	99.40 185	94.35 292	98.36 259	100.00 1	96.13 206	99.97 123	99.12 187	100.00 1	100.00 1

PVSNet	94.91 18	99.30 103	99.25 98	99.44 150	100.00 1	98.32 215	100.00 1	99.86 37	98.04 98	100.00 1	100.00 1	96.10 207	100.00 1	99.55 157	99.73 143	100.00 1

Effi-MVS+-dtu		98.51 171	98.86 137	97.47 277	99.77 152	94.21 325	100.00 1	98.94 341	97.61 140	99.91 151	98.75 328	95.89 208	99.51 225	99.36 170	99.48 154	98.68 236

mvs-test1		98.89 146	98.99 122	98.60 209	99.77 152	95.96 288	100.00 1	98.94 341	97.61 140	99.93 148	99.92 212	95.89 208	99.93 156	99.36 170	99.50 153	99.90 153

our_test_3		96.51 256	96.35 250	96.98 296	97.61 330	95.05 301	99.98 215	99.01 338	94.68 279	96.77 321	99.06 305	95.87 210	98.14 322	91.81 330	92.37 291	97.75 254

UA-Net		99.06 122	98.83 138	99.74 117	99.52 211	99.40 142	99.08 348	99.45 102	97.64 136	99.83 162	100.00 1	95.80 211	99.94 154	98.35 225	99.80 141	99.88 169

FMVSNet5		95.32 296	95.43 292	94.99 325	99.39 241	92.99 336	99.25 322	99.24 262	90.45 340	97.44 303	98.45 339	95.78 212	94.39 364	87.02 352	91.88 299	97.59 325

CVMVSNet		98.56 166	98.47 167	98.82 199	99.11 254	97.67 252	99.74 267	99.47 80	97.57 148	99.06 216	100.00 1	95.72 213	98.97 262	98.21 232	97.33 225	99.83 184

RPMNet		95.26 298	93.82 304	99.56 140	99.31 245	98.86 185	99.13 342	99.42 130	79.82 363	99.96 118	95.13 359	95.69 214	99.98 118	77.54 369	98.40 182	99.84 181

MVS		99.22 114	98.96 124	99.98 25	99.00 270	99.95 34	99.24 323	99.94 21	98.14 89	98.88 225	100.00 1	95.63 215	100.00 1	99.85 109	100.00 1	100.00 1

jason		99.11 118	98.96 124	99.59 133	99.17 252	99.31 150	100.00 1	99.13 300	97.38 165	99.83 162	100.00 1	95.54 216	99.72 193	99.57 156	99.97 124	99.74 210
jason: jason.
AdaColmap		99.44 86	99.26 97	99.95 61	100.00 1	99.86 89	99.70 276	99.99 13	98.53 61	99.90 152	100.00 1	95.34 217	100.00 1	99.92 100	100.00 1	100.00 1

CANet		99.40 88	99.24 100	99.89 88	99.99 59	99.76 104	100.00 1	99.73 57	98.40 68	99.78 173	100.00 1	95.28 218	99.96 137	100.00 1	99.99 113	99.96 120

FIs		97.95 197	97.73 203	98.62 208	98.53 295	99.24 158	100.00 1	99.43 122	96.74 206	97.87 286	99.82 227	95.27 219	98.89 269	98.78 202	93.07 281	97.74 277

canonicalmvs		99.03 126	98.73 147	99.94 76	99.75 156	99.95 34	100.00 1	99.30 234	97.64 136	100.00 1	100.00 1	95.22 220	99.97 123	99.76 124	96.90 232	99.91 144

FC-MVSNet-test		97.84 199	97.63 207	98.45 217	98.30 305	99.05 171	100.00 1	99.43 122	96.63 219	97.61 297	99.82 227	95.19 221	98.57 300	98.64 211	93.05 282	97.73 284

UniMVSNet_NR-MVSNet		97.16 227	96.80 230	98.22 232	98.38 299	98.41 203	100.00 1	99.45 102	96.14 240	97.76 288	99.64 261	95.05 222	98.50 305	97.98 241	86.84 342	97.75 254

Fast-Effi-MVS+-dtu		98.38 180	98.56 162	97.82 268	99.58 194	94.44 322	100.00 1	99.16 290	96.75 205	99.51 187	99.63 265	95.03 223	99.60 199	97.71 250	99.67 146	99.42 227

UniMVSNet (Re)		97.29 223	96.85 229	98.59 212	98.49 296	99.13 166	100.00 1	99.42 130	96.52 224	98.24 272	98.90 322	94.93 224	98.89 269	97.54 255	87.61 338	97.75 254

BH-w/o		98.82 151	98.81 141	98.88 196	99.62 182	96.71 281	100.00 1	99.28 244	97.09 187	98.81 233	100.00 1	94.91 225	99.96 137	99.54 160	100.00 1	99.96 120

AUN-MVS		96.26 272	95.67 282	98.06 249	99.68 164	95.60 295	99.82 252	99.42 130	96.78 204	99.88 157	99.80 233	94.84 226	99.47 230	97.48 257	73.29 362	99.12 232

PCF-MVS	98.23 3	98.69 158	98.37 174	99.62 128	99.78 149	99.02 174	99.23 329	99.06 329	96.43 227	98.08 275	100.00 1	94.72 227	99.95 143	98.16 234	99.91 132	99.90 153
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
VNet		99.04 124	98.75 146	99.90 85	99.81 134	99.75 106	99.50 300	99.47 80	98.36 75	100.00 1	99.99 177	94.66 228	100.00 1	99.90 102	97.09 227	99.96 120

diffmvs		98.96 138	98.73 147	99.63 127	99.54 201	99.16 164	100.00 1	99.18 284	97.33 170	99.96 118	100.00 1	94.60 229	99.91 160	99.66 145	98.33 191	99.82 188

BH-untuned		98.64 161	98.65 153	98.60 209	99.59 189	96.17 287	100.00 1	99.28 244	96.67 215	98.41 258	100.00 1	94.52 230	99.83 173	99.41 168	100.00 1	99.81 193

nrg030		97.64 206	97.27 221	98.75 203	98.34 300	99.53 128	100.00 1	99.22 268	96.21 239	98.27 268	99.95 204	94.40 231	98.98 260	99.23 182	89.78 321	97.75 254

ppachtmachnet_test		96.17 277	95.89 268	97.02 293	97.61 330	95.24 298	99.99 197	99.24 262	93.31 316	96.71 322	99.62 269	94.34 232	98.07 331	89.87 343	92.30 293	97.75 254

D2MVS		97.63 209	97.83 198	97.05 291	98.83 287	94.60 318	100.00 1	99.82 39	96.89 200	98.28 266	99.03 310	94.05 233	99.47 230	98.58 217	94.97 262	97.09 343

RPSCF		97.37 219	98.24 179	94.76 329	99.80 144	84.57 364	99.99 197	99.05 331	94.95 272	99.82 170	100.00 1	94.03 234	100.00 1	98.15 235	98.38 185	99.70 215

CANet_DTU		99.02 130	98.90 135	99.41 155	99.88 126	98.71 193	100.00 1	99.29 239	98.84 41	100.00 1	100.00 1	94.02 235	100.00 1	98.08 236	99.96 126	99.52 225

LCM-MVSNet-Re		96.52 255	97.21 223	94.44 330	99.27 248	85.80 362	99.85 248	96.61 372	95.98 242	92.75 352	98.48 338	93.97 236	97.55 344	99.58 155	98.43 180	99.98 112

Effi-MVS+		98.58 164	98.24 179	99.61 129	99.60 186	99.26 154	97.85 363	99.10 309	96.22 238	99.97 114	99.89 215	93.75 237	99.77 186	99.43 166	98.34 187	99.81 193

pmmvs4		97.17 226	96.80 230	98.27 228	97.68 327	98.64 198	100.00 1	99.18 284	94.22 294	98.55 247	99.71 243	93.67 238	98.47 308	95.66 292	92.57 289	97.71 297

CHOSEN 1792x2688		99.00 132	98.91 132	99.25 174	99.90 122	97.79 249	100.00 1	99.99 13	98.79 48	98.28 266	100.00 1	93.63 239	99.95 143	99.66 145	99.95 128	100.00 1

cdsmvs_eth3d_5k		24.41 345	32.55 347	0.00 361	0.00 384	0.00 385	0.00 372	99.39 198	0.00 379	0.00 380	100.00 1	93.55 240	0.00 380	0.00 378	0.00 378	0.00 376

AllTest		98.55 167	98.40 171	98.99 188	99.93 115	97.35 262	100.00 1	99.40 185	97.08 189	99.09 212	99.98 180	93.37 241	99.95 143	96.94 271	99.84 137	99.68 217

TestCases				98.99 188	99.93 115	97.35 262		99.40 185	97.08 189	99.09 212	99.98 180	93.37 241	99.95 143	96.94 271	99.84 137	99.68 217

FMVSNet3		97.30 222	96.95 226	98.37 222	99.65 172	99.25 156	99.71 274	99.28 244	94.23 293	98.53 249	98.91 321	93.30 243	98.11 326	95.31 298	93.60 273	97.73 284

Fast-Effi-MVS+		98.40 179	98.02 193	99.55 141	99.63 179	99.06 170	100.00 1	99.15 291	95.07 269	99.42 193	99.95 204	93.26 244	99.73 192	97.44 258	98.24 194	99.87 177

baseline		98.69 158	98.45 168	99.41 155	99.52 211	98.67 196	100.00 1	99.17 289	97.03 192	99.13 210	100.00 1	93.17 245	99.74 190	99.70 133	98.34 187	99.81 193

QAPM		98.99 134	98.66 152	99.96 49	99.01 266	99.87 86	99.88 246	99.93 29	97.99 101	98.68 240	100.00 1	93.17 245	100.00 1	99.32 176	100.00 1	100.00 1

PatchMatch-RL		99.02 130	98.78 143	99.74 117	99.99 59	99.29 151	100.00 1	100.00 1	98.38 71	99.89 155	99.81 230	93.14 247	99.99 94	97.85 247	99.98 121	99.95 125

test_part1		96.98 238	96.36 249	98.85 198	99.78 149	99.77 102	99.63 285	99.30 234	92.74 327	97.05 310	99.52 282	93.10 248	99.02 255	98.02 239	88.10 334	97.76 243

WR-MVS_H		96.73 246	96.32 253	97.95 261	98.26 307	97.88 243	99.72 273	99.43 122	95.06 270	96.99 312	98.68 331	93.02 249	98.53 303	97.43 259	88.33 333	97.43 334

3Dnovator	95.63 14	99.06 122	98.76 145	99.96 49	98.86 284	99.90 65	99.98 215	99.93 29	98.95 31	98.49 254	100.00 1	92.91 250	100.00 1	99.71 131	100.00 1	100.00 1

3Dnovator+	95.58 15	99.03 126	98.71 150	99.96 49	98.99 273	99.89 73	100.00 1	99.51 76	98.96 28	98.32 263	100.00 1	92.78 251	100.00 1	99.87 106	100.00 1	100.00 1

casdiffmvs		98.65 160	98.38 172	99.46 148	99.52 211	98.74 192	100.00 1	99.15 291	96.91 198	99.05 217	100.00 1	92.75 252	99.83 173	99.70 133	98.38 185	99.81 193

NR-MVSNet		96.63 251	96.04 262	98.38 221	98.31 303	98.98 180	99.22 331	99.35 217	95.87 244	94.43 346	99.65 257	92.73 253	98.40 311	96.78 279	88.05 335	97.75 254

COLMAP_ROB	97.10 7	98.29 185	98.17 184	98.65 207	99.94 113	97.39 260	99.30 319	99.40 185	95.64 253	97.75 291	100.00 1	92.69 254	99.95 143	98.89 197	99.92 131	98.62 238
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
EU-MVSNet		96.63 251	96.53 239	96.94 298	97.59 332	96.87 278	99.76 265	99.47 80	96.35 232	96.85 317	99.78 236	92.57 255	96.27 355	95.33 297	91.08 310	97.68 304

MVP-Stereo		96.51 256	96.48 243	96.60 310	95.65 356	94.25 324	98.84 355	98.16 354	95.85 248	95.23 337	99.04 308	92.54 256	99.13 250	92.98 322	99.98 121	96.43 354
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
DeepC-MVS	97.84 5	99.00 132	98.80 142	99.60 131	99.93 115	99.03 173	100.00 1	99.40 185	98.61 59	99.33 199	100.00 1	92.23 257	99.95 143	99.74 126	99.96 126	99.83 184
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
DU-MVS		96.93 240	96.49 242	98.22 232	98.31 303	98.41 203	100.00 1	99.37 203	96.41 229	97.76 288	99.65 257	92.14 258	98.50 305	97.98 241	86.84 342	97.75 254

Baseline_NR-MVSNet		96.16 278	95.70 278	97.56 276	98.28 306	96.79 280	100.00 1	97.86 365	91.93 332	97.63 294	99.47 287	92.14 258	98.35 313	97.13 266	86.83 344	97.54 328

cascas		98.43 174	98.07 190	99.50 144	99.65 172	99.02 174	100.00 1	99.22 268	94.21 295	99.72 179	99.98 180	92.03 260	99.93 156	99.68 140	98.12 201	99.54 224

test_djsdf		97.55 212	97.38 214	98.07 245	97.50 336	97.99 235	100.00 1	99.13 300	95.46 265	98.47 255	99.85 221	92.01 261	98.59 297	98.63 212	95.36 244	97.62 321

v8		96.35 267	95.73 277	98.21 234	98.11 314	98.23 220	99.94 234	99.07 321	92.66 328	98.29 265	99.00 313	91.46 262	98.77 282	94.17 311	88.83 331	97.62 321

OpenMVS	95.20 17	98.76 153	98.41 169	99.78 113	98.89 280	99.81 98	99.99 197	99.76 48	98.02 99	98.02 280	100.00 1	91.44 263	100.00 1	99.63 150	99.97 124	99.55 223

v148		96.29 270	95.84 270	97.63 271	97.74 325	96.53 285	100.00 1	99.07 321	93.52 310	98.01 281	99.42 290	91.22 264	98.60 295	96.37 287	87.22 341	97.75 254

GeoE		98.06 192	97.65 206	99.29 168	99.47 225	98.41 203	100.00 1	99.19 277	94.85 274	98.88 225	100.00 1	91.21 265	99.59 201	97.02 269	98.19 198	99.88 169

XVG-OURS		98.30 183	98.36 175	98.13 242	99.58 194	95.91 291	100.00 1	99.36 209	98.69 53	99.23 203	100.00 1	91.20 266	99.92 159	99.34 173	97.82 214	98.56 239

WR-MVS		97.09 230	96.64 235	98.46 216	98.43 297	99.09 167	99.97 221	99.33 224	95.62 255	97.76 288	99.67 253	91.17 267	98.56 302	98.49 219	89.28 326	97.74 277

V42		96.65 250	96.16 258	98.11 244	98.17 313	98.23 220	99.99 197	99.09 315	93.97 300	98.74 238	99.05 307	91.09 268	98.82 275	95.46 296	89.90 319	97.27 340

v10		96.14 280	95.50 286	98.07 245	98.19 311	97.96 237	99.83 250	99.07 321	92.10 331	98.07 276	98.94 319	91.07 269	98.61 293	92.41 328	89.82 320	97.63 319

v7n		96.06 284	95.42 293	97.99 260	97.58 333	97.35 262	99.86 247	99.11 307	92.81 326	97.91 285	99.49 285	90.99 270	98.92 265	92.51 325	88.49 332	97.70 298

v1144		96.51 256	95.97 266	98.13 242	97.98 319	98.04 233	99.99 197	99.08 317	93.51 311	98.62 244	98.98 314	90.98 271	98.62 292	93.79 317	90.79 313	97.74 277

ab-mvs		98.42 176	98.02 193	99.61 129	99.71 158	99.00 178	99.10 345	99.64 66	96.70 211	99.04 218	99.81 230	90.64 272	99.98 118	99.64 147	97.93 207	99.84 181

Anonymous202405211		97.87 198	97.53 209	98.90 194	99.81 134	96.70 282	99.35 315	99.46 95	92.98 322	98.83 232	99.99 177	90.63 273	100.00 1	99.70 133	97.03 228	100.00 1

Anonymous20231206		93.45 311	93.17 311	94.30 333	95.00 361	89.69 355	99.98 215	98.43 351	93.30 317	94.50 345	98.59 334	90.52 274	95.73 360	77.46 370	90.73 315	97.48 333

anonymousdsp		97.16 227	96.88 228	98.00 258	97.08 346	98.06 231	99.81 253	99.15 291	94.58 282	97.84 287	99.62 269	90.49 275	98.60 295	97.98 241	95.32 245	97.33 339

v2v482		96.70 249	96.18 256	98.27 228	98.04 316	98.39 206	100.00 1	99.13 300	94.19 297	98.58 246	99.08 304	90.48 276	98.67 289	95.69 291	90.44 317	97.75 254

v144192		96.40 264	95.81 271	98.17 237	97.89 322	98.11 227	99.99 197	99.06 329	93.39 313	98.75 236	99.09 303	90.43 277	98.66 290	93.10 321	90.55 316	97.75 254

Vis-MVSNet		98.52 170	98.25 178	99.34 163	99.68 164	98.55 200	99.68 280	99.41 182	97.34 169	99.94 143	100.00 1	90.38 278	99.70 195	99.03 191	98.84 164	99.76 208
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
CP-MVSNet		96.73 246	96.25 254	98.18 235	98.21 310	98.67 196	99.77 263	99.32 226	95.06 270	97.20 308	99.65 257	90.10 279	98.19 319	98.06 238	88.90 329	97.66 310

TranMVSNet+NR-MVSNet		96.45 260	96.01 263	97.79 269	98.00 318	97.62 254	100.00 1	99.35 217	95.98 242	97.31 305	99.64 261	90.09 280	98.00 336	96.89 274	86.80 345	97.75 254

DSMNet-mixed		95.18 299	95.21 295	95.08 323	96.03 353	90.21 354	99.65 282	93.64 376	92.91 323	98.34 261	97.40 352	90.05 281	95.51 361	91.02 335	97.86 210	99.51 226

N_pmnet		91.88 320	93.37 310	87.40 347	97.24 345	66.33 375	99.90 240	91.05 378	89.77 345	95.65 335	98.58 335	90.05 281	98.11 326	85.39 354	92.72 285	97.75 254

GA-MVS		97.72 203	97.27 221	99.06 181	99.24 251	97.93 240	100.00 1	99.24 262	95.80 249	98.99 220	99.64 261	89.77 283	99.36 241	95.12 302	97.62 223	99.89 158

MIMVSNet		97.06 233	96.73 233	98.05 253	99.38 242	96.64 284	98.47 359	99.35 217	93.41 312	99.48 189	98.53 336	89.66 284	97.70 343	94.16 313	98.11 202	99.80 203

IterMVS-SCA-FT		96.72 248	96.42 246	97.62 273	99.40 238	96.83 279	99.99 197	99.14 296	94.65 281	97.55 300	99.72 241	89.65 285	98.31 315	95.62 294	92.05 295	97.73 284

SCA		98.30 183	97.98 195	99.23 175	99.41 233	98.25 219	99.99 197	99.45 102	96.91 198	99.76 176	99.58 274	89.65 285	99.54 217	98.31 227	98.79 165	99.91 144

IterMVS		96.76 245	96.46 244	97.63 271	99.41 233	96.89 277	99.99 197	99.13 300	94.74 278	97.59 299	99.66 255	89.63 287	98.28 317	95.71 290	92.31 292	97.72 290
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
v1192		96.18 275	95.49 288	98.26 230	98.01 317	98.15 224	99.99 197	99.08 317	93.36 314	98.54 248	98.97 317	89.47 288	98.89 269	91.15 334	90.82 312	97.75 254

v1921920		96.16 278	95.50 286	98.14 239	97.88 323	97.96 237	99.99 197	99.07 321	93.33 315	98.60 245	99.24 297	89.37 289	98.71 287	91.28 332	90.74 314	97.75 254

XVG-OURS-SEG-HR		98.27 187	98.31 176	98.14 239	99.59 189	95.92 290	100.00 1	99.36 209	98.48 63	99.21 204	100.00 1	89.27 290	99.94 154	99.76 124	99.17 156	98.56 239

test20.03		93.11 313	92.85 315	93.88 338	95.19 360	91.83 344	100.00 1	98.87 346	93.68 306	92.76 351	98.88 323	89.20 291	92.71 369	77.88 368	89.19 327	97.09 343

MDA-MVSNet_test_wron		92.61 315	91.09 323	97.19 289	96.71 349	97.26 268	100.00 1	99.14 296	88.61 348	67.90 372	98.32 344	89.03 292	96.57 350	90.47 340	89.59 322	97.74 277

BH-RMVSNet		98.46 173	98.08 189	99.59 133	99.61 184	99.19 163	100.00 1	99.28 244	97.06 191	98.95 221	100.00 1	88.99 293	99.82 176	98.83 201	100.00 1	99.77 206

v1240		95.96 286	95.25 294	98.07 245	97.91 321	97.87 245	99.96 225	99.07 321	93.24 318	98.64 243	98.96 318	88.98 294	98.61 293	89.58 346	90.92 311	97.75 254

Anonymous20231211		96.29 270	95.70 278	98.07 245	99.80 144	97.49 257	99.15 340	99.40 185	89.11 346	97.75 291	99.45 288	88.93 295	98.98 260	98.26 231	89.47 324	97.73 284

TR-MVS		98.14 190	97.74 201	99.33 164	99.59 189	98.28 217	99.27 320	99.21 273	96.42 228	99.15 209	99.94 208	88.87 296	99.79 182	98.88 198	98.29 192	99.93 140

CL-MVSNet_self_test		91.07 324	90.35 327	93.24 339	93.27 364	89.16 357	99.55 294	99.25 257	92.34 329	95.23 337	97.05 353	88.86 297	93.59 367	80.67 363	66.95 366	96.96 346

YYNet1		92.44 316	90.92 324	97.03 292	96.20 351	97.06 275	99.99 197	99.14 296	88.21 351	67.93 371	98.43 341	88.63 298	96.28 354	90.64 336	89.08 328	97.74 277

HQP2-MVS												88.61 299

HQP-MVS		97.73 202	97.85 197	97.39 278	99.07 258	94.82 306	100.00 1	99.40 185	99.04 14	99.17 205	99.97 188	88.61 299	99.57 205	99.79 118	95.58 236	97.77 241

HQP_MVS		97.71 204	97.82 199	97.37 279	99.00 270	94.80 309	100.00 1	99.40 185	99.00 25	99.08 214	99.97 188	88.58 301	99.55 214	99.79 118	95.57 240	97.76 243

plane_prior6					99.06 262	94.80 309						88.58 301

tfpnnormal		96.36 266	95.69 281	98.37 222	98.55 293	98.71 193	99.69 278	99.45 102	93.16 320	96.69 323	99.71 243	88.44 303	98.99 259	94.17 311	91.38 307	97.41 335

test1111		98.42 176	98.12 186	99.29 168	99.88 126	98.15 224	99.46 302	100.00 1	98.36 75	99.42 193	100.00 1	87.91 304	99.79 182	99.31 177	98.78 166	99.94 130

ECVR-MVS		98.43 174	98.14 185	99.32 166	99.89 124	98.21 222	99.46 302	100.00 1	98.38 71	99.47 192	100.00 1	87.91 304	99.80 181	99.35 172	98.78 166	99.94 130

TransMVSNet (Re)		94.78 301	93.72 305	97.93 264	98.34 300	97.88 243	99.23 329	97.98 362	91.60 333	94.55 343	99.71 243	87.89 306	98.36 312	89.30 348	84.92 348	97.56 327

DTE-MVSNet		95.52 293	94.99 299	97.08 290	97.49 338	96.45 286	100.00 1	99.25 257	93.82 302	96.17 329	99.57 277	87.81 307	97.18 345	94.57 306	86.26 347	97.62 321

XXY-MVS		97.14 229	96.63 236	98.67 206	98.65 289	98.92 183	99.54 296	99.29 239	95.57 257	97.63 294	99.83 224	87.79 308	99.35 243	98.39 223	92.95 283	97.75 254

UGNet		98.41 178	98.11 187	99.31 167	99.54 201	98.55 200	99.18 332	100.00 1	98.64 58	99.79 172	99.04 308	87.61 309	100.00 1	99.30 178	99.89 133	99.40 228
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
CLD-MVS		97.64 206	97.74 201	97.36 280	99.01 266	94.76 314	100.00 1	99.34 222	99.30 4	99.00 219	99.97 188	87.49 310	99.57 205	99.96 90	95.58 236	97.75 254
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
PEN-MVS		96.01 285	95.48 290	97.58 275	97.74 325	97.26 268	99.90 240	99.29 239	94.55 283	96.79 319	99.55 279	87.38 311	97.84 341	96.92 273	87.24 340	97.65 315

ACMM	97.17 6	97.37 219	97.40 213	97.29 284	99.01 266	94.64 317	100.00 1	99.25 257	98.07 96	98.44 257	99.98 180	87.38 311	99.55 214	99.25 180	95.19 253	97.69 302
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
jajsoiax		97.07 232	96.79 232	97.89 266	97.28 344	97.12 272	99.95 230	99.19 277	96.55 221	97.31 305	99.69 248	87.35 313	98.91 266	98.70 207	95.12 258	97.66 310

pmmvs5		95.94 287	95.61 283	96.95 297	97.42 341	94.66 315	100.00 1	98.08 358	93.60 309	97.05 310	99.43 289	87.02 314	98.46 309	95.76 289	92.12 294	97.72 290

VPA-MVSNet		97.03 235	96.43 245	98.82 199	98.64 290	99.32 149	99.38 312	99.47 80	96.73 208	98.91 224	98.94 319	87.00 315	99.40 239	99.23 182	89.59 322	97.76 243

PS-CasMVS		96.34 268	95.78 274	98.03 257	98.18 312	98.27 218	99.71 274	99.32 226	94.75 276	96.82 318	99.65 257	86.98 316	98.15 321	97.74 249	88.85 330	97.66 310

LPG-MVS_test		97.31 221	97.32 217	97.28 285	98.85 285	94.60 318	100.00 1	99.37 203	97.35 167	98.85 228	99.98 180	86.66 317	99.56 209	99.55 157	95.26 248	97.70 298

LGP-MVS_train				97.28 285	98.85 285	94.60 318		99.37 203	97.35 167	98.85 228	99.98 180	86.66 317	99.56 209	99.55 157	95.26 248	97.70 298

mvs_tets		97.00 237	96.69 234	97.94 262	97.41 343	97.27 267	99.60 290	99.18 284	96.51 225	97.35 304	99.69 248	86.53 319	98.91 266	98.84 199	95.09 259	97.65 315

pm-mvs1		95.76 290	95.01 298	98.00 258	98.23 309	97.45 258	99.24 323	99.04 334	93.13 321	95.93 333	99.72 241	86.28 320	98.84 274	95.62 294	87.92 336	97.72 290

KD-MVS_self_test		91.16 323	90.09 328	94.35 332	94.44 363	91.27 349	99.74 267	99.08 317	90.82 339	94.53 344	94.91 362	86.11 321	94.78 363	82.67 359	68.52 365	96.99 345

MVS-HIRNet		94.12 307	92.73 317	98.29 227	99.33 244	95.95 289	99.38 312	99.19 277	74.54 366	98.26 269	86.34 371	86.07 322	99.06 253	91.60 331	99.87 136	99.85 180

DeepMVS_CX				89.98 344	98.90 279	71.46 371		99.18 284	97.61 140	96.92 313	99.83 224	86.07 322	99.83 173	96.02 288	97.65 222	98.65 237

OPM-MVS		97.21 224	97.18 224	97.32 283	98.08 315	94.66 315	100.00 1	99.28 244	98.65 57	98.92 222	99.98 180	86.03 324	99.56 209	98.28 230	95.41 242	97.72 290
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
new_pmnet		94.11 308	93.47 309	96.04 318	96.60 350	92.82 337	99.97 221	98.91 345	90.21 342	95.26 336	98.05 347	85.89 325	98.14 322	84.28 356	92.01 296	97.16 342

ACMP	97.00 8	97.19 225	97.16 225	97.27 287	98.97 275	94.58 321	100.00 1	99.32 226	97.97 105	97.45 302	99.98 180	85.79 326	99.56 209	99.70 133	95.24 251	97.67 309
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
OurMVSNet-221017-0		96.14 280	95.98 265	96.62 309	97.49 338	93.44 331	99.92 237	98.16 354	95.86 246	97.65 293	99.95 204	85.71 327	98.78 279	94.93 304	94.18 271	97.64 318

SixPastTwentyTwo		95.71 291	95.49 288	96.38 313	97.42 341	93.01 334	99.84 249	98.23 353	94.75 276	95.98 332	99.97 188	85.35 328	98.43 310	94.71 305	93.17 280	97.69 302

LTVRE_ROB	95.29 16	96.32 269	96.10 259	96.99 295	98.55 293	93.88 327	99.45 304	99.28 244	94.50 287	96.46 325	99.52 282	84.86 329	99.48 228	97.26 265	95.03 260	97.59 325
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
ITE_SJBPF				96.84 304	98.96 276	93.49 330		98.12 356	98.12 93	98.35 260	99.97 188	84.45 330	99.56 209	95.63 293	95.25 250	97.49 331

PVSNet_0	93.57 19	96.41 261	95.74 276	98.41 219	99.84 129	95.22 299	100.00 1	100.00 1	98.08 95	97.55 300	99.78 236	84.40 331	100.00 1	100.00 1	81.99 352	100.00 1

K. test v3		95.46 295	95.14 296	96.40 312	97.53 335	93.40 332	99.99 197	99.23 266	95.49 263	92.70 353	99.73 239	84.26 332	98.12 324	93.94 316	93.38 278	97.68 304

GBi-Net		96.07 282	95.80 272	96.89 301	99.53 204	94.87 303	99.18 332	99.27 252	93.71 303	98.53 249	98.81 325	84.23 333	98.07 331	95.31 298	93.60 273	97.72 290

test1		96.07 282	95.80 272	96.89 301	99.53 204	94.87 303	99.18 332	99.27 252	93.71 303	98.53 249	98.81 325	84.23 333	98.07 331	95.31 298	93.60 273	97.72 290

FMVSNet2		96.22 273	95.60 284	98.06 249	99.53 204	98.33 213	99.45 304	99.27 252	93.71 303	98.03 278	98.84 324	84.23 333	98.10 329	93.97 315	93.40 277	97.73 284

testgi		96.18 275	95.93 267	96.93 299	98.98 274	94.20 326	100.00 1	99.07 321	97.16 183	96.06 331	99.86 219	84.08 336	97.79 342	90.38 341	97.80 216	98.81 235

Anonymous20240521		93.29 312	92.76 316	94.90 328	95.64 357	91.27 349	99.97 221	98.82 348	87.04 354	94.71 341	98.19 346	83.86 337	96.80 347	84.04 357	92.56 290	96.64 351

ACMH	96.25 11	96.77 244	96.62 237	97.21 288	98.96 276	94.43 323	99.64 283	99.33 224	97.43 162	96.55 324	99.97 188	83.52 338	99.54 217	99.07 190	95.13 257	97.66 310
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
Anonymous20240529		96.93 240	96.22 255	99.05 183	99.79 147	97.30 266	99.16 338	99.47 80	88.51 349	98.69 239	100.00 1	83.50 339	100.00 1	99.83 112	97.02 229	99.83 184

lessismore_v0				96.05 317	97.55 334	91.80 345		99.22 268		91.87 354	99.91 213	83.50 339	98.68 288	92.48 326	90.42 318	97.68 304

UnsupCasMVSNet_eth		94.25 304	93.89 303	95.34 322	97.63 328	92.13 342	99.73 271	99.36 209	94.88 273	92.78 350	98.63 333	82.72 341	96.53 351	94.57 306	84.73 349	97.36 337

LF4IMVS		96.19 274	96.18 256	96.23 316	98.26 307	92.09 343	100.00 1	97.89 364	97.82 119	97.94 283	99.87 217	82.71 342	99.38 240	97.41 260	93.71 272	97.20 341

ACMH+	96.20 13	96.49 259	96.33 252	97.00 294	99.06 262	93.80 328	99.81 253	99.31 231	97.32 171	95.89 334	99.97 188	82.62 343	99.54 217	98.34 226	94.63 266	97.65 315

pmmvs3		90.62 327	89.36 331	94.40 331	90.53 369	91.49 347	100.00 1	96.73 370	84.21 359	93.65 349	96.65 355	82.56 344	94.83 362	82.28 360	77.62 359	96.89 348

XVG-ACMP-BASELINE		96.60 253	96.52 241	96.84 304	98.41 298	93.29 333	99.99 197	99.32 226	97.76 124	98.51 252	99.29 295	81.95 345	99.54 217	98.40 222	95.03 260	97.68 304

VPNet		96.41 261	95.76 275	98.33 225	98.61 291	98.30 216	99.48 301	99.45 102	96.98 193	98.87 227	99.88 216	81.57 346	98.93 264	99.22 184	87.82 337	97.76 243

MDA-MVSNet-bldmvs		91.65 322	89.94 329	96.79 307	96.72 348	96.70 282	99.42 309	98.94 341	88.89 347	66.97 374	98.37 342	81.43 347	95.91 358	89.24 349	89.46 325	97.75 254

MS-PatchMatch		95.66 292	95.87 269	95.05 324	97.80 324	89.25 356	98.88 354	99.30 234	96.35 232	96.86 316	99.01 312	81.35 348	99.43 236	93.30 320	99.98 121	96.46 353

USDC		95.90 288	95.70 278	96.50 311	98.60 292	92.56 341	100.00 1	98.30 352	97.77 122	96.92 313	99.94 208	81.25 349	99.45 235	93.54 319	94.96 263	97.49 331

TDRefinement		91.93 318	90.48 326	96.27 315	81.60 374	92.65 340	99.10 345	97.61 367	93.96 301	93.77 348	99.85 221	80.03 350	99.53 222	97.82 248	70.59 364	96.63 352

test_0402		94.35 303	93.70 306	96.32 314	97.92 320	93.60 329	99.61 289	98.85 347	88.19 352	94.68 342	99.48 286	80.01 351	98.58 299	89.39 347	95.15 256	96.77 349

TinyColmap		95.50 294	95.12 297	96.64 308	98.69 288	93.00 335	99.40 310	97.75 366	96.40 230	96.14 330	99.87 217	79.47 352	99.50 226	93.62 318	94.72 265	97.40 336

LFMVS		97.42 217	96.62 237	99.81 103	99.80 144	99.50 130	99.16 338	99.56 69	94.48 288	100.00 1	100.00 1	79.35 353	100.00 1	99.89 104	97.37 224	99.94 130

pmmvs-eth3d		91.73 321	90.67 325	94.92 327	91.63 367	92.71 339	99.90 240	98.54 350	91.19 336	88.08 360	95.50 357	79.31 354	96.13 356	90.55 339	81.32 355	95.91 359

new-patchmatchnet		90.30 328	89.46 330	92.84 341	90.77 368	88.55 359	99.83 250	98.80 349	90.07 344	87.86 361	95.00 360	78.77 355	94.30 365	84.86 355	79.15 357	95.68 361

test123		79.44 334	79.23 337	80.05 352	80.03 375	71.72 370	100.00 1	77.93 383	62.52 369	94.81 340	99.69 248	78.21 356	74.53 376	92.57 324	27.33 376	93.90 362

CMPMVS	66.12 22	90.65 326	92.04 319	86.46 348	96.18 352	66.87 374	98.03 362	99.38 201	83.38 361	85.49 364	99.55 279	77.59 357	98.80 278	94.44 308	94.31 270	93.72 364
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
pmmvs6		93.64 309	92.87 314	95.94 319	97.47 340	91.41 348	98.92 352	99.02 336	87.84 353	95.01 339	99.61 271	77.24 358	98.77 282	94.33 309	86.41 346	97.63 319

tmp_tt		75.80 338	74.26 340	80.43 351	52.91 383	53.67 381	87.42 370	97.98 362	61.80 370	67.04 373	100.00 1	76.43 359	96.40 352	96.47 283	28.26 375	91.23 366

MIMVSNet1		91.96 317	91.20 320	94.23 335	94.94 362	91.69 346	99.34 316	99.22 268	88.23 350	94.18 347	98.45 339	75.52 360	93.41 368	79.37 366	91.49 304	97.60 324

VDDNet		96.39 265	95.55 285	98.90 194	99.27 248	97.45 258	99.15 340	99.92 33	91.28 335	99.98 110	100.00 1	73.55 361	100.00 1	99.85 109	96.98 230	99.24 229

EGC-MVSNET		79.46 333	74.04 341	95.72 321	96.00 354	92.73 338	99.09 347	99.04 334	5.08 378	16.72 378	98.71 329	73.03 362	98.74 286	82.05 361	96.64 234	95.69 360

FMVSNet1		94.45 302	93.63 307	96.89 301	98.87 283	94.87 303	99.18 332	99.27 252	90.95 338	97.31 305	98.81 325	72.89 363	98.07 331	92.61 323	92.81 284	97.72 290

VDD-MVS		96.58 254	95.99 264	98.34 224	99.52 211	95.33 297	99.18 332	99.38 201	96.64 217	99.77 174	100.00 1	72.51 364	100.00 1	100.00 1	96.94 231	99.70 215

EG-PatchMatch MVS		92.94 314	92.49 318	94.29 334	95.87 355	87.07 361	99.07 350	98.11 357	93.19 319	88.98 359	98.66 332	70.89 365	99.08 252	92.43 327	95.21 252	96.72 350

test_method		91.04 325	91.10 322	90.85 343	98.34 300	77.63 368	100.00 1	98.93 344	76.69 364	96.25 328	98.52 337	70.44 366	97.98 337	89.02 350	91.74 300	96.92 347

UniMVSNet_ETH3D		95.28 297	94.41 302	97.89 266	98.91 278	95.14 300	99.13 342	99.35 217	92.11 330	97.17 309	99.66 255	70.28 367	99.36 241	97.88 246	95.18 254	99.16 230

OpenMVS_ROB	88.34 20	91.89 319	91.12 321	94.19 336	95.55 358	87.63 360	99.26 321	98.03 359	86.61 355	90.65 358	96.82 354	70.14 368	98.78 279	86.54 353	96.50 235	96.15 355

MVS_0304		95.11 300	94.84 301	95.91 320	99.60 186	91.24 351	98.64 357	99.88 36	94.51 286	99.62 184	98.31 345	69.19 369	98.82 275	95.22 301	98.60 171	97.66 310

testmvs		80.17 332	81.95 335	74.80 354	58.54 381	59.58 380	100.00 1	87.14 381	76.09 365	99.61 185	100.00 1	67.06 370	74.19 377	98.84 199	50.30 371	90.64 367

UnsupCasMVSNet_bld		89.50 329	88.00 332	93.99 337	95.30 359	88.86 358	98.52 358	99.28 244	85.50 357	87.80 362	94.11 363	61.63 371	96.96 346	90.63 337	79.26 356	96.15 355

Gipuma		84.73 331	83.50 334	88.40 346	97.50 336	82.21 366	88.87 368	99.05 331	65.81 368	85.71 363	90.49 366	53.70 372	96.31 353	78.64 367	91.74 300	86.67 368
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
EMVS		69.88 340	69.09 343	72.24 358	84.70 371	65.82 376	99.96 225	87.08 382	49.82 375	71.51 370	84.74 373	49.30 373	75.32 375	50.97 376	43.71 373	75.59 373

PM-MVS		88.39 330	87.41 333	91.31 342	91.73 366	82.02 367	99.79 257	96.62 371	91.06 337	90.71 357	95.73 356	48.60 374	95.96 357	90.56 338	81.91 354	95.97 358

E-PMN		70.72 339	70.06 342	72.69 357	83.92 372	65.48 377	99.95 230	92.72 377	49.88 374	72.30 369	86.26 372	47.17 375	77.43 374	53.83 375	44.49 372	75.17 374

ambc				88.45 345	86.84 370	70.76 372	97.79 364	98.02 361		90.91 356	95.14 358	38.69 376	98.51 304	94.97 303	84.23 350	96.09 357

FPMVS		77.92 337	79.45 336	73.34 356	76.87 377	46.81 382	98.24 360	99.05 331	59.89 371	73.55 368	98.34 343	36.81 377	86.55 371	80.96 362	91.35 308	86.65 369

PMMVS2		79.15 335	77.28 338	84.76 350	82.34 373	72.66 369	99.70 276	95.11 375	71.68 367	84.78 365	90.87 365	32.05 378	89.99 370	75.53 371	63.45 369	91.64 365

LCM-MVSNet		79.01 336	76.93 339	85.27 349	78.28 376	68.01 373	96.57 365	98.03 359	55.10 372	82.03 366	93.27 364	31.99 379	93.95 366	82.72 358	74.37 361	93.84 363

ANet_high		66.05 342	63.44 346	73.88 355	61.14 380	63.45 378	95.68 367	87.18 380	79.93 362	47.35 376	80.68 376	22.35 380	72.33 378	61.24 373	35.42 374	85.88 370

wuyk23d		28.28 344	29.73 348	23.92 360	75.89 378	32.61 384	66.50 371	12.88 384	16.09 377	14.59 379	16.59 378	12.35 381	32.36 379	39.36 377	13.36 377	6.79 375

PMVS	60.66 23	65.98 343	65.05 344	68.75 359	55.06 382	38.40 383	88.19 369	96.98 368	48.30 376	44.82 377	88.52 369	12.22 382	86.49 372	67.58 372	83.79 351	81.35 372
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
MVE	68.59 21	67.22 341	64.68 345	74.84 353	74.67 379	62.32 379	95.84 366	90.87 379	50.98 373	58.72 375	81.05 375	12.20 383	78.95 373	61.06 374	56.75 370	83.24 371
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
test_blank		0.07 348	0.09 351	0.00 361	0.00 384	0.00 385	0.00 372	0.00 385	0.00 379	0.00 380	0.79 379	0.00 384	0.00 380	0.00 378	0.00 378	0.00 376

uanet_test		0.01 349	0.02 352	0.00 361	0.00 384	0.00 385	0.00 372	0.00 385	0.00 379	0.00 380	0.14 380	0.00 384	0.00 380	0.00 378	0.00 378	0.00 376

DCPMVS		0.01 349	0.02 352	0.00 361	0.00 384	0.00 385	0.00 372	0.00 385	0.00 379	0.00 380	0.14 380	0.00 384	0.00 380	0.00 378	0.00 378	0.00 376

sosnet-low-res		0.01 349	0.02 352	0.00 361	0.00 384	0.00 385	0.00 372	0.00 385	0.00 379	0.00 380	0.14 380	0.00 384	0.00 380	0.00 378	0.00 378	0.00 376

sosnet		0.01 349	0.02 352	0.00 361	0.00 384	0.00 385	0.00 372	0.00 385	0.00 379	0.00 380	0.14 380	0.00 384	0.00 380	0.00 378	0.00 378	0.00 376

uncertanet		0.01 349	0.02 352	0.00 361	0.00 384	0.00 385	0.00 372	0.00 385	0.00 379	0.00 380	0.14 380	0.00 384	0.00 380	0.00 378	0.00 378	0.00 376

Regformer		0.01 349	0.02 352	0.00 361	0.00 384	0.00 385	0.00 372	0.00 385	0.00 379	0.00 380	0.14 380	0.00 384	0.00 380	0.00 378	0.00 378	0.00 376

ab-mvs-re		8.33 346	11.11 349	0.00 361	0.00 384	0.00 385	0.00 372	0.00 385	0.00 379	0.00 380	100.00 1	0.00 384	0.00 380	0.00 378	0.00 378	0.00 376

uanet		0.01 349	0.02 352	0.00 361	0.00 384	0.00 385	0.00 372	0.00 385	0.00 379	0.00 380	0.14 380	0.00 384	0.00 380	0.00 378	0.00 378	0.00 376

FOURS1					100.00 1	99.97 22	100.00 1	99.42 130	98.52 62	100.00 1

MSC_two_6792asdad				100.00 1	100.00 1	100.00 1		99.42 130					100.00 1	100.00 1	100.00 1	100.00 1

No_MVS				100.00 1	100.00 1	100.00 1		99.42 130					100.00 1	100.00 1	100.00 1	100.00 1

eth-test2					0.00 384

eth-test					0.00 384

IU-MVS					100.00 1	99.99 5		99.42 130	99.12 6	100.00 1				100.00 1	100.00 1	100.00 1

save fliter					99.99 59	99.93 47	100.00 1	99.42 130	98.93 33

test_0728_SECOND				100.00 1	99.99 59	99.99 5	100.00 1	99.42 130					100.00 1	100.00 1	100.00 1	100.00 1

GSMVS																99.91 144

test_part2					100.00 1	99.99 5				100.00 1

MTGPA								99.42 130

MTMP							100.00 1	99.18 284

gm-plane-assit					99.52 211	97.26 268			95.86 246		100.00 1		99.43 236	98.76 204

test9_res														100.00 1	100.00 1	100.00 1

agg_prior2														100.00 1	100.00 1	100.00 1

agg_prior					100.00 1	99.88 83		99.42 130		100.00 1			99.97 123

test_prior4						99.93 47	100.00 1

test_prior				99.90 85	100.00 1	99.75 106		99.73 57					99.97 123			100.00 1

旧先验2							100.00 1		98.11 94	100.00 1			100.00 1	99.67 143

新几何2							100.00 1

无先验							100.00 1	99.80 42	97.98 103				100.00 1	99.33 174		100.00 1

原ACMM2							100.00 1

testdata2													100.00 1	97.36 262

testdata1							100.00 1		98.77 51

plane_prior7					99.00 270	94.78 313

plane_prior5								99.40 185					99.55 214	99.79 118	95.57 240	97.76 243

plane_prior4											99.97 188

plane_prior3						94.79 312			99.03 19	99.08 214

plane_prior2							100.00 1		99.00 25

plane_prior1					99.02 265

plane_prior						94.80 309	100.00 1		99.03 19						95.58 236

n2								0.00 385

nn								0.00 385

door-mid								96.32 373

test11								99.42 130

door								96.13 374

HQP5-MVS						94.82 306

HQP-NCC					99.07 258		100.00 1		99.04 14	99.17 205

ACMP_Plane					99.07 258		100.00 1		99.04 14	99.17 205

BP-MVS														99.79 118

HQP4-MVS										99.17 205			99.57 205			97.77 241

HQP3-MVS								99.40 185							95.58 236

NP-MVS					99.07 258	94.81 308					99.97 188

ACMMP++_ref															94.58 268

ACMMP++															95.17 255

High-resolution multi-view benchmark