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.

test1172		99.64 58	99.53 66	99.96 46	100.00 1	99.90 60	100.00 1	99.51 73	97.59 133	100.00 1	100.00 1	98.65 127	99.99 89	99.99 58	100.00 1	100.00 1

SR-MVS-dyc-post		99.63 62	99.52 69	99.97 31	99.99 54	99.91 52	100.00 1	99.42 126	97.62 127	100.00 1	100.00 1	98.65 127	99.99 89	99.99 58	100.00 1	100.00 1

RE-MVS-def			99.55 64		99.99 54	99.91 52	100.00 1	99.42 126	97.62 127	100.00 1	100.00 1	98.94 108		99.99 58	100.00 1	100.00 1

SED-MVS		99.83 7	99.77 9	100.00 1	100.00 1	99.99 3	100.00 1	99.42 126	99.03 19	100.00 1	100.00 1	99.50 33	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 22	100.00 1	100.00 1	100.00 1	100.00 1

xxxxxxxxxxxxxcwj		99.77 18	99.70 20	99.97 31	99.99 54	99.93 42	100.00 1	99.31 220	98.93 32	100.00 1	100.00 1	99.05 90	99.99 89	100.00 1	100.00 1	100.00 1

SF-MVS		99.66 54	99.57 57	99.95 58	99.99 54	99.85 87	100.00 1	99.42 126	97.67 121	100.00 1	100.00 1	99.05 90	99.99 89	100.00 1	100.00 1	100.00 1

ETH3D cwj APD-0.16		99.63 62	99.53 66	99.94 73	99.97 96	99.82 92	100.00 1	99.42 126	97.39 154	100.00 1	100.00 1	98.98 100	99.99 89	100.00 1	100.00 1	100.00 1

cl-mvsnet2		98.23 181	98.11 179	98.58 204	99.82 118	99.01 170	100.00 1	99.28 233	96.92 184	98.33 248	99.21 285	98.09 147	98.97 248	98.72 193	92.61 273	97.76 229

miper_enhance_ethall		98.33 173	98.27 171	98.51 205	99.66 157	99.04 166	100.00 1	99.22 258	97.53 141	98.51 238	99.38 278	99.49 35	98.75 270	98.02 226	92.61 273	97.76 229

ZNCC-MVS		99.71 35	99.62 46	99.97 31	99.99 54	99.90 60	100.00 1	99.79 41	97.97 94	99.97 106	100.00 1	98.97 102	100.00 1	99.94 92	100.00 1	100.00 1

ETH3 D test6400		99.68 47	99.59 50	99.97 31	99.99 54	99.93 42	100.00 1	99.42 126	97.97 94	100.00 1	100.00 1	98.90 113	99.99 89	100.00 1	100.00 1	100.00 1

cl-mvsnet_		97.54 204	97.32 208	98.18 225	99.47 212	98.14 215	100.00 1	99.10 295	94.16 284	97.60 284	99.63 252	97.52 161	98.65 276	96.47 269	91.97 284	97.76 229

cl-mvsnet1		97.52 206	97.35 207	98.05 243	99.46 213	98.11 216	100.00 1	99.10 295	94.21 281	97.62 282	99.63 252	97.65 156	98.29 301	96.47 269	91.98 283	97.76 229

9.14			99.57 57		99.99 54		100.00 1	99.42 126	97.54 139	100.00 1	100.00 1	99.15 84	99.99 89	100.00 1	100.00 1

testtj		99.70 39	99.61 47	99.99 9	100.00 1	99.98 13	100.00 1	99.53 68	97.71 117	100.00 1	100.00 1	99.23 74	100.00 1	100.00 1	100.00 1	100.00 1

ETH3D-3000-0.1		99.66 54	99.57 57	99.95 58	99.99 54	99.85 87	100.00 1	99.42 126	97.58 135	100.00 1	100.00 1	99.12 86	99.99 89	100.00 1	100.00 1	100.00 1

save fliter					99.99 54	99.93 42	100.00 1	99.42 126	98.93 32

ET-MVSNet_ETH3D		96.41 250	95.48 279	99.20 169	99.81 122	99.75 101	100.00 1	99.02 320	97.30 165	78.33 351	100.00 1	97.73 153	97.94 323	99.70 125	87.41 324	99.92 133

EIA-MVS		99.26 105	99.19 104	99.45 144	99.63 165	98.75 181	100.00 1	99.27 241	96.93 182	99.95 131	100.00 1	97.47 162	99.79 174	99.74 120	99.72 137	99.82 177

miper_lstm_enhance		97.40 209	97.28 210	97.75 259	99.48 209	97.52 245	100.00 1	99.07 307	94.08 285	98.01 267	99.61 258	97.38 167	97.98 322	96.44 272	91.47 291	97.76 229

ETV-MVS		99.34 94	99.24 94	99.64 123	99.58 181	99.33 142	100.00 1	99.25 247	97.57 137	99.96 110	100.00 1	97.44 165	99.79 174	99.70 125	99.65 140	99.81 181

CS-MVS		99.33 96	99.23 97	99.65 122	99.63 165	99.18 158	100.00 1	99.27 241	97.45 149	99.96 110	100.00 1	97.22 168	99.87 159	99.67 134	99.86 131	99.90 144

D2MVS		97.63 200	97.83 190	97.05 280	98.83 272	94.60 305	100.00 1	99.82 36	96.89 187	98.28 252	99.03 297	94.05 223	99.47 217	98.58 204	94.97 249	97.09 329

DVP-MVS		99.83 7	99.78 6	100.00 1	100.00 1	99.99 3	100.00 1	99.42 126	99.04 14	100.00 1	100.00 1	99.53 23	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
test_0728_SECOND				100.00 1	99.99 54	99.99 3	100.00 1	99.42 126					100.00 1	100.00 1	100.00 1	100.00 1

test0726					100.00 1	99.99 3	100.00 1	99.42 126	99.04 14	100.00 1	100.00 1	99.53 23

SR-MVS		99.68 47	99.58 54	99.98 22	100.00 1	99.95 29	100.00 1	99.64 63	97.59 133	100.00 1	100.00 1	98.99 99	99.99 89	100.00 1	100.00 1	100.00 1

DPM-MVS		99.63 62	99.51 70	100.00 1	99.90 114	100.00 1	100.00 1	99.43 118	99.00 25	100.00 1	100.00 1	99.58 18	100.00 1	97.64 239	100.00 1	100.00 1

GST-MVS		99.64 58	99.53 66	99.95 58	100.00 1	99.86 84	100.00 1	99.79 41	97.72 114	99.95 131	100.00 1	98.39 138	100.00 1	99.96 84	99.99 107	100.00 1

test_yl		99.51 75	99.37 82	99.95 58	99.82 118	99.90 60	100.00 1	99.47 77	97.48 146	100.00 1	100.00 1	99.80 4	100.00 1	99.98 75	97.75 206	99.94 124

thisisatest0530		99.37 90	99.27 90	99.69 117	99.59 176	99.41 135	100.00 1	99.46 92	96.46 213	99.90 142	100.00 1	99.44 43	99.85 164	98.97 179	99.58 144	99.80 191

DCV-MVSNet		99.51 75	99.37 82	99.95 58	99.82 118	99.90 60	100.00 1	99.47 77	97.48 146	100.00 1	100.00 1	99.80 4	100.00 1	99.98 75	97.75 206	99.94 124

tttt0517		99.34 94	99.23 97	99.67 119	99.57 184	99.38 137	100.00 1	99.46 92	96.33 221	99.89 145	100.00 1	99.44 43	99.84 166	98.93 181	99.46 147	99.78 193

thisisatest0515		99.42 85	99.31 89	99.74 113	99.59 176	99.55 121	100.00 1	99.46 92	96.65 203	99.92 139	100.00 1	99.44 43	99.85 164	99.09 176	99.63 142	99.81 181

SMA-MVS		99.69 43	99.59 50	99.98 22	99.99 54	99.93 42	100.00 1	99.43 118	97.50 145	100.00 1	100.00 1	99.43 47	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
DPE-MVS		99.79 14	99.73 16	99.99 9	99.99 54	99.98 13	100.00 1	99.42 126	98.91 35	100.00 1	100.00 1	99.22 76	100.00 1	100.00 1	100.00 1	100.00 1

thres100view900		99.25 108	99.01 113	99.95 58	99.81 122	99.87 81	100.00 1	99.94 18	97.13 173	99.83 152	99.96 186	97.01 175	100.00 1	99.59 142	97.85 199	99.98 108

tfpn200view9		99.26 105	99.03 111	99.96 46	99.81 122	99.89 68	100.00 1	99.94 18	97.23 166	99.83 152	99.96 186	97.04 171	100.00 1	99.59 142	97.85 199	99.98 108

CANet		99.40 86	99.24 94	99.89 85	99.99 54	99.76 99	100.00 1	99.73 54	98.40 63	99.78 162	100.00 1	95.28 208	99.96 131	100.00 1	99.99 107	99.96 116

Fast-Effi-MVS+-dtu		98.38 172	98.56 156	97.82 257	99.58 181	94.44 309	100.00 1	99.16 277	96.75 192	99.51 176	99.63 252	95.03 213	99.60 188	97.71 237	99.67 139	99.42 214

Effi-MVS+-dtu		98.51 165	98.86 131	97.47 266	99.77 139	94.21 312	100.00 1	98.94 325	97.61 129	99.91 141	98.75 315	95.89 198	99.51 213	99.36 160	99.48 146	98.68 222

CANet_DTU		99.02 125	98.90 129	99.41 149	99.88 116	98.71 185	100.00 1	99.29 228	98.84 40	100.00 1	100.00 1	94.02 225	100.00 1	98.08 223	99.96 120	99.52 212

MP-MVS-pluss		99.61 68	99.50 72	99.97 31	99.98 92	99.92 49	100.00 1	99.42 126	97.53 141	99.77 163	100.00 1	98.77 123	100.00 1	99.99 58	100.00 1	99.99 106
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
MSP-MVS		99.81 11	99.77 9	99.94 73	100.00 1	99.86 84	100.00 1	99.42 126	98.87 39	100.00 1	100.00 1	99.65 12	99.96 131	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
TSAR-MVS + MP.		99.82 9	99.77 9	99.99 9	100.00 1	99.96 20	100.00 1	99.43 118	99.05 13	100.00 1	100.00 1	99.45 42	99.99 89	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
OPM-MVS		97.21 215	97.18 215	97.32 272	98.08 299	94.66 302	100.00 1	99.28 233	98.65 53	98.92 209	99.98 169	86.03 311	99.56 197	98.28 217	95.41 229	97.72 276

ACMMP_NAP		99.67 52	99.57 57	99.97 31	99.98 92	99.92 49	100.00 1	99.42 126	97.83 107	100.00 1	100.00 1	98.89 115	100.00 1	99.98 75	100.00 1	100.00 1

zzz-MVS		99.68 47	99.59 50	99.97 31	99.99 54	99.91 52	100.00 1	99.42 126	98.32 71	99.94 133	100.00 1	98.65 127	100.00 1	99.96 84	100.00 1	100.00 1

mvs-test1		98.89 141	98.99 116	98.60 200	99.77 139	95.96 277	100.00 1	98.94 325	97.61 129	99.93 138	99.92 201	95.89 198	99.93 150	99.36 160	99.50 145	99.90 144

pmmvs5		95.94 276	95.61 272	96.95 286	97.42 325	94.66 302	100.00 1	98.08 340	93.60 295	97.05 296	99.43 276	87.02 301	98.46 294	95.76 275	92.12 280	97.72 276

Fast-Effi-MVS+		98.40 171	98.02 185	99.55 138	99.63 165	99.06 164	100.00 1	99.15 278	95.07 256	99.42 181	99.95 193	93.26 234	99.73 183	97.44 245	98.24 183	99.87 167

MTAPA		99.68 47	99.59 50	99.97 31	99.99 54	99.91 52	100.00 1	99.42 126	98.32 71	99.94 133	100.00 1	98.65 127	100.00 1	99.96 84	100.00 1	100.00 1

MTMP							100.00 1	99.18 271

TEST9					100.00 1	99.95 29	100.00 1	99.42 126	97.65 123	100.00 1	100.00 1	99.53 23	99.97 117

train_agg		99.71 35	99.63 42	99.97 31	100.00 1	99.95 29	100.00 1	99.42 126	97.70 118	100.00 1	100.00 1	99.51 28	99.97 117	100.00 1	100.00 1	100.00 1

test_8					100.00 1	99.91 52	100.00 1	99.42 126	97.70 118	100.00 1	100.00 1	99.51 28	99.98 112

agg_prior1		99.71 35	99.63 42	99.95 58	100.00 1	99.88 78	100.00 1	99.42 126	97.72 114	100.00 1	100.00 1	99.51 28	99.97 117	100.00 1	100.00 1	100.00 1

canonicalmvs		99.03 121	98.73 141	99.94 73	99.75 143	99.95 29	100.00 1	99.30 223	97.64 125	100.00 1	100.00 1	95.22 210	99.97 117	99.76 118	96.90 220	99.91 135

alignmvs		99.38 88	99.21 100	99.91 79	99.73 144	99.92 49	100.00 1	99.51 73	97.61 129	100.00 1	100.00 1	99.06 89	99.93 150	99.83 106	97.12 214	99.90 144

nrg030		97.64 197	97.27 212	98.75 194	98.34 285	99.53 123	100.00 1	99.22 258	96.21 226	98.27 254	99.95 193	94.40 221	98.98 246	99.23 169	89.78 306	97.75 240

FIs		97.95 188	97.73 195	98.62 199	98.53 280	99.24 152	100.00 1	99.43 118	96.74 193	97.87 272	99.82 216	95.27 209	98.89 255	98.78 189	93.07 268	97.74 263

FC-MVSNet-test		97.84 190	97.63 198	98.45 207	98.30 289	99.05 165	100.00 1	99.43 118	96.63 206	97.61 283	99.82 216	95.19 211	98.57 285	98.64 198	93.05 269	97.73 270

HFP-MVS		99.74 26	99.67 30	99.96 46	100.00 1	99.89 68	100.00 1	99.76 45	97.95 99	100.00 1	100.00 1	99.31 60	100.00 1	99.99 58	100.00 1	100.00 1

v148		96.29 259	95.84 259	97.63 260	97.74 309	96.53 274	100.00 1	99.07 307	93.52 296	98.01 267	99.42 277	91.22 254	98.60 280	96.37 273	87.22 326	97.75 240

AllTest		98.55 161	98.40 165	98.99 179	99.93 108	97.35 251	100.00 1	99.40 174	97.08 177	99.09 199	99.98 169	93.37 231	99.95 137	96.94 257	99.84 132	99.68 205

region2R		99.72 32	99.64 38	99.97 31	100.00 1	99.90 60	100.00 1	99.74 52	97.86 106	100.00 1	100.00 1	99.19 80	100.00 1	99.99 58	100.00 1	100.00 1

bset_n11_16_dypcd		97.66 196	97.54 199	98.04 245	96.88 331	98.04 222	100.00 1	99.25 247	95.72 237	98.47 241	99.73 226	96.23 195	98.34 299	98.18 220	93.37 266	97.74 263

RRT_MVS		98.48 166	98.41 163	98.70 196	99.64 163	99.67 114	100.00 1	99.10 295	96.26 224	98.75 222	99.96 186	99.04 93	98.75 270	98.42 208	94.51 256	97.68 290

#test#		99.75 21	99.68 25	99.96 46	100.00 1	99.89 68	100.00 1	99.76 45	98.07 85	100.00 1	100.00 1	99.31 60	100.00 1	99.99 58	100.00 1	100.00 1

Regformer-3		99.73 29	99.65 34	99.96 46	100.00 1	99.89 68	100.00 1	99.44 108	98.40 63	100.00 1	100.00 1	99.03 97	99.97 117	99.99 58	100.00 1	100.00 1

Regformer-4		99.73 29	99.65 34	99.95 58	100.00 1	99.89 68	100.00 1	99.44 108	98.40 63	100.00 1	100.00 1	99.03 97	99.97 117	99.99 58	100.00 1	100.00 1

Regformer-1		99.75 21	99.68 25	99.98 22	100.00 1	99.94 37	100.00 1	99.44 108	98.43 60	100.00 1	100.00 1	99.23 74	99.99 89	99.99 58	100.00 1	100.00 1

Regformer-2		99.75 21	99.68 25	99.97 31	100.00 1	99.94 37	100.00 1	99.44 108	98.42 62	100.00 1	100.00 1	99.22 76	99.99 89	99.99 58	100.00 1	100.00 1

HPM-MVS++		99.82 9	99.76 12	99.99 9	99.99 54	99.98 13	100.00 1	99.83 35	98.88 37	99.96 110	100.00 1	99.21 78	100.00 1	100.00 1	100.00 1	99.99 106

test_prior4						99.93 42	100.00 1

XVS		99.79 14	99.73 16	99.98 22	100.00 1	99.94 37	100.00 1	99.75 49	98.67 51	100.00 1	100.00 1	99.16 82	100.00 1	100.00 1	100.00 1	100.00 1

test_prior3		99.81 11	99.78 6	99.90 82	100.00 1	99.75 101	100.00 1	99.73 54	98.82 43	100.00 1	100.00 1	99.47 39	99.97 117	100.00 1	100.00 1	100.00 1

test_prior2							100.00 1		98.82 43	100.00 1	100.00 1	99.47 39		100.00 1	100.00 1

X-MVStestdata		97.04 225	96.06 250	99.98 22	100.00 1	99.94 37	100.00 1	99.75 49	98.67 51	100.00 1	66.97 361	99.16 82	100.00 1	100.00 1	100.00 1	100.00 1

旧先验2							100.00 1		98.11 83	100.00 1			100.00 1	99.67 134

新几何2							100.00 1

无先验							100.00 1	99.80 39	97.98 92				100.00 1	99.33 163		100.00 1

原ACMM2							100.00 1

test222					99.99 54	99.90 60	100.00 1	99.69 61	97.66 122	100.00 1	100.00 1	99.30 66			100.00 1	100.00 1

testdata1							100.00 1		98.77 48

v2v482		96.70 238	96.18 245	98.27 218	98.04 300	98.39 197	100.00 1	99.13 287	94.19 283	98.58 232	99.08 291	90.48 265	98.67 274	95.69 277	90.44 302	97.75 240

SD-MVS		99.81 11	99.75 14	99.99 9	99.99 54	99.96 20	100.00 1	99.42 126	99.01 24	100.00 1	100.00 1	99.33 55	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
GA-MVS		97.72 194	97.27 212	99.06 172	99.24 236	97.93 229	100.00 1	99.24 252	95.80 236	98.99 207	99.64 248	89.77 272	99.36 227	95.12 288	97.62 211	99.89 150

MSLP-MVS++		99.89 1	99.85 2	99.99 9	100.00 1	99.96 20	100.00 1	99.95 15	99.11 7	100.00 1	100.00 1	99.60 14	100.00 1	100.00 1	100.00 1	100.00 1

APDe-MVS		99.84 6	99.78 6	99.99 9	100.00 1	99.98 13	100.00 1	99.44 108	99.06 11	100.00 1	100.00 1	99.56 19	99.99 89	100.00 1	100.00 1	100.00 1

APD-MVS_3200maxsize		99.65 56	99.55 64	99.97 31	99.99 54	99.91 52	100.00 1	99.48 76	97.54 139	100.00 1	100.00 1	98.97 102	99.99 89	99.98 75	100.00 1	100.00 1

pmmvs4		97.17 217	96.80 221	98.27 218	97.68 311	98.64 190	100.00 1	99.18 271	94.22 280	98.55 233	99.71 230	93.67 228	98.47 293	95.66 278	92.57 276	97.71 283

test-LLR		99.03 121	98.91 126	99.40 151	99.40 223	99.28 146	100.00 1	99.45 99	96.70 198	99.42 181	99.12 288	99.31 60	99.01 243	96.82 262	99.99 107	99.91 135

TESTMET0.1,1		99.08 116	98.96 118	99.44 145	99.63 165	99.38 137	100.00 1	99.45 99	95.53 245	99.48 178	100.00 1	99.71 10	99.02 241	96.84 261	99.99 107	99.91 135

test-mter		98.96 133	98.82 133	99.40 151	99.40 223	99.28 146	100.00 1	99.45 99	95.44 254	99.42 181	99.12 288	99.70 11	99.01 243	96.82 262	99.99 107	99.91 135

ACMMPR		99.74 26	99.67 30	99.96 46	100.00 1	99.89 68	100.00 1	99.76 45	97.95 99	100.00 1	100.00 1	99.29 67	100.00 1	99.99 58	100.00 1	100.00 1

testgi		96.18 264	95.93 256	96.93 288	98.98 259	94.20 313	100.00 1	99.07 307	97.16 171	96.06 316	99.86 208	84.08 323	97.79 326	90.38 327	97.80 204	98.81 221

test20.03		93.11 301	92.85 304	93.88 323	95.19 342	91.83 330	100.00 1	98.87 329	93.68 292	92.76 335	98.88 310	89.20 280	92.71 352	77.88 351	89.19 312	97.09 329

thres600view7		99.24 110	99.00 114	99.95 58	99.81 122	99.87 81	100.00 1	99.94 18	97.13 173	99.83 152	99.96 186	97.01 175	100.00 1	99.54 150	97.77 205	99.97 113

MP-MVS		99.61 68	99.49 74	99.98 22	99.99 54	99.94 37	100.00 1	99.42 126	97.82 108	99.99 97	100.00 1	98.20 141	100.00 1	99.99 58	100.00 1	100.00 1
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
testmvs		80.17 319	81.95 322	74.80 338	58.54 363	59.58 362	100.00 1	87.14 363	76.09 349	99.61 174	100.00 1	67.06 354	74.19 360	98.84 186	50.30 354	90.64 350

thres400		99.26 105	99.03 111	99.95 58	99.81 122	99.89 68	100.00 1	99.94 18	97.23 166	99.83 152	99.96 186	97.04 171	100.00 1	99.59 142	97.85 199	99.97 113

test123		79.44 320	79.23 324	80.05 336	80.03 357	71.72 352	100.00 1	77.93 365	62.52 353	94.81 325	99.69 235	78.21 342	74.53 359	92.57 310	27.33 359	93.90 345

thres200		99.27 103	99.04 110	99.96 46	99.81 122	99.90 60	100.00 1	99.94 18	97.31 163	99.83 152	99.96 186	97.04 171	100.00 1	99.62 141	97.88 197	99.98 108

test0.0.03 1		98.12 183	98.03 184	98.39 210	99.11 239	98.07 219	100.00 1	99.93 26	96.70 198	96.91 301	99.95 193	99.31 60	98.19 304	91.93 315	98.44 168	98.91 220

pmmvs3		90.62 314	89.36 318	94.40 316	90.53 351	91.49 333	100.00 1	96.73 352	84.21 344	93.65 333	96.65 339	82.56 330	94.83 345	82.28 344	77.62 344	96.89 333

PGM-MVS		99.69 43	99.61 47	99.95 58	99.99 54	99.85 87	100.00 1	99.58 65	97.69 120	100.00 1	100.00 1	99.44 43	100.00 1	99.79 112	100.00 1	100.00 1

MCST-MVS		99.85 3	99.80 4	100.00 1	100.00 1	99.99 3	100.00 1	99.73 54	99.19 5	100.00 1	100.00 1	99.31 60	100.00 1	100.00 1	100.00 1	100.00 1

mvs_anonymous		98.80 146	98.60 153	99.38 154	99.57 184	99.24 152	100.00 1	99.21 263	95.87 231	98.92 209	99.82 216	96.39 194	99.03 240	99.13 173	98.50 164	99.88 161

CDPH-MVS		99.73 29	99.64 38	99.99 9	100.00 1	99.97 18	100.00 1	99.42 126	98.02 88	100.00 1	100.00 1	99.32 58	99.99 89	100.00 1	100.00 1	100.00 1

casdiffmvs		98.65 154	98.38 166	99.46 143	99.52 198	98.74 184	100.00 1	99.15 278	96.91 185	99.05 204	100.00 1	92.75 242	99.83 167	99.70 125	98.38 174	99.81 181

diffmvs		98.96 133	98.73 141	99.63 124	99.54 188	99.16 159	100.00 1	99.18 271	97.33 160	99.96 110	100.00 1	94.60 219	99.91 154	99.66 137	98.33 180	99.82 177

baseline2		98.99 129	98.93 124	99.18 170	99.26 235	99.15 160	100.00 1	99.46 92	96.71 197	96.79 305	100.00 1	99.42 49	99.25 233	98.75 192	99.94 123	99.15 218

MDA-MVSNet_test_wron		92.61 303	91.09 310	97.19 278	96.71 333	97.26 257	100.00 1	99.14 283	88.61 334	67.90 356	98.32 329	89.03 281	96.57 333	90.47 326	89.59 307	97.74 263

HQP_MVS		97.71 195	97.82 191	97.37 268	99.00 255	94.80 296	100.00 1	99.40 174	99.00 25	99.08 201	99.97 177	88.58 290	99.55 202	99.79 112	95.57 227	97.76 229

plane_prior2							100.00 1		99.00 25

plane_prior						94.80 296	100.00 1		99.03 19						95.58 223

UniMVSNet_NR-MVSNet		97.16 218	96.80 221	98.22 222	98.38 284	98.41 195	100.00 1	99.45 99	96.14 227	97.76 274	99.64 248	95.05 212	98.50 290	97.98 228	86.84 327	97.75 240

DTE-MVSNet		95.52 282	94.99 288	97.08 279	97.49 322	96.45 275	100.00 1	99.25 247	93.82 288	96.17 314	99.57 264	87.81 294	97.18 329	94.57 292	86.26 332	97.62 307

DU-MVS		96.93 230	96.49 232	98.22 222	98.31 287	98.41 195	100.00 1	99.37 192	96.41 216	97.76 274	99.65 244	92.14 248	98.50 290	97.98 228	86.84 327	97.75 240

UniMVSNet (Re)		97.29 214	96.85 220	98.59 203	98.49 281	99.13 161	100.00 1	99.42 126	96.52 211	98.24 258	98.90 309	94.93 214	98.89 255	97.54 242	87.61 323	97.75 240

Baseline_NR-MVSNet		96.16 267	95.70 267	97.56 265	98.28 290	96.79 269	100.00 1	97.86 347	91.93 318	97.63 280	99.47 274	92.14 248	98.35 298	97.13 253	86.83 329	97.54 314

TranMVSNet+NR-MVSNet		96.45 249	96.01 252	97.79 258	98.00 302	97.62 243	100.00 1	99.35 206	95.98 229	97.31 291	99.64 248	90.09 269	98.00 321	96.89 260	86.80 330	97.75 240

TSAR-MVS + GP.		99.61 68	99.69 22	99.35 156	99.99 54	98.06 220	100.00 1	99.36 198	99.83 2	100.00 1	100.00 1	98.95 106	99.99 89	100.00 1	99.11 150	100.00 1

abl_6		99.53 74	99.40 77	99.92 78	100.00 1	99.76 99	100.00 1	99.42 126	97.21 169	100.00 1	100.00 1	98.12 144	100.00 1	99.82 111	100.00 1	100.00 1

mPP-MVS		99.69 43	99.60 49	99.97 31	100.00 1	99.91 52	100.00 1	99.42 126	97.91 101	100.00 1	100.00 1	99.04 93	100.00 1	100.00 1	100.00 1	100.00 1

XVG-OURS-SEG-HR		98.27 179	98.31 170	98.14 229	99.59 176	95.92 279	100.00 1	99.36 198	98.48 58	99.21 191	100.00 1	89.27 279	99.94 148	99.76 118	99.17 148	98.56 225

MVSFormer		98.94 136	98.82 133	99.28 162	99.45 214	99.49 127	100.00 1	99.13 287	95.46 252	99.97 106	100.00 1	96.76 185	98.59 282	98.63 199	100.00 1	99.74 198

jason		99.11 114	98.96 118	99.59 130	99.17 237	99.31 144	100.00 1	99.13 287	97.38 155	99.83 152	100.00 1	95.54 206	99.72 184	99.57 146	99.97 118	99.74 198
jason: jason.
lupinMVS		99.29 101	99.16 107	99.69 117	99.45 214	99.49 127	100.00 1	99.15 278	97.45 149	99.97 106	100.00 1	96.76 185	99.76 178	99.67 134	100.00 1	99.81 181

test_djsdf		97.55 203	97.38 205	98.07 235	97.50 320	97.99 224	100.00 1	99.13 287	95.46 252	98.47 241	99.85 210	92.01 251	98.59 282	98.63 199	95.36 231	97.62 307

HPM-MVS_fast		99.60 71	99.49 74	99.91 79	99.99 54	99.78 96	100.00 1	99.42 126	97.09 175	100.00 1	100.00 1	98.95 106	99.96 131	99.98 75	100.00 1	100.00 1

RRT_test8_iter05		98.32 174	98.23 175	98.60 200	99.65 158	99.23 155	100.00 1	99.09 301	95.65 239	98.07 262	99.93 200	99.25 72	98.82 261	98.90 183	93.50 263	97.75 240

HPM-MVS		99.59 72	99.50 72	99.89 85	100.00 1	99.70 111	100.00 1	99.42 126	97.46 148	100.00 1	100.00 1	98.60 131	99.96 131	99.99 58	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
XVG-OURS		98.30 175	98.36 169	98.13 232	99.58 181	95.91 280	100.00 1	99.36 198	98.69 49	99.23 190	100.00 1	91.20 255	99.92 153	99.34 162	97.82 202	98.56 225

LPG-MVS_test		97.31 212	97.32 208	97.28 274	98.85 270	94.60 305	100.00 1	99.37 192	97.35 157	98.85 214	99.98 169	86.66 304	99.56 197	99.55 147	95.26 235	97.70 284

baseline		98.69 152	98.45 162	99.41 149	99.52 198	98.67 188	100.00 1	99.17 276	97.03 180	99.13 197	100.00 1	93.17 235	99.74 181	99.70 125	98.34 176	99.81 181

CHOSEN 1792x2688		99.00 127	98.91 126	99.25 165	99.90 114	97.79 238	100.00 1	99.99 10	98.79 46	98.28 252	100.00 1	93.63 229	99.95 137	99.66 137	99.95 122	100.00 1

EPNet		99.62 66	99.69 22	99.42 148	99.99 54	98.37 200	100.00 1	99.89 32	98.83 41	100.00 1	100.00 1	98.97 102	100.00 1	99.90 96	99.61 143	99.89 150
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
HQP-NCC					99.07 243		100.00 1		99.04 14	99.17 192

ACMP_Plane					99.07 243		100.00 1		99.04 14	99.17 192

APD-MVS		99.68 47	99.58 54	99.97 31	99.99 54	99.96 20	100.00 1	99.42 126	97.53 141	100.00 1	100.00 1	99.27 70	99.97 117	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
CNVR-MVS		99.85 3	99.80 4	100.00 1	100.00 1	99.99 3	100.00 1	99.77 44	99.07 9	100.00 1	100.00 1	99.39 53	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 3	100.00 1	99.71 60	99.07 9	100.00 1	100.00 1	99.59 16	100.00 1	100.00 1	100.00 1	100.00 1

114514_t		99.39 87	99.25 92	99.81 100	99.97 96	99.48 131	100.00 1	99.42 126	95.53 245	100.00 1	100.00 1	98.37 139	99.95 137	99.97 82	100.00 1	100.00 1

CP-MVS		99.67 52	99.58 54	99.95 58	100.00 1	99.84 90	100.00 1	99.42 126	97.77 111	100.00 1	100.00 1	99.07 88	100.00 1	100.00 1	100.00 1	100.00 1

SteuartSystems-ACMMP		99.78 16	99.71 19	99.98 22	99.76 141	99.95 29	100.00 1	99.42 126	98.69 49	100.00 1	100.00 1	99.52 26	99.99 89	100.00 1	100.00 1	100.00 1
Skip Steuart: Steuart Systems R&D Blog.
BH-w/o		98.82 145	98.81 135	98.88 187	99.62 169	96.71 270	100.00 1	99.28 233	97.09 175	98.81 219	100.00 1	94.91 215	99.96 131	99.54 150	100.00 1	99.96 116

DELS-MVS		99.62 66	99.56 63	99.82 97	99.92 111	99.45 132	100.00 1	99.78 43	98.92 34	99.73 167	100.00 1	97.70 155	100.00 1	99.93 93	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
BH-untuned		98.64 155	98.65 147	98.60 200	99.59 176	96.17 276	100.00 1	99.28 233	96.67 202	98.41 244	100.00 1	94.52 220	99.83 167	99.41 158	100.00 1	99.81 181

MVSTER		98.58 158	98.52 158	98.77 193	99.65 158	99.68 113	100.00 1	99.29 228	95.63 241	98.65 227	99.80 222	99.78 6	98.88 258	98.59 203	95.31 233	97.73 270

CPTT-MVS		99.49 80	99.38 80	99.85 93	100.00 1	99.54 122	100.00 1	99.42 126	97.58 135	99.98 102	100.00 1	97.43 166	100.00 1	99.99 58	100.00 1	100.00 1

PVSNet_Blended_VisFu		99.33 96	99.18 106	99.78 110	99.82 118	99.49 127	100.00 1	99.95 15	97.36 156	99.63 172	100.00 1	96.45 193	99.95 137	99.79 112	99.65 140	99.89 150

PVSNet_BlendedMVS		98.71 150	98.62 150	98.98 181	99.98 92	99.60 119	100.00 1	100.00 1	97.23 166	100.00 1	99.03 297	96.57 189	99.99 89	100.00 1	94.75 251	97.35 324

PVSNet_Blended		99.48 82	99.36 84	99.83 96	99.98 92	99.60 119	100.00 1	100.00 1	97.79 110	100.00 1	100.00 1	96.57 189	99.99 89	100.00 1	99.88 128	99.90 144

cascas		98.43 168	98.07 182	99.50 141	99.65 158	99.02 168	100.00 1	99.22 258	94.21 281	99.72 168	99.98 169	92.03 250	99.93 150	99.68 132	98.12 189	99.54 211

BH-RMVSNet		98.46 167	98.08 181	99.59 130	99.61 171	99.19 157	100.00 1	99.28 233	97.06 179	98.95 208	100.00 1	88.99 282	99.82 170	98.83 188	100.00 1	99.77 194

WTY-MVS		99.54 73	99.40 77	99.95 58	99.81 122	99.93 42	100.00 1	100.00 1	97.98 92	99.84 150	100.00 1	98.94 108	99.98 112	99.86 101	98.21 185	99.94 124

sss		99.45 83	99.34 88	99.80 104	99.76 141	99.50 124	100.00 1	99.91 31	97.72 114	99.98 102	99.94 197	98.45 136	100.00 1	99.53 152	98.75 158	99.89 150

DP-MVS Recon		99.76 19	99.69 22	99.98 22	100.00 1	99.95 29	100.00 1	99.52 69	97.99 90	99.99 97	100.00 1	99.72 9	100.00 1	99.96 84	100.00 1	100.00 1

MVS_111021_LR		99.70 39	99.65 34	99.88 89	99.96 102	99.70 111	100.00 1	99.97 14	98.96 28	100.00 1	100.00 1	97.93 149	99.95 137	99.99 58	100.00 1	100.00 1

HQP-MVS		97.73 193	97.85 189	97.39 267	99.07 243	94.82 293	100.00 1	99.40 174	99.04 14	99.17 192	99.97 177	88.61 288	99.57 193	99.79 112	95.58 223	97.77 227

HyFIR lowres test		99.32 98	99.24 94	99.58 134	99.95 103	99.26 148	100.00 1	99.99 10	96.72 196	99.29 188	99.91 202	99.49 35	99.47 217	99.74 120	98.08 191	100.00 1

PAPM_NR		99.74 26	99.66 33	99.99 9	100.00 1	99.96 20	100.00 1	99.47 77	97.87 105	100.00 1	100.00 1	99.60 14	100.00 1	100.00 1	100.00 1	100.00 1

PAPR		99.76 19	99.68 25	99.99 9	100.00 1	99.96 20	100.00 1	99.47 77	98.16 75	100.00 1	100.00 1	99.51 28	100.00 1	100.00 1	100.00 1	100.00 1

IB-MVS	96.24 12	97.54 204	96.95 217	99.33 158	99.67 153	98.10 218	100.00 1	99.47 77	97.42 153	99.26 189	99.69 235	98.83 119	99.89 155	99.43 156	78.77 343	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
MVS_111021_HR		99.71 35	99.63 42	99.93 76	99.95 103	99.83 91	100.00 1	100.00 1	98.89 36	100.00 1	100.00 1	97.85 151	99.95 137	100.00 1	100.00 1	100.00 1

CSCG		99.28 102	99.35 86	99.05 174	99.99 54	97.15 260	100.00 1	99.47 77	97.44 151	99.42 181	100.00 1	97.83 152	100.00 1	99.99 58	100.00 1	100.00 1

PatchMatch-RL		99.02 125	98.78 137	99.74 113	99.99 54	99.29 145	100.00 1	100.00 1	98.38 66	99.89 145	99.81 219	93.14 237	99.99 89	97.85 234	99.98 115	99.95 121

USDC		95.90 277	95.70 267	96.50 298	98.60 277	92.56 327	100.00 1	98.30 334	97.77 111	96.92 299	99.94 197	81.25 335	99.45 221	93.54 305	94.96 250	97.49 317

PMMVS		99.12 113	98.97 117	99.58 134	99.57 184	98.98 173	100.00 1	99.30 223	97.14 172	99.96 110	100.00 1	96.53 192	99.82 170	99.70 125	98.49 165	99.94 124

PAPM		99.78 16	99.76 12	99.85 93	99.01 251	99.95 29	100.00 1	99.75 49	99.37 3	99.99 97	100.00 1	99.76 8	99.60 188	100.00 1	100.00 1	100.00 1

CNLPA		99.72 32	99.65 34	99.91 79	99.97 96	99.72 106	100.00 1	99.47 77	98.43 60	99.88 147	100.00 1	99.14 85	100.00 1	99.97 82	100.00 1	100.00 1

PHI-MVS		99.50 78	99.39 79	99.82 97	100.00 1	99.45 132	100.00 1	99.94 18	96.38 218	100.00 1	100.00 1	98.18 142	100.00 1	100.00 1	100.00 1	100.00 1

PVSNet	94.91 18	99.30 100	99.25 92	99.44 145	100.00 1	98.32 206	100.00 1	99.86 34	98.04 87	100.00 1	100.00 1	96.10 197	100.00 1	99.55 147	99.73 136	100.00 1

PVSNet_0	93.57 19	96.41 250	95.74 265	98.41 209	99.84 117	95.22 286	100.00 1	100.00 1	98.08 84	97.55 286	99.78 224	84.40 318	100.00 1	100.00 1	81.99 337	100.00 1

F-COLMAP		99.64 58	99.64 38	99.67 119	99.99 54	99.07 163	100.00 1	99.44 108	98.30 73	99.90 142	100.00 1	99.18 81	99.99 89	99.91 95	100.00 1	99.94 124

DeepPCF-MVS	98.03 4	98.54 162	99.72 18	94.98 312	99.99 54	84.94 346	100.00 1	99.42 126	99.98 1	100.00 1	100.00 1	98.11 145	100.00 1	100.00 1	100.00 1	100.00 1

OMC-MVS		99.27 103	99.38 80	98.96 182	99.95 103	97.06 264	100.00 1	99.40 174	98.83 41	99.88 147	100.00 1	97.01 175	99.86 160	99.47 155	99.84 132	99.97 113

DeepC-MVS	97.84 5	99.00 127	98.80 136	99.60 128	99.93 108	99.03 167	100.00 1	99.40 174	98.61 55	99.33 186	100.00 1	92.23 247	99.95 137	99.74 120	99.96 120	99.83 173
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
PLC	98.56 2	99.70 39	99.74 15	99.58 134	100.00 1	98.79 180	100.00 1	99.54 67	98.58 56	99.96 110	100.00 1	99.59 16	100.00 1	100.00 1	100.00 1	99.94 124
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
ACMP	97.00 8	97.19 216	97.16 216	97.27 276	98.97 260	94.58 308	100.00 1	99.32 215	97.97 94	97.45 288	99.98 169	85.79 313	99.56 197	99.70 125	95.24 238	97.67 295
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
3Dnovator+	95.58 15	99.03 121	98.71 144	99.96 46	98.99 258	99.89 68	100.00 1	99.51 73	98.96 28	98.32 249	100.00 1	92.78 241	100.00 1	99.87 100	100.00 1	100.00 1

LF4IMVS		96.19 263	96.18 245	96.23 303	98.26 291	92.09 329	100.00 1	97.89 346	97.82 108	97.94 269	99.87 206	82.71 328	99.38 226	97.41 247	93.71 259	97.20 327

TAPA-MVS	96.40 10	97.64 197	97.37 206	98.45 207	99.94 106	95.70 282	100.00 1	99.40 174	97.65 123	99.53 175	100.00 1	99.31 60	99.66 187	80.48 347	100.00 1	100.00 1
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
MSDG		98.90 140	98.63 149	99.70 116	99.92 111	99.25 150	100.00 1	99.37 192	95.71 238	99.40 185	100.00 1	96.58 188	99.95 137	96.80 264	99.94 123	99.91 135

ACMM	97.17 6	97.37 210	97.40 204	97.29 273	99.01 251	94.64 304	100.00 1	99.25 247	98.07 85	98.44 243	99.98 169	87.38 298	99.55 202	99.25 168	95.19 240	97.69 288
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
CLD-MVS		97.64 197	97.74 193	97.36 269	99.01 251	94.76 301	100.00 1	99.34 211	99.30 4	99.00 206	99.97 177	87.49 297	99.57 193	99.96 84	95.58 223	97.75 240
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
miper_ehance_all_eth		97.81 192	97.66 197	98.23 221	99.49 207	98.37 200	99.99 190	99.11 293	94.78 261	98.25 256	99.21 285	98.18 142	98.57 285	97.35 250	92.61 273	97.76 229

ppachtmachnet_test		96.17 266	95.89 257	97.02 282	97.61 314	95.24 285	99.99 190	99.24 252	93.31 302	96.71 308	99.62 256	94.34 222	98.07 316	89.87 329	92.30 279	97.75 240

IterMVS-SCA-FT		96.72 237	96.42 236	97.62 262	99.40 223	96.83 268	99.99 190	99.14 283	94.65 267	97.55 286	99.72 228	89.65 274	98.31 300	95.62 280	92.05 281	97.73 270

SCA		98.30 175	97.98 187	99.23 166	99.41 218	98.25 210	99.99 190	99.45 99	96.91 185	99.76 165	99.58 261	89.65 274	99.54 205	98.31 214	98.79 157	99.91 135

v144192		96.40 253	95.81 260	98.17 227	97.89 306	98.11 216	99.99 190	99.06 314	93.39 299	98.75 222	99.09 290	90.43 266	98.66 275	93.10 307	90.55 301	97.75 240

v1921920		96.16 267	95.50 275	98.14 229	97.88 307	97.96 226	99.99 190	99.07 307	93.33 301	98.60 231	99.24 284	89.37 278	98.71 272	91.28 318	90.74 299	97.75 240

v1192		96.18 264	95.49 277	98.26 220	98.01 301	98.15 214	99.99 190	99.08 303	93.36 300	98.54 234	98.97 304	89.47 277	98.89 255	91.15 320	90.82 297	97.75 240

v1144		96.51 245	95.97 255	98.13 232	97.98 303	98.04 222	99.99 190	99.08 303	93.51 297	98.62 230	98.98 301	90.98 260	98.62 277	93.79 303	90.79 298	97.74 263

V42		96.65 239	96.16 247	98.11 234	98.17 297	98.23 211	99.99 190	99.09 301	93.97 286	98.74 224	99.05 294	91.09 257	98.82 261	95.46 282	89.90 304	97.27 326

MVS_Test		98.93 137	98.65 147	99.77 112	99.62 169	99.50 124	99.99 190	99.19 266	95.52 247	99.96 110	99.86 208	96.54 191	99.98 112	98.65 197	98.48 166	99.82 177

YYNet1		92.44 304	90.92 311	97.03 281	96.20 335	97.06 264	99.99 190	99.14 283	88.21 337	67.93 355	98.43 326	88.63 287	96.28 337	90.64 322	89.08 313	97.74 263

K. test v3		95.46 284	95.14 285	96.40 299	97.53 319	93.40 319	99.99 190	99.23 256	95.49 250	92.70 337	99.73 226	84.26 319	98.12 309	93.94 302	93.38 265	97.68 290

XVG-ACMP-BASELINE		96.60 242	96.52 231	96.84 292	98.41 283	93.29 320	99.99 190	99.32 215	97.76 113	98.51 238	99.29 282	81.95 331	99.54 205	98.40 209	95.03 247	97.68 290

Test_1112_low_res		98.83 144	98.60 153	99.51 139	99.69 148	98.75 181	99.99 190	99.14 283	96.81 189	98.84 216	99.06 292	97.45 163	99.89 155	98.66 195	97.75 206	99.89 150

1112_ss		98.91 138	98.71 144	99.51 139	99.69 148	98.75 181	99.99 190	99.15 278	96.82 188	98.84 216	100.00 1	97.45 163	99.89 155	98.66 195	97.75 206	99.89 150

IterMVS		96.76 234	96.46 234	97.63 260	99.41 218	96.89 266	99.99 190	99.13 287	94.74 264	97.59 285	99.66 242	89.63 276	98.28 302	95.71 276	92.31 278	97.72 276
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
RPSCF		97.37 210	98.24 173	94.76 314	99.80 132	84.57 347	99.99 190	99.05 316	94.95 259	99.82 159	100.00 1	94.03 224	100.00 1	98.15 222	98.38 174	99.70 203

OpenMVS	95.20 17	98.76 147	98.41 163	99.78 110	98.89 265	99.81 93	99.99 190	99.76 45	98.02 88	98.02 266	100.00 1	91.44 253	100.00 1	99.63 140	99.97 118	99.55 210

our_test_3		96.51 245	96.35 239	96.98 285	97.61 314	95.05 288	99.98 208	99.01 322	94.68 265	96.77 307	99.06 292	95.87 200	98.14 307	91.81 316	92.37 277	97.75 240

Anonymous20231206		93.45 300	93.17 300	94.30 318	95.00 343	89.69 338	99.98 208	98.43 333	93.30 303	94.50 329	98.59 320	90.52 263	95.73 343	77.46 353	90.73 300	97.48 319

EI-MVSNet-Vis-set		99.70 39	99.64 38	99.87 90	100.00 1	99.64 117	99.98 208	99.44 108	98.35 69	99.99 97	100.00 1	99.04 93	99.96 131	99.98 75	100.00 1	100.00 1

Vis-MVSNet (Re-imp)		98.99 129	98.89 130	99.29 161	99.64 163	98.89 177	99.98 208	99.31 220	96.74 193	99.48 178	100.00 1	98.11 145	99.10 237	98.39 210	98.34 176	99.89 150

MG-MVS		99.75 21	99.68 25	99.97 31	100.00 1	99.91 52	99.98 208	99.47 77	99.09 8	100.00 1	100.00 1	98.59 132	100.00 1	99.95 90	100.00 1	100.00 1

3Dnovator	95.63 14	99.06 118	98.76 139	99.96 46	98.86 269	99.90 60	99.98 208	99.93 26	98.95 31	98.49 240	100.00 1	92.91 240	100.00 1	99.71 123	100.00 1	100.00 1

CHOSEN 280x420		99.85 3	99.87 1	99.80 104	99.99 54	99.97 18	99.97 214	99.98 13	98.96 28	100.00 1	100.00 1	99.96 3	99.42 224	100.00 1	100.00 1	100.00 1

WR-MVS		97.09 221	96.64 226	98.46 206	98.43 282	99.09 162	99.97 214	99.33 213	95.62 242	97.76 274	99.67 240	91.17 256	98.56 287	98.49 206	89.28 311	97.74 263

new_pmnet		94.11 297	93.47 298	96.04 305	96.60 334	92.82 324	99.97 214	98.91 328	90.21 328	95.26 321	98.05 331	85.89 312	98.14 307	84.28 341	92.01 282	97.16 328

cl_fuxian		97.58 201	97.42 202	98.06 239	99.48 209	98.16 213	99.96 217	99.10 295	94.54 270	98.13 260	99.20 287	97.87 150	98.25 303	97.28 251	91.20 294	97.75 240

v1240		95.96 275	95.25 283	98.07 235	97.91 305	97.87 234	99.96 217	99.07 307	93.24 304	98.64 229	98.96 305	88.98 283	98.61 278	89.58 332	90.92 296	97.75 240

EMVS		69.88 326	69.09 329	72.24 342	84.70 353	65.82 358	99.96 217	87.08 364	49.82 359	71.51 354	84.74 357	49.30 357	75.32 358	50.97 359	43.71 356	75.59 356

EPNet_dtu		98.53 163	98.23 175	99.43 147	99.92 111	99.01 170	99.96 217	99.47 77	98.80 45	99.96 110	99.96 186	98.56 133	99.30 231	87.78 336	99.68 138	100.00 1
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
API-MVS		99.72 32	99.70 20	99.79 106	99.97 96	99.37 140	99.96 217	99.94 18	98.48 58	100.00 1	100.00 1	98.92 111	100.00 1	100.00 1	100.00 1	100.00 1

PS-MVSNAJ		99.64 58	99.57 57	99.85 93	99.78 136	99.81 93	99.95 222	99.42 126	98.38 66	100.00 1	100.00 1	98.75 124	100.00 1	99.88 99	99.99 107	99.74 198

jajsoiax		97.07 223	96.79 223	97.89 255	97.28 328	97.12 261	99.95 222	99.19 266	96.55 208	97.31 291	99.69 235	87.35 300	98.91 252	98.70 194	95.12 245	97.66 296

EI-MVSNet-UG-set		99.69 43	99.63 42	99.87 90	99.99 54	99.64 117	99.95 222	99.44 108	98.35 69	100.00 1	100.00 1	98.98 100	99.97 117	99.98 75	100.00 1	100.00 1

E-PMN		70.72 325	70.06 328	72.69 341	83.92 354	65.48 359	99.95 222	92.72 359	49.88 358	72.30 353	86.26 356	47.17 359	77.43 357	53.83 358	44.49 355	75.17 357

v8		96.35 256	95.73 266	98.21 224	98.11 298	98.23 211	99.94 226	99.07 307	92.66 314	98.29 251	99.00 300	91.46 252	98.77 268	94.17 297	88.83 316	97.62 307

CDS-MVSNet		98.96 133	98.95 122	99.01 178	99.48 209	98.36 202	99.93 227	99.37 192	96.79 190	99.31 187	99.83 213	99.77 7	98.91 252	98.07 224	97.98 193	99.77 194
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
xiu_mvs_v2_base		99.51 75	99.41 76	99.82 97	99.70 147	99.73 105	99.92 228	99.40 174	98.15 77	100.00 1	100.00 1	98.50 135	100.00 1	99.85 103	99.13 149	99.74 198

OurMVSNet-221017-0		96.14 269	95.98 254	96.62 296	97.49 322	93.44 318	99.92 228	98.16 336	95.86 233	97.65 279	99.95 193	85.71 314	98.78 265	94.93 290	94.18 258	97.64 304

EPP-MVSNet		99.10 115	99.00 114	99.40 151	99.51 203	98.68 187	99.92 228	99.43 118	95.47 251	99.65 171	100.00 1	99.51 28	99.76 178	99.53 152	98.00 192	99.75 197

pmmvs-eth3d		91.73 309	90.67 312	94.92 313	91.63 349	92.71 325	99.90 231	98.54 332	91.19 322	88.08 344	95.50 341	79.31 340	96.13 339	90.55 325	81.32 340	95.91 343

PEN-MVS		96.01 274	95.48 279	97.58 264	97.74 309	97.26 257	99.90 231	99.29 228	94.55 269	96.79 305	99.55 266	87.38 298	97.84 325	96.92 259	87.24 325	97.65 301

N_pmnet		91.88 308	93.37 299	87.40 331	97.24 329	66.33 357	99.90 231	91.05 360	89.77 331	95.65 320	98.58 321	90.05 270	98.11 311	85.39 339	92.72 272	97.75 240

PS-MVSNAJss		98.03 185	98.06 183	97.94 251	97.63 312	97.33 254	99.89 234	99.23 256	96.27 223	98.03 264	99.59 260	98.75 124	98.78 265	98.52 205	94.61 254	97.70 284

DWT-MVSNet_test		99.22 111	99.22 99	99.22 168	99.56 187	97.98 225	99.89 234	99.39 187	97.20 170	99.96 110	100.00 1	99.52 26	99.82 170	99.11 175	98.34 176	99.87 167

IterMVS-LS		97.56 202	97.44 201	97.92 254	99.38 227	97.90 230	99.89 234	99.10 295	94.41 276	98.32 249	99.54 268	97.21 169	98.11 311	97.50 243	91.62 287	97.75 240
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
QAPM		98.99 129	98.66 146	99.96 46	99.01 251	99.87 81	99.88 237	99.93 26	97.99 90	98.68 226	100.00 1	93.17 235	100.00 1	99.32 165	100.00 1	100.00 1

v7n		96.06 273	95.42 282	97.99 249	97.58 317	97.35 251	99.86 238	99.11 293	92.81 312	97.91 271	99.49 272	90.99 259	98.92 251	92.51 311	88.49 317	97.70 284

LCM-MVSNet-Re		96.52 244	97.21 214	94.44 315	99.27 233	85.80 345	99.85 239	96.61 354	95.98 229	92.75 336	98.48 323	93.97 226	97.55 328	99.58 145	98.43 169	99.98 108

SixPastTwentyTwo		95.71 280	95.49 277	96.38 300	97.42 325	93.01 321	99.84 240	98.23 335	94.75 262	95.98 317	99.97 177	85.35 315	98.43 295	94.71 291	93.17 267	97.69 288

new-patchmatchnet		90.30 315	89.46 317	92.84 326	90.77 350	88.55 342	99.83 241	98.80 331	90.07 330	87.86 345	95.00 344	78.77 341	94.30 348	84.86 340	79.15 342	95.68 344

v10		96.14 269	95.50 275	98.07 235	98.19 295	97.96 226	99.83 241	99.07 307	92.10 317	98.07 262	98.94 306	91.07 258	98.61 278	92.41 314	89.82 305	97.63 305

AUN-MVS		96.26 261	95.67 271	98.06 239	99.68 151	95.60 283	99.82 243	99.42 126	96.78 191	99.88 147	99.80 222	94.84 216	99.47 217	97.48 244	73.29 346	99.12 219

anonymousdsp		97.16 218	96.88 219	98.00 247	97.08 330	98.06 220	99.81 244	99.15 278	94.58 268	97.84 273	99.62 256	90.49 264	98.60 280	97.98 228	95.32 232	97.33 325

JIA-IIPM		97.09 221	96.34 240	99.36 155	98.88 266	98.59 191	99.81 244	99.43 118	84.81 343	99.96 110	90.34 351	98.55 134	99.52 211	97.00 256	98.28 182	99.98 108

ACMH+	96.20 13	96.49 248	96.33 241	97.00 283	99.06 247	93.80 315	99.81 244	99.31 220	97.32 161	95.89 319	99.97 177	82.62 329	99.54 205	98.34 213	94.63 253	97.65 301

PM-MVS		88.39 317	87.41 320	91.31 327	91.73 348	82.02 350	99.79 247	96.62 353	91.06 323	90.71 341	95.73 340	48.60 358	95.96 340	90.56 324	81.91 339	95.97 342

xiu_mvs_v1_base_debu		99.35 91	99.21 100	99.79 106	99.67 153	99.71 107	99.78 248	99.36 198	98.13 79	100.00 1	100.00 1	97.00 178	100.00 1	99.83 106	99.07 151	99.66 207

xiu_mvs_v1_base		99.35 91	99.21 100	99.79 106	99.67 153	99.71 107	99.78 248	99.36 198	98.13 79	100.00 1	100.00 1	97.00 178	100.00 1	99.83 106	99.07 151	99.66 207

xiu_mvs_v1_base_debi		99.35 91	99.21 100	99.79 106	99.67 153	99.71 107	99.78 248	99.36 198	98.13 79	100.00 1	100.00 1	97.00 178	100.00 1	99.83 106	99.07 151	99.66 207

baseline1		98.91 138	98.61 151	99.81 100	99.71 145	99.77 97	99.78 248	99.44 108	97.51 144	98.81 219	99.99 166	98.25 140	99.76 178	98.60 202	95.41 229	99.89 150

IS-MVSNet		99.08 116	98.91 126	99.59 130	99.65 158	99.38 137	99.78 248	99.24 252	96.70 198	99.51 176	100.00 1	98.44 137	99.52 211	98.47 207	98.39 173	99.88 161

CP-MVSNet		96.73 235	96.25 243	98.18 225	98.21 294	98.67 188	99.77 253	99.32 215	95.06 257	97.20 294	99.65 244	90.10 268	98.19 304	98.06 225	88.90 314	97.66 296

tpm cat1		98.05 184	97.76 192	98.92 184	99.50 206	97.10 263	99.77 253	99.30 223	90.20 329	99.72 168	98.71 316	97.71 154	99.86 160	96.75 268	98.20 186	99.81 181

EU-MVSNet		96.63 240	96.53 230	96.94 287	97.59 316	96.87 267	99.76 255	99.47 77	96.35 219	96.85 303	99.78 224	92.57 245	96.27 338	95.33 283	91.08 295	97.68 290

ACMMP		99.65 56	99.57 57	99.89 85	99.99 54	99.66 115	99.75 256	99.73 54	98.16 75	99.75 166	100.00 1	98.90 113	100.00 1	99.96 84	99.88 128	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
DIV-MVS_2432*1600		91.16 311	90.09 315	94.35 317	94.44 345	91.27 335	99.74 257	99.08 303	90.82 325	94.53 328	94.91 346	86.11 308	94.78 346	82.67 343	68.52 348	96.99 331

EI-MVSNet		97.98 187	97.93 188	98.16 228	99.11 239	97.84 235	99.74 257	99.29 228	94.39 277	98.65 227	100.00 1	97.21 169	98.88 258	97.62 241	95.31 233	97.75 240

CVMVSNet		98.56 160	98.47 161	98.82 190	99.11 239	97.67 241	99.74 257	99.47 77	97.57 137	99.06 203	100.00 1	95.72 203	98.97 248	98.21 219	97.33 213	99.83 173

MAR-MVS		99.49 80	99.36 84	99.89 85	99.97 96	99.66 115	99.74 257	99.95 15	97.89 102	100.00 1	100.00 1	96.71 187	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
UnsupCasMVSNet_eth		94.25 293	93.89 292	95.34 308	97.63 312	92.13 328	99.73 261	99.36 198	94.88 260	92.78 334	98.63 319	82.72 327	96.53 334	94.57 292	84.73 334	97.36 323

DeepC-MVS_fast	98.92 1	99.75 21	99.67 30	99.99 9	99.99 54	99.96 20	99.73 261	99.52 69	99.06 11	100.00 1	100.00 1	98.80 122	100.00 1	99.95 90	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
WR-MVS_H		96.73 235	96.32 242	97.95 250	98.26 291	97.88 232	99.72 263	99.43 118	95.06 257	96.99 298	98.68 317	93.02 239	98.53 288	97.43 246	88.33 318	97.43 320

PS-CasMVS		96.34 257	95.78 263	98.03 246	98.18 296	98.27 209	99.71 264	99.32 215	94.75 262	96.82 304	99.65 244	86.98 303	98.15 306	97.74 236	88.85 315	97.66 296

FMVSNet3		97.30 213	96.95 217	98.37 212	99.65 158	99.25 150	99.71 264	99.28 233	94.23 279	98.53 235	98.91 308	93.30 233	98.11 311	95.31 284	93.60 260	97.73 270

PMMVS2		79.15 321	77.28 325	84.76 334	82.34 355	72.66 351	99.70 266	95.11 357	71.68 351	84.78 349	90.87 349	32.05 362	89.99 353	75.53 354	63.45 352	91.64 348

AdaColmap		99.44 84	99.26 91	99.95 58	100.00 1	99.86 84	99.70 266	99.99 10	98.53 57	99.90 142	100.00 1	95.34 207	100.00 1	99.92 94	100.00 1	100.00 1

tfpnnormal		96.36 255	95.69 270	98.37 212	98.55 278	98.71 185	99.69 268	99.45 99	93.16 306	96.69 309	99.71 230	88.44 292	98.99 245	94.17 297	91.38 292	97.41 321

tpm2		98.64 155	98.58 155	98.81 192	99.42 217	97.12 261	99.69 268	99.37 192	93.63 294	99.94 133	99.67 240	98.96 105	99.47 217	98.62 201	97.95 194	99.83 173

Vis-MVSNet		98.52 164	98.25 172	99.34 157	99.68 151	98.55 192	99.68 270	99.41 172	97.34 159	99.94 133	100.00 1	90.38 267	99.70 186	99.03 178	98.84 156	99.76 196
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
CostFormer		98.84 143	98.77 138	99.04 176	99.41 218	97.58 244	99.67 271	99.35 206	94.66 266	99.96 110	99.36 279	99.28 69	99.74 181	99.41 158	97.81 203	99.81 181

DSMNet-mixed		95.18 288	95.21 284	95.08 309	96.03 337	90.21 337	99.65 272	93.64 358	92.91 309	98.34 247	97.40 336	90.05 270	95.51 344	91.02 321	97.86 198	99.51 213

HY-MVS	96.53 9	99.50 78	99.35 86	99.96 46	99.81 122	99.93 42	99.64 273	100.00 1	97.97 94	99.84 150	99.85 210	98.94 108	99.99 89	99.86 101	98.23 184	99.95 121

ACMH	96.25 11	96.77 233	96.62 228	97.21 277	98.96 261	94.43 310	99.64 273	99.33 213	97.43 152	96.55 310	99.97 177	83.52 324	99.54 205	99.07 177	95.13 244	97.66 296
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
KD-MVS_2432*1600		94.15 294	93.08 301	97.35 270	99.53 191	97.83 236	99.63 275	99.19 266	92.88 310	96.29 312	97.68 333	98.84 117	96.70 331	89.73 330	63.92 350	97.53 315

miper_refine_blended		94.15 294	93.08 301	97.35 270	99.53 191	97.83 236	99.63 275	99.19 266	92.88 310	96.29 312	97.68 333	98.84 117	96.70 331	89.73 330	63.92 350	97.53 315

test_part1		96.98 228	96.36 238	98.85 189	99.78 136	99.77 97	99.63 275	99.30 223	92.74 313	97.05 296	99.52 269	93.10 238	99.02 241	98.02 226	88.10 319	97.76 229

eth_miper_zixun_eth		97.47 207	97.28 210	98.06 239	99.41 218	97.94 228	99.62 278	99.08 303	94.46 275	98.19 259	99.56 265	96.91 183	98.50 290	96.78 265	91.49 289	97.74 263

test_0402		94.35 292	93.70 295	96.32 301	97.92 304	93.60 316	99.61 279	98.85 330	88.19 338	94.68 326	99.48 273	80.01 337	98.58 284	89.39 333	95.15 243	96.77 334

mvs_tets		97.00 227	96.69 225	97.94 251	97.41 327	97.27 256	99.60 280	99.18 271	96.51 212	97.35 290	99.69 235	86.53 306	98.91 252	98.84 186	95.09 246	97.65 301

EPMVS		99.25 108	99.13 108	99.60 128	99.60 173	99.20 156	99.60 280	100.00 1	96.93 182	99.92 139	99.36 279	99.05 90	99.71 185	98.77 190	98.94 155	99.90 144

TAMVS		98.76 147	98.73 141	98.86 188	99.44 216	97.69 240	99.57 282	99.34 211	96.57 207	99.12 198	99.81 219	98.83 119	99.16 235	97.97 231	97.91 196	99.73 202

MDTV_nov1_ep13_2view						99.24 152	99.56 283		96.31 222	99.96 110		98.86 116		98.92 182		99.89 150

CL-MVSNet_2432*1600		91.07 312	90.35 314	93.24 324	93.27 346	89.16 340	99.55 284	99.25 247	92.34 315	95.23 322	97.05 337	88.86 286	93.59 350	80.67 346	66.95 349	96.96 332

LS3D		99.31 99	99.13 108	99.87 90	99.99 54	99.71 107	99.55 284	99.46 92	97.32 161	99.82 159	100.00 1	96.85 184	99.97 117	99.14 172	100.00 1	99.92 133

XXY-MVS		97.14 220	96.63 227	98.67 197	98.65 274	98.92 176	99.54 286	99.29 228	95.57 244	97.63 280	99.83 213	87.79 295	99.35 229	98.39 210	92.95 270	97.75 240

tpm		98.24 180	98.22 177	98.32 216	99.13 238	95.79 281	99.53 287	99.12 292	95.20 255	99.96 110	99.36 279	97.58 158	99.28 232	97.41 247	96.67 221	99.88 161

tpmrst		98.98 132	98.93 124	99.14 171	99.61 171	97.74 239	99.52 288	99.36 198	96.05 228	99.98 102	99.64 248	99.04 93	99.86 160	98.94 180	98.19 187	99.82 177

DP-MVS		98.86 142	98.54 157	99.81 100	99.97 96	99.45 132	99.52 288	99.40 174	94.35 278	98.36 245	100.00 1	96.13 196	99.97 117	99.12 174	100.00 1	100.00 1

VNet		99.04 120	98.75 140	99.90 82	99.81 122	99.75 101	99.50 290	99.47 77	98.36 68	100.00 1	99.99 166	94.66 218	100.00 1	99.90 96	97.09 215	99.96 116

VPNet		96.41 250	95.76 264	98.33 215	98.61 276	98.30 207	99.48 291	99.45 99	96.98 181	98.87 213	99.88 205	81.57 332	98.93 250	99.22 171	87.82 322	97.76 229

dp		98.72 149	98.61 151	99.03 177	99.53 191	97.39 249	99.45 292	99.39 187	95.62 242	99.94 133	99.52 269	98.83 119	99.82 170	96.77 267	98.42 170	99.89 150

FMVSNet2		96.22 262	95.60 273	98.06 239	99.53 191	98.33 204	99.45 292	99.27 241	93.71 289	98.03 264	98.84 311	84.23 320	98.10 314	93.97 301	93.40 264	97.73 270

LTVRE_ROB	95.29 16	96.32 258	96.10 248	96.99 284	98.55 278	93.88 314	99.45 292	99.28 233	94.50 273	96.46 311	99.52 269	84.86 316	99.48 216	97.26 252	95.03 247	97.59 311
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
MDA-MVSNet-bldmvs		91.65 310	89.94 316	96.79 294	96.72 332	96.70 271	99.42 295	98.94 325	88.89 333	66.97 358	98.37 327	81.43 333	95.91 341	89.24 335	89.46 310	97.75 240

TinyColmap		95.50 283	95.12 286	96.64 295	98.69 273	93.00 322	99.40 296	97.75 348	96.40 217	96.14 315	99.87 206	79.47 338	99.50 214	93.62 304	94.72 252	97.40 322

MDTV_nov1_ep13			98.94 123		99.53 191	98.36 202	99.39 297	99.46 92	96.54 209	99.99 97	99.63 252	98.92 111	99.86 160	98.30 216	98.71 159

VPA-MVSNet		97.03 226	96.43 235	98.82 190	98.64 275	99.32 143	99.38 298	99.47 77	96.73 195	98.91 211	98.94 306	87.00 302	99.40 225	99.23 169	89.59 307	97.76 229

MVS-HIRNet		94.12 296	92.73 305	98.29 217	99.33 229	95.95 278	99.38 298	99.19 266	74.54 350	98.26 255	86.34 355	86.07 309	99.06 239	91.60 317	99.87 130	99.85 169

PatchmatchNet		99.03 121	98.96 118	99.26 164	99.49 207	98.33 204	99.38 298	99.45 99	96.64 204	99.96 110	99.58 261	99.49 35	99.50 214	97.63 240	99.00 154	99.93 131
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
Anonymous202405211		97.87 189	97.53 200	98.90 185	99.81 122	96.70 271	99.35 301	99.46 92	92.98 308	98.83 218	99.99 166	90.63 262	100.00 1	99.70 125	97.03 216	100.00 1

MIMVSNet1		91.96 305	91.20 308	94.23 320	94.94 344	91.69 332	99.34 302	99.22 258	88.23 336	94.18 331	98.45 324	75.52 346	93.41 351	79.37 349	91.49 289	97.60 310

test_post1							99.32 303				88.24 354	99.33 55	99.59 190	98.31 214

tpmvs		98.59 157	98.38 166	99.23 166	99.69 148	97.90 230	99.31 304	99.47 77	94.52 271	99.68 170	99.28 283	97.64 157	99.89 155	97.71 237	98.17 188	99.89 150

COLMAP_ROB	97.10 7	98.29 177	98.17 178	98.65 198	99.94 106	97.39 249	99.30 305	99.40 174	95.64 240	97.75 277	100.00 1	92.69 244	99.95 137	98.89 184	99.92 125	98.62 224
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
TR-MVS		98.14 182	97.74 193	99.33 158	99.59 176	98.28 208	99.27 306	99.21 263	96.42 215	99.15 196	99.94 197	88.87 285	99.79 174	98.88 185	98.29 181	99.93 131

OpenMVS_ROB	88.34 20	91.89 307	91.12 309	94.19 321	95.55 340	87.63 343	99.26 307	98.03 341	86.61 340	90.65 342	96.82 338	70.14 352	98.78 265	86.54 338	96.50 222	96.15 339

FMVSNet5		95.32 285	95.43 281	94.99 311	99.39 226	92.99 323	99.25 308	99.24 252	90.45 326	97.44 289	98.45 324	95.78 202	94.39 347	87.02 337	91.88 285	97.59 311

pm-mvs1		95.76 279	95.01 287	98.00 247	98.23 293	97.45 247	99.24 309	99.04 319	93.13 307	95.93 318	99.72 228	86.28 307	98.84 260	95.62 280	87.92 321	97.72 276

1314		99.38 88	99.19 104	99.96 46	98.88 266	99.89 68	99.24 309	99.93 26	98.88 37	98.79 221	100.00 1	97.02 174	100.00 1	100.00 1	100.00 1	100.00 1

1121		99.63 62	99.51 70	99.99 9	99.99 54	99.96 20	99.24 309	99.74 52	97.89 102	100.00 1	100.00 1	99.39 53	100.00 1	99.33 163	100.00 1	100.00 1

MVS		99.22 111	98.96 118	99.98 22	99.00 255	99.95 29	99.24 309	99.94 18	98.14 78	98.88 212	100.00 1	95.63 205	100.00 1	99.85 103	100.00 1	100.00 1

ADS-MVSNet2		98.28 178	98.51 159	97.62 262	99.51 203	95.03 289	99.24 309	99.41 172	95.52 247	99.96 110	99.70 233	97.57 159	97.94 323	97.11 254	98.54 162	99.88 161

ADS-MVSNet		98.70 151	98.51 159	99.28 162	99.51 203	98.39 197	99.24 309	99.44 108	95.52 247	99.96 110	99.70 233	97.57 159	99.58 192	97.11 254	98.54 162	99.88 161

TransMVSNet (Re)		94.78 290	93.72 294	97.93 253	98.34 285	97.88 232	99.23 315	97.98 344	91.60 319	94.55 327	99.71 230	87.89 293	98.36 297	89.30 334	84.92 333	97.56 313

PCF-MVS	98.23 3	98.69 152	98.37 168	99.62 125	99.78 136	99.02 168	99.23 315	99.06 314	96.43 214	98.08 261	100.00 1	94.72 217	99.95 137	98.16 221	99.91 126	99.90 144
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
NR-MVSNet		96.63 240	96.04 251	98.38 211	98.31 287	98.98 173	99.22 317	99.35 206	95.87 231	94.43 330	99.65 244	92.73 243	98.40 296	96.78 265	88.05 320	97.75 240

VDD-MVS		96.58 243	95.99 253	98.34 214	99.52 198	95.33 284	99.18 318	99.38 190	96.64 204	99.77 163	100.00 1	72.51 349	100.00 1	100.00 1	96.94 219	99.70 203

GBi-Net		96.07 271	95.80 261	96.89 289	99.53 191	94.87 290	99.18 318	99.27 241	93.71 289	98.53 235	98.81 312	84.23 320	98.07 316	95.31 284	93.60 260	97.72 276

test1		96.07 271	95.80 261	96.89 289	99.53 191	94.87 290	99.18 318	99.27 241	93.71 289	98.53 235	98.81 312	84.23 320	98.07 316	95.31 284	93.60 260	97.72 276

FMVSNet1		94.45 291	93.63 296	96.89 289	98.87 268	94.87 290	99.18 318	99.27 241	90.95 324	97.31 291	98.81 312	72.89 348	98.07 316	92.61 309	92.81 271	97.72 276

UGNet		98.41 170	98.11 179	99.31 160	99.54 188	98.55 192	99.18 318	100.00 1	98.64 54	99.79 161	99.04 295	87.61 296	100.00 1	99.30 166	99.89 127	99.40 215
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
GG-mvs-BLEND				99.59 130	99.54 188	99.49 127	99.17 323	99.52 69		99.96 110	99.68 239	100.00 1	99.33 230	99.71 123	99.99 107	99.96 116

Anonymous20240529		96.93 230	96.22 244	99.05 174	99.79 135	97.30 255	99.16 324	99.47 77	88.51 335	98.69 225	100.00 1	83.50 325	100.00 1	99.83 106	97.02 217	99.83 173

LFMVS		97.42 208	96.62 228	99.81 100	99.80 132	99.50 124	99.16 324	99.56 66	94.48 274	100.00 1	100.00 1	79.35 339	100.00 1	99.89 98	97.37 212	99.94 124

Anonymous20231211		96.29 259	95.70 267	98.07 235	99.80 132	97.49 246	99.15 326	99.40 174	89.11 332	97.75 277	99.45 275	88.93 284	98.98 246	98.26 218	89.47 309	97.73 270

VDDNet		96.39 254	95.55 274	98.90 185	99.27 233	97.45 247	99.15 326	99.92 30	91.28 321	99.98 102	100.00 1	73.55 347	100.00 1	99.85 103	96.98 218	99.24 216

UniMVSNet_ETH3D		95.28 286	94.41 291	97.89 255	98.91 263	95.14 287	99.13 328	99.35 206	92.11 316	97.17 295	99.66 242	70.28 351	99.36 227	97.88 233	95.18 241	99.16 217

CR-MVSNet		98.02 186	97.71 196	98.93 183	99.31 230	98.86 178	99.13 328	99.00 323	96.53 210	99.96 110	98.98 301	96.94 181	98.10 314	91.18 319	98.40 171	99.84 170

RPMNet		95.26 287	93.82 293	99.56 137	99.31 230	98.86 178	99.13 328	99.42 126	79.82 348	99.96 110	95.13 343	95.69 204	99.98 112	77.54 352	98.40 171	99.84 170

ab-mvs		98.42 169	98.02 185	99.61 126	99.71 145	99.00 172	99.10 331	99.64 63	96.70 198	99.04 205	99.81 219	90.64 261	99.98 112	99.64 139	97.93 195	99.84 170

TDRefinement		91.93 306	90.48 313	96.27 302	81.60 356	92.65 326	99.10 331	97.61 349	93.96 287	93.77 332	99.85 210	80.03 336	99.53 210	97.82 235	70.59 347	96.63 336

UA-Net		99.06 118	98.83 132	99.74 113	99.52 198	99.40 136	99.08 333	99.45 99	97.64 125	99.83 152	100.00 1	95.80 201	99.94 148	98.35 212	99.80 135	99.88 161

PatchT		95.90 277	94.95 289	98.75 194	99.03 249	98.39 197	99.08 333	99.32 215	85.52 341	99.96 110	94.99 345	97.94 148	98.05 320	80.20 348	98.47 167	99.81 181

gg-mvs-nofinetune		96.95 229	96.10 248	99.50 141	99.41 218	99.36 141	99.07 335	99.52 69	83.69 345	99.96 110	83.60 358	100.00 1	99.20 234	99.68 132	99.99 107	99.96 116

EG-PatchMatch MVS		92.94 302	92.49 306	94.29 319	95.87 338	87.07 344	99.07 335	98.11 339	93.19 305	88.98 343	98.66 318	70.89 350	99.08 238	92.43 313	95.21 239	96.72 335

pmmvs6		93.64 298	92.87 303	95.94 306	97.47 324	91.41 334	98.92 337	99.02 320	87.84 339	95.01 324	99.61 258	77.24 344	98.77 268	94.33 295	86.41 331	97.63 305

Patchmtry		96.81 232	96.37 237	98.14 229	99.31 230	98.55 192	98.91 338	99.00 323	90.45 326	97.92 270	98.98 301	96.94 181	98.12 309	94.27 296	91.53 288	97.75 240

MS-PatchMatch		95.66 281	95.87 258	95.05 310	97.80 308	89.25 339	98.88 339	99.30 223	96.35 219	96.86 302	99.01 299	81.35 334	99.43 222	93.30 306	99.98 115	96.46 337

MVP-Stereo		96.51 245	96.48 233	96.60 297	95.65 339	94.25 311	98.84 340	98.16 336	95.85 235	95.23 322	99.04 295	92.54 246	99.13 236	92.98 308	99.98 115	96.43 338
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
Patchmatch-test		97.83 191	97.42 202	99.06 172	99.08 242	97.66 242	98.66 341	99.21 263	93.65 293	98.25 256	99.58 261	99.47 39	99.57 193	90.25 328	98.59 161	99.95 121

MVS_0304		95.11 289	94.84 290	95.91 307	99.60 173	91.24 336	98.64 342	99.88 33	94.51 272	99.62 173	98.31 330	69.19 353	98.82 261	95.22 287	98.60 160	97.66 296

UnsupCasMVSNet_bld		89.50 316	88.00 319	93.99 322	95.30 341	88.86 341	98.52 343	99.28 233	85.50 342	87.80 346	94.11 347	61.63 355	96.96 330	90.63 323	79.26 341	96.15 339

MIMVSNet		97.06 224	96.73 224	98.05 243	99.38 227	96.64 273	98.47 344	99.35 206	93.41 298	99.48 178	98.53 322	89.66 273	97.70 327	94.16 299	98.11 190	99.80 191

FPMVS		77.92 323	79.45 323	73.34 340	76.87 359	46.81 364	98.24 345	99.05 316	59.89 355	73.55 352	98.34 328	36.81 361	86.55 354	80.96 345	91.35 293	86.65 352

Patchmatch-RL test		93.49 299	93.63 296	93.05 325	91.78 347	83.41 348	98.21 346	96.95 351	91.58 320	91.05 339	97.64 335	99.40 52	95.83 342	94.11 300	81.95 338	99.91 135

CMPMVS	66.12 22	90.65 313	92.04 307	86.46 332	96.18 336	66.87 356	98.03 347	99.38 190	83.38 346	85.49 348	99.55 266	77.59 343	98.80 264	94.44 294	94.31 257	93.72 347
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
Effi-MVS+		98.58 158	98.24 173	99.61 126	99.60 173	99.26 148	97.85 348	99.10 295	96.22 225	99.97 106	99.89 204	93.75 227	99.77 177	99.43 156	98.34 176	99.81 181

ambc				88.45 329	86.84 352	70.76 354	97.79 349	98.02 343		90.91 340	95.14 342	38.69 360	98.51 289	94.97 289	84.23 335	96.09 341

LCM-MVSNet		79.01 322	76.93 326	85.27 333	78.28 358	68.01 355	96.57 350	98.03 341	55.10 356	82.03 350	93.27 348	31.99 363	93.95 349	82.72 342	74.37 345	93.84 346

MVE	68.59 21	67.22 327	64.68 331	74.84 337	74.67 361	62.32 361	95.84 351	90.87 361	50.98 357	58.72 359	81.05 359	12.20 367	78.95 356	61.06 357	56.75 353	83.24 354
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
ANet_high		66.05 328	63.44 332	73.88 339	61.14 362	63.45 360	95.68 352	87.18 362	79.93 347	47.35 360	80.68 360	22.35 364	72.33 361	61.24 356	35.42 357	85.88 353

Gipuma		84.73 318	83.50 321	88.40 330	97.50 320	82.21 349	88.87 353	99.05 316	65.81 352	85.71 347	90.49 350	53.70 356	96.31 336	78.64 350	91.74 286	86.67 351
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
PMVS	60.66 23	65.98 329	65.05 330	68.75 343	55.06 364	38.40 365	88.19 354	96.98 350	48.30 360	44.82 361	88.52 353	12.22 366	86.49 355	67.58 355	83.79 336	81.35 355
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
tmp_tt		75.80 324	74.26 327	80.43 335	52.91 365	53.67 363	87.42 355	97.98 344	61.80 354	67.04 357	100.00 1	76.43 345	96.40 335	96.47 269	28.26 358	91.23 349

wuyk23d		28.28 330	29.73 334	23.92 344	75.89 360	32.61 366	66.50 356	12.88 366	16.09 361	14.59 362	16.59 362	12.35 365	32.36 362	39.36 360	13.36 360	6.79 358

uanet_test		0.01 334	0.02 337	0.00 345	0.00 366	0.00 367	0.00 357	0.00 367	0.00 362	0.00 363	0.14 363	0.00 368	0.00 363	0.00 361	0.00 361	0.00 359

cdsmvs_eth3d_5k		24.41 331	32.55 333	0.00 345	0.00 366	0.00 367	0.00 357	99.39 187	0.00 362	0.00 363	100.00 1	93.55 230	0.00 363	0.00 361	0.00 361	0.00 359

pcd_1.5k_mvsjas		8.24 333	10.99 336	0.00 345	0.00 366	0.00 367	0.00 357	0.00 367	0.00 362	0.00 363	0.14 363	98.75 124	0.00 363	0.00 361	0.00 361	0.00 359

sosnet-low-res		0.01 334	0.02 337	0.00 345	0.00 366	0.00 367	0.00 357	0.00 367	0.00 362	0.00 363	0.14 363	0.00 368	0.00 363	0.00 361	0.00 361	0.00 359

sosnet		0.01 334	0.02 337	0.00 345	0.00 366	0.00 367	0.00 357	0.00 367	0.00 362	0.00 363	0.14 363	0.00 368	0.00 363	0.00 361	0.00 361	0.00 359

uncertanet		0.01 334	0.02 337	0.00 345	0.00 366	0.00 367	0.00 357	0.00 367	0.00 362	0.00 363	0.14 363	0.00 368	0.00 363	0.00 361	0.00 361	0.00 359

Regformer		0.01 334	0.02 337	0.00 345	0.00 366	0.00 367	0.00 357	0.00 367	0.00 362	0.00 363	0.14 363	0.00 368	0.00 363	0.00 361	0.00 361	0.00 359

ab-mvs-re		8.33 332	11.11 335	0.00 345	0.00 366	0.00 367	0.00 357	0.00 367	0.00 362	0.00 363	100.00 1	0.00 368	0.00 363	0.00 361	0.00 361	0.00 359

uanet		0.01 334	0.02 337	0.00 345	0.00 366	0.00 367	0.00 357	0.00 367	0.00 362	0.00 363	0.14 363	0.00 368	0.00 363	0.00 361	0.00 361	0.00 359

ZD-MVS					100.00 1	99.98 13		99.80 39	97.31 163	100.00 1	100.00 1	99.32 58	99.99 89	100.00 1	100.00 1

IU-MVS					100.00 1	99.99 3		99.42 126	99.12 6	100.00 1				100.00 1	100.00 1	100.00 1

test_241102_TWO								99.42 126	99.03 19	100.00 1	100.00 1	99.56 19	100.00 1	100.00 1	100.00 1	100.00 1

test_241102_ONE					100.00 1	99.99 3		99.42 126	99.03 19	100.00 1	100.00 1	99.50 33	100.00 1

test_0728_THIRD									98.79 46	100.00 1	100.00 1	99.61 13	100.00 1	100.00 1	100.00 1	100.00 1

GSMVS																99.91 135

test_part2					100.00 1	99.99 3				100.00 1

sam_mvs1												99.29 67				99.91 135

sam_mvs												99.33 55

MTGPA								99.42 126

test_post											89.05 352	99.49 35	99.59 190

patchmatchnet-post											97.79 332	99.41 51	99.54 205

gm-plane-assit					99.52 198	97.26 257			95.86 233		100.00 1		99.43 222	98.76 191

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 78		99.42 126		100.00 1			99.97 117

TestCases				98.99 179	99.93 108	97.35 251		99.40 174	97.08 177	99.09 199	99.98 169	93.37 231	99.95 137	96.94 257	99.84 132	99.68 205

test_prior				99.90 82	100.00 1	99.75 101		99.73 54					99.97 117			100.00 1

新几何1				99.99 9	100.00 1	99.96 20		99.81 38	97.89 102	100.00 1	100.00 1	99.20 79	100.00 1	97.91 232	100.00 1	100.00 1

旧先验1					99.99 54	99.88 78		99.82 36			100.00 1	99.27 70			100.00 1	100.00 1

原ACMM1				99.93 76	100.00 1	99.80 95		99.66 62	98.18 74	100.00 1	100.00 1	99.43 47	100.00 1	99.50 154	100.00 1	100.00 1

testdata2													100.00 1	97.36 249

segment_acmp												99.55 21

testdata				99.66 121	99.99 54	98.97 175		99.73 54	97.96 98	100.00 1	100.00 1	99.42 49	100.00 1	99.28 167	100.00 1	100.00 1

test12				99.95 58	99.99 54	99.89 68		99.42 126		100.00 1		99.24 73	99.97 117		100.00 1	100.00 1

plane_prior7					99.00 255	94.78 300

plane_prior6					99.06 247	94.80 296						88.58 290

plane_prior5								99.40 174					99.55 202	99.79 112	95.57 227	97.76 229

plane_prior4											99.97 177

plane_prior3						94.79 299			99.03 19	99.08 201

plane_prior1					99.02 250

n2								0.00 367

nn								0.00 367

door-mid								96.32 355

lessismore_v0				96.05 304	97.55 318	91.80 331		99.22 258		91.87 338	99.91 202	83.50 325	98.68 273	92.48 312	90.42 303	97.68 290

LGP-MVS_train				97.28 274	98.85 270	94.60 305		99.37 192	97.35 157	98.85 214	99.98 169	86.66 304	99.56 197	99.55 147	95.26 235	97.70 284

test11								99.42 126

door								96.13 356

HQP5-MVS						94.82 293

BP-MVS														99.79 112

HQP4-MVS										99.17 192			99.57 193			97.77 227

HQP3-MVS								99.40 174							95.58 223

HQP2-MVS												88.61 288

NP-MVS					99.07 243	94.81 295					99.97 177

ACMMP++_ref															94.58 255

ACMMP++															95.17 242

Test By Simon												99.10 87

ITE_SJBPF				96.84 292	98.96 261	93.49 317		98.12 338	98.12 82	98.35 246	99.97 177	84.45 317	99.56 197	95.63 279	95.25 237	97.49 317

DeepMVS_CX				89.98 328	98.90 264	71.46 353		99.18 271	97.61 129	96.92 299	99.83 213	86.07 309	99.83 167	96.02 274	97.65 210	98.65 223

High-resolution multi-view benchmark