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

(*) 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 Infoallhigh-res
multi-view
indooroutdoorbotani.boulde.bridgedoorexhibi.lectur.living.loungeobserv.old co.statueterrac.
sort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysorted bysort by
SMA-MVS89.08 589.23 588.61 294.25 2373.73 792.40 1893.63 1974.77 9992.29 295.97 274.28 2797.24 588.58 796.91 194.87 7
test_0728_THIRD78.38 3292.12 495.78 481.46 297.40 289.42 296.57 294.67 13
HPM-MVS++copyleft89.02 689.15 688.63 195.01 576.03 192.38 2292.85 5080.26 1387.78 2294.27 2875.89 1296.81 1587.45 1396.44 393.05 82
DVP-MVS89.60 190.35 187.33 4095.27 271.25 5793.49 592.73 5577.33 4592.12 495.78 480.98 397.40 289.08 496.41 493.33 71
test_0728_SECOND87.71 2895.34 171.43 5693.49 594.23 697.49 189.08 496.41 494.21 28
ACMMP_NAP88.05 1588.08 1687.94 1493.70 3573.05 2090.86 4793.59 2076.27 7488.14 1895.09 1071.06 5196.67 2087.67 1096.37 694.09 32
DPE-MVS89.48 389.98 288.01 1194.80 672.69 2991.59 3594.10 975.90 7892.29 295.66 681.67 197.38 487.44 1496.34 793.95 40
MP-MVS-pluss87.67 2087.72 2087.54 3493.64 3872.04 4689.80 7493.50 2375.17 9486.34 3095.29 770.86 5296.00 4588.78 696.04 894.58 16
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
xxxxxxxxxxxxxcwj88.46 988.74 987.64 3292.78 5571.95 4792.40 1894.74 275.71 8089.16 1195.10 875.65 1496.19 3787.07 1596.01 994.79 8
xxxxxxxxxxxx88.46 988.74 987.64 3292.78 5571.95 4792.40 1894.74 275.71 8089.16 1195.10 875.65 1496.19 3787.07 1596.01 994.79 8
CNVR-MVS88.93 789.13 788.33 494.77 773.82 690.51 5493.00 4180.90 988.06 2094.06 3776.43 996.84 1388.48 895.99 1194.34 24
PHI-MVS86.43 4386.17 4687.24 4190.88 8470.96 6292.27 2694.07 1172.45 13685.22 4091.90 7369.47 6796.42 3083.28 4795.94 1294.35 23
ETH3D-3000-0.188.09 1288.29 1387.50 3692.76 5771.89 5191.43 3994.70 474.47 10588.86 1494.61 1675.23 1795.84 4986.62 2095.92 1394.78 10
test_prior386.73 3786.86 3786.33 5892.61 6169.59 8688.85 9892.97 4675.41 8784.91 4493.54 4374.28 2795.48 5983.31 4495.86 1493.91 41
test_prior288.85 9875.41 8784.91 4493.54 4374.28 2783.31 4495.86 14
SteuartSystems-ACMMP88.72 888.86 888.32 592.14 6772.96 2393.73 393.67 1880.19 1488.10 1994.80 1173.76 3197.11 787.51 1295.82 1694.90 6
Skip Steuart: Steuart Systems R&D Blog.
ZNCC-MVS87.94 1787.85 1888.20 894.39 2073.33 1793.03 1093.81 1676.81 5785.24 3994.32 2771.76 4696.93 1285.53 2395.79 1794.32 25
ETH3D cwj APD-0.1687.31 3087.27 2687.44 3891.60 7472.45 3890.02 6894.37 571.76 14687.28 2594.27 2875.18 1896.08 4185.16 2495.77 1893.80 51
ETH3 D test640087.50 2387.44 2487.70 2993.71 3471.75 5290.62 5294.05 1270.80 16187.59 2493.51 4577.57 796.63 2383.31 4495.77 1894.72 12
9.1488.26 1492.84 5491.52 3894.75 173.93 11788.57 1694.67 1475.57 1695.79 5186.77 1795.76 20
DeepPCF-MVS80.84 188.10 1188.56 1186.73 5192.24 6569.03 9589.57 8093.39 2977.53 4289.79 1094.12 3578.98 596.58 2885.66 2195.72 2194.58 16
train_agg86.43 4386.20 4487.13 4493.26 4472.96 2388.75 10291.89 8868.69 20785.00 4293.10 5474.43 2395.41 6384.97 2695.71 2293.02 84
test9_res84.90 2795.70 2392.87 88
APDe-MVS89.15 489.63 487.73 2494.49 1471.69 5393.83 293.96 1375.70 8391.06 896.03 176.84 897.03 989.09 395.65 2494.47 20
agg_prior282.91 5295.45 2592.70 91
CDPH-MVS85.76 5185.29 5787.17 4393.49 4171.08 6088.58 10992.42 6768.32 21284.61 5293.48 4672.32 4196.15 4079.00 7895.43 2694.28 27
DeepC-MVS79.81 287.08 3586.88 3687.69 3091.16 7872.32 4290.31 6193.94 1477.12 4982.82 7894.23 3172.13 4497.09 884.83 3095.37 2793.65 58
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
zzz-MVS87.53 2287.41 2587.90 1894.18 2774.25 290.23 6392.02 7979.45 1985.88 3294.80 1168.07 7696.21 3586.69 1895.34 2893.23 74
MTAPA87.23 3187.00 3287.90 1894.18 2774.25 286.58 16992.02 7979.45 1985.88 3294.80 1168.07 7696.21 3586.69 1895.34 2893.23 74
agg_prior186.22 4786.09 4886.62 5492.85 5271.94 4988.59 10891.78 9468.96 20284.41 5593.18 5374.94 1994.93 8284.75 3295.33 3093.01 85
DeepC-MVS_fast79.65 386.91 3686.62 3987.76 2393.52 4072.37 4091.26 4193.04 3776.62 6484.22 5993.36 5071.44 4996.76 1780.82 6795.33 3094.16 29
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
MP-MVScopyleft87.71 1987.64 2187.93 1794.36 2173.88 492.71 1792.65 5977.57 3883.84 6594.40 2672.24 4296.28 3385.65 2295.30 3293.62 60
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
MCST-MVS87.37 2887.25 2887.73 2494.53 1372.46 3789.82 7293.82 1573.07 13184.86 4992.89 6076.22 1096.33 3184.89 2995.13 3394.40 21
GST-MVS87.42 2687.26 2787.89 2194.12 2972.97 2292.39 2193.43 2776.89 5584.68 5093.99 3970.67 5696.82 1484.18 4095.01 3493.90 43
APD-MVScopyleft87.44 2487.52 2287.19 4294.24 2472.39 3991.86 3392.83 5173.01 13388.58 1594.52 1773.36 3296.49 2984.26 3795.01 3492.70 91
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
NCCC88.06 1388.01 1788.24 794.41 1873.62 891.22 4492.83 5181.50 685.79 3593.47 4873.02 3797.00 1184.90 2794.94 3694.10 31
ACMMPR87.44 2487.23 2988.08 1094.64 873.59 993.04 893.20 3376.78 5984.66 5194.52 1768.81 7496.65 2184.53 3394.90 3794.00 38
HFP-MVS87.58 2187.47 2387.94 1494.58 1073.54 1293.04 893.24 3176.78 5984.91 4494.44 2270.78 5396.61 2484.53 3394.89 3893.66 53
#test#87.33 2987.13 3187.94 1494.58 1073.54 1292.34 2493.24 3175.23 9184.91 4494.44 2270.78 5396.61 2483.75 4394.89 3893.66 53
testtj87.78 1887.78 1987.77 2294.55 1272.47 3692.23 2793.49 2474.75 10088.33 1794.43 2473.27 3497.02 1084.18 4094.84 4093.82 48
region2R87.42 2687.20 3088.09 994.63 973.55 1093.03 1093.12 3676.73 6284.45 5494.52 1769.09 7196.70 1984.37 3694.83 4194.03 35
原ACMM184.35 10393.01 5068.79 10192.44 6463.96 25981.09 10091.57 8166.06 9795.45 6167.19 18494.82 4288.81 220
HPM-MVScopyleft87.11 3386.98 3387.50 3693.88 3272.16 4392.19 2893.33 3076.07 7783.81 6693.95 4069.77 6596.01 4485.15 2594.66 4394.32 25
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
DPM-MVS84.93 6484.29 6886.84 4890.20 9473.04 2187.12 15193.04 3769.80 18082.85 7791.22 8973.06 3696.02 4376.72 10394.63 4491.46 128
TSAR-MVS + MP.88.02 1688.11 1587.72 2693.68 3772.13 4491.41 4092.35 6974.62 10388.90 1393.85 4175.75 1396.00 4587.80 994.63 4495.04 3
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
PGM-MVS86.68 3986.27 4387.90 1894.22 2573.38 1690.22 6593.04 3775.53 8583.86 6494.42 2567.87 8096.64 2282.70 5494.57 4693.66 53
XVS87.18 3286.91 3588.00 1294.42 1673.33 1792.78 1392.99 4379.14 2183.67 6894.17 3267.45 8396.60 2683.06 4994.50 4794.07 33
X-MVStestdata80.37 13377.83 16688.00 1294.42 1673.33 1792.78 1392.99 4379.14 2183.67 6812.47 34467.45 8396.60 2683.06 4994.50 4794.07 33
test1286.80 5092.63 6070.70 7091.79 9382.71 8071.67 4796.16 3994.50 4793.54 64
CP-MVS87.11 3386.92 3487.68 3194.20 2673.86 593.98 192.82 5476.62 6483.68 6794.46 2167.93 7895.95 4784.20 3994.39 5093.23 74
CSCG86.41 4586.19 4587.07 4592.91 5172.48 3590.81 4893.56 2173.95 11583.16 7391.07 9475.94 1195.19 7279.94 7594.38 5193.55 63
MSLP-MVS++85.43 5685.76 5184.45 9991.93 7070.24 7390.71 5092.86 4977.46 4484.22 5992.81 6467.16 8792.94 16780.36 7194.35 5290.16 166
mPP-MVS86.67 4086.32 4287.72 2694.41 1873.55 1092.74 1592.22 7276.87 5682.81 7994.25 3066.44 9296.24 3482.88 5394.28 5393.38 68
SD-MVS88.06 1388.50 1286.71 5292.60 6372.71 2791.81 3493.19 3477.87 3390.32 994.00 3874.83 2093.78 13087.63 1194.27 5493.65 58
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
MSP-MVS89.51 289.91 388.30 694.28 2273.46 1592.90 1294.11 780.27 1291.35 794.16 3378.35 696.77 1689.59 194.22 5594.67 13
DELS-MVS85.41 5785.30 5685.77 6788.49 14967.93 12485.52 19993.44 2678.70 2883.63 7089.03 14074.57 2195.71 5480.26 7394.04 5693.66 53
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
EPNet83.72 7282.92 7986.14 6384.22 23069.48 8991.05 4685.27 23681.30 776.83 15991.65 7766.09 9695.56 5776.00 10893.85 5793.38 68
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
3Dnovator+77.84 485.48 5484.47 6788.51 391.08 7973.49 1493.18 793.78 1780.79 1076.66 16493.37 4960.40 17196.75 1877.20 9693.73 5895.29 2
CANet86.45 4286.10 4787.51 3590.09 9670.94 6489.70 7892.59 6181.78 481.32 9591.43 8670.34 5897.23 684.26 3793.36 5994.37 22
新几何183.42 13193.13 4670.71 6985.48 23457.43 30881.80 9091.98 7163.28 11892.27 18664.60 20692.99 6087.27 252
112180.84 11679.77 12284.05 11493.11 4870.78 6884.66 21285.42 23557.37 30981.76 9392.02 7063.41 11694.12 11367.28 18192.93 6187.26 253
HPM-MVS_fast85.35 5884.95 6286.57 5693.69 3670.58 7192.15 3091.62 9873.89 11882.67 8194.09 3662.60 13095.54 5880.93 6592.93 6193.57 62
SR-MVS86.73 3786.67 3886.91 4794.11 3072.11 4592.37 2392.56 6274.50 10486.84 2894.65 1567.31 8595.77 5284.80 3192.85 6392.84 89
旧先验191.96 6965.79 15886.37 22693.08 5869.31 7092.74 6488.74 223
3Dnovator76.31 583.38 7982.31 8786.59 5587.94 16672.94 2690.64 5192.14 7677.21 4775.47 18792.83 6258.56 17894.72 9473.24 13292.71 6592.13 111
CS-MVS84.76 6784.61 6685.22 7789.66 10466.43 14690.23 6393.56 2176.52 6682.59 8285.93 22070.41 5795.80 5079.93 7692.68 6693.42 67
MVS_111021_HR85.14 6184.75 6486.32 6091.65 7372.70 2885.98 18490.33 13676.11 7682.08 8591.61 8071.36 5094.17 11281.02 6492.58 6792.08 112
APD-MVS_3200maxsize85.97 4885.88 4986.22 6192.69 5969.53 8891.93 3292.99 4373.54 12585.94 3194.51 2065.80 10195.61 5583.04 5192.51 6893.53 65
MAR-MVS81.84 9980.70 10685.27 7491.32 7771.53 5589.82 7290.92 11869.77 18178.50 12586.21 21662.36 13694.52 9865.36 19892.05 6989.77 190
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
TSAR-MVS + GP.85.71 5285.33 5486.84 4891.34 7672.50 3489.07 9287.28 21576.41 6785.80 3490.22 11174.15 3095.37 6881.82 5991.88 7092.65 95
IS-MVSNet83.15 8182.81 8084.18 10989.94 10063.30 20891.59 3588.46 19279.04 2579.49 11292.16 6865.10 10694.28 10367.71 17691.86 7194.95 5
Vis-MVSNet (Re-imp)78.36 17578.45 15078.07 25388.64 14551.78 31786.70 16679.63 30074.14 11375.11 20290.83 10161.29 15489.75 24358.10 26091.60 7292.69 93
MG-MVS83.41 7783.45 7183.28 13692.74 5862.28 22488.17 12689.50 15875.22 9281.49 9492.74 6566.75 8895.11 7572.85 13591.58 7392.45 99
CPTT-MVS83.73 7183.33 7384.92 8793.28 4370.86 6792.09 3190.38 13268.75 20679.57 11192.83 6260.60 16793.04 16580.92 6691.56 7490.86 142
test22291.50 7568.26 11884.16 22783.20 26554.63 32079.74 10991.63 7958.97 17691.42 7586.77 264
ETV-MVS84.90 6684.67 6585.59 6989.39 11468.66 11188.74 10492.64 6079.97 1784.10 6185.71 22669.32 6995.38 6580.82 6791.37 7692.72 90
testdata79.97 21990.90 8364.21 18884.71 24059.27 29685.40 3692.91 5962.02 14389.08 25568.95 16991.37 7686.63 268
abl_685.23 5984.95 6286.07 6492.23 6670.48 7290.80 4992.08 7773.51 12685.26 3894.16 3362.75 12995.92 4882.46 5791.30 7891.81 119
API-MVS81.99 9781.23 10084.26 10790.94 8270.18 7991.10 4589.32 16271.51 15378.66 12388.28 15965.26 10495.10 7864.74 20591.23 7987.51 246
Vis-MVSNetpermissive83.46 7682.80 8185.43 7190.25 9368.74 10590.30 6290.13 14276.33 7380.87 10392.89 6061.00 16094.20 10972.45 13990.97 8093.35 70
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
OpenMVScopyleft72.83 1079.77 14378.33 15584.09 11285.17 21569.91 8090.57 5390.97 11766.70 22372.17 23391.91 7254.70 20693.96 11761.81 22890.95 8188.41 231
UA-Net85.08 6384.96 6185.45 7092.07 6868.07 12289.78 7590.86 12182.48 284.60 5393.20 5269.35 6895.22 7171.39 14690.88 8293.07 81
ACMMPcopyleft85.89 5085.39 5387.38 3993.59 3972.63 3192.74 1593.18 3576.78 5980.73 10493.82 4264.33 11096.29 3282.67 5590.69 8393.23 74
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
Regformer-186.41 4586.33 4186.64 5389.33 11670.93 6588.43 11191.39 10782.14 386.65 2990.09 11374.39 2595.01 8183.97 4290.63 8493.97 39
Regformer-286.63 4186.53 4086.95 4689.33 11671.24 5988.43 11192.05 7882.50 186.88 2790.09 11374.45 2295.61 5584.38 3590.63 8494.01 37
casdiffmvs85.11 6285.14 5885.01 8287.20 18965.77 15987.75 13692.83 5177.84 3484.36 5892.38 6672.15 4393.93 12381.27 6390.48 8695.33 1
UGNet80.83 11879.59 12784.54 9688.04 16368.09 12189.42 8188.16 19476.95 5376.22 17489.46 13049.30 26393.94 12068.48 17190.31 8791.60 121
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
baseline84.93 6484.98 6084.80 9187.30 18765.39 16687.30 14792.88 4877.62 3684.04 6392.26 6771.81 4593.96 11781.31 6290.30 8895.03 4
MVSFormer82.85 8682.05 9085.24 7587.35 18270.21 7490.50 5590.38 13268.55 20981.32 9589.47 12861.68 14593.46 14578.98 7990.26 8992.05 113
lupinMVS81.39 10880.27 11684.76 9287.35 18270.21 7485.55 19586.41 22462.85 26781.32 9588.61 14961.68 14592.24 18978.41 8590.26 8991.83 117
DP-MVS Recon83.11 8382.09 8986.15 6294.44 1570.92 6688.79 10092.20 7370.53 16879.17 11591.03 9764.12 11296.03 4268.39 17390.14 9191.50 125
EIA-MVS83.31 8082.80 8184.82 8989.59 10665.59 16188.21 12492.68 5674.66 10278.96 11786.42 21269.06 7295.26 7075.54 11390.09 9293.62 60
MVS_111021_LR82.61 8982.11 8884.11 11088.82 13871.58 5485.15 20286.16 22974.69 10180.47 10691.04 9562.29 13790.55 23380.33 7290.08 9390.20 165
jason81.39 10880.29 11584.70 9386.63 19969.90 8185.95 18586.77 22063.24 26181.07 10189.47 12861.08 15992.15 19178.33 8690.07 9492.05 113
jason: jason.
LFMVS81.82 10081.23 10083.57 12891.89 7163.43 20689.84 7181.85 27977.04 5283.21 7193.10 5452.26 22593.43 14771.98 14189.95 9593.85 45
MVS78.19 18076.99 18581.78 18185.66 20866.99 13884.66 21290.47 13055.08 31972.02 23585.27 23663.83 11494.11 11566.10 19289.80 9684.24 296
CANet_DTU80.61 12679.87 12082.83 15985.60 21063.17 21387.36 14588.65 18876.37 7175.88 18188.44 15553.51 21693.07 16273.30 13089.74 9792.25 106
PVSNet_Blended80.98 11380.34 11382.90 15688.85 13565.40 16484.43 22292.00 8267.62 21578.11 13585.05 24366.02 9894.27 10471.52 14389.50 9889.01 210
PAPM_NR83.02 8482.41 8484.82 8992.47 6466.37 14887.93 13391.80 9273.82 11977.32 15090.66 10367.90 7994.90 8670.37 15489.48 9993.19 78
114514_t80.68 12579.51 12884.20 10894.09 3167.27 13589.64 7991.11 11558.75 30174.08 21590.72 10258.10 18095.04 8069.70 16189.42 10090.30 162
LCM-MVSNet-Re77.05 20276.94 18677.36 26387.20 18951.60 31880.06 27380.46 29275.20 9367.69 27586.72 19662.48 13388.98 25763.44 21189.25 10191.51 124
alignmvs85.48 5485.32 5585.96 6689.51 11069.47 9089.74 7692.47 6376.17 7587.73 2391.46 8570.32 5993.78 13081.51 6088.95 10294.63 15
VNet82.21 9282.41 8481.62 18490.82 8560.93 23884.47 21889.78 15076.36 7284.07 6291.88 7464.71 10990.26 23570.68 15188.89 10393.66 53
PS-MVSNAJ81.69 10181.02 10483.70 12589.51 11068.21 12084.28 22690.09 14370.79 16281.26 9985.62 23063.15 12394.29 10275.62 11188.87 10488.59 226
canonicalmvs85.91 4985.87 5086.04 6589.84 10269.44 9390.45 5993.00 4176.70 6388.01 2191.23 8873.28 3393.91 12481.50 6188.80 10594.77 11
QAPM80.88 11479.50 12985.03 8188.01 16568.97 9991.59 3592.00 8266.63 22775.15 20192.16 6857.70 18395.45 6163.52 20988.76 10690.66 148
VDD-MVS83.01 8582.36 8684.96 8491.02 8166.40 14788.91 9588.11 19577.57 3884.39 5793.29 5152.19 22693.91 12477.05 9888.70 10794.57 18
PVSNet_Blended_VisFu82.62 8881.83 9584.96 8490.80 8669.76 8388.74 10491.70 9769.39 18878.96 11788.46 15465.47 10394.87 8974.42 11788.57 10890.24 164
DI_MVS_plusplus_test79.89 14278.58 14783.85 12482.89 26165.32 16886.12 18189.55 15669.64 18570.55 24685.82 22557.24 19193.81 12876.85 10088.55 10992.41 101
xiu_mvs_v2_base81.69 10181.05 10383.60 12689.15 12768.03 12384.46 22090.02 14470.67 16581.30 9886.53 21063.17 12294.19 11075.60 11288.54 11088.57 227
PAPR81.66 10380.89 10583.99 11990.27 9264.00 19186.76 16591.77 9668.84 20577.13 15789.50 12667.63 8194.88 8867.55 17888.52 11193.09 80
MVS_Test83.15 8183.06 7683.41 13386.86 19363.21 21086.11 18292.00 8274.31 10882.87 7689.44 13370.03 6193.21 15277.39 9588.50 11293.81 49
AdaColmapbinary80.58 12979.42 13084.06 11393.09 4968.91 10089.36 8288.97 17969.27 19175.70 18489.69 12057.20 19295.77 5263.06 21588.41 11387.50 247
VDDNet81.52 10580.67 10784.05 11490.44 9064.13 19089.73 7785.91 23271.11 15783.18 7293.48 4650.54 24993.49 14473.40 12988.25 11494.54 19
PCF-MVS73.52 780.38 13278.84 14385.01 8287.71 17468.99 9883.65 23691.46 10663.00 26477.77 14290.28 10866.10 9595.09 7961.40 23188.22 11590.94 140
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
Effi-MVS+83.62 7483.08 7585.24 7588.38 15467.45 13088.89 9689.15 17075.50 8682.27 8388.28 15969.61 6694.45 10077.81 9087.84 11693.84 47
gg-mvs-nofinetune69.95 27467.96 27675.94 27583.07 25354.51 30777.23 29870.29 32963.11 26270.32 25062.33 33143.62 29488.69 26353.88 28087.76 11784.62 294
Regformer-385.23 5985.07 5985.70 6888.95 13369.01 9788.29 12189.91 14880.95 885.01 4190.01 11572.45 4094.19 11082.50 5687.57 11893.90 43
Regformer-485.68 5385.45 5286.35 5788.95 13369.67 8588.29 12191.29 10981.73 585.36 3790.01 11572.62 3995.35 6983.28 4787.57 11894.03 35
xiu_mvs_v1_base_debu80.80 12179.72 12484.03 11687.35 18270.19 7685.56 19288.77 18469.06 19881.83 8788.16 16250.91 24392.85 16978.29 8787.56 12089.06 205
xiu_mvs_v1_base80.80 12179.72 12484.03 11687.35 18270.19 7685.56 19288.77 18469.06 19881.83 8788.16 16250.91 24392.85 16978.29 8787.56 12089.06 205
xiu_mvs_v1_base_debi80.80 12179.72 12484.03 11687.35 18270.19 7685.56 19288.77 18469.06 19881.83 8788.16 16250.91 24392.85 16978.29 8787.56 12089.06 205
CLD-MVS82.31 9181.65 9684.29 10688.47 15067.73 12885.81 19092.35 6975.78 7978.33 13086.58 20764.01 11394.35 10176.05 10787.48 12390.79 143
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
CDS-MVSNet79.07 16077.70 17283.17 14387.60 17768.23 11984.40 22486.20 22867.49 21776.36 17186.54 20961.54 14890.79 22961.86 22787.33 12490.49 156
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
diffmvs82.10 9381.88 9482.76 16783.00 25663.78 19683.68 23589.76 15172.94 13482.02 8689.85 11865.96 10090.79 22982.38 5887.30 12593.71 52
EPP-MVSNet83.40 7883.02 7784.57 9590.13 9564.47 18492.32 2590.73 12374.45 10779.35 11491.10 9269.05 7395.12 7472.78 13687.22 12694.13 30
TAMVS78.89 16577.51 17683.03 15087.80 17067.79 12784.72 21185.05 23967.63 21476.75 16287.70 17062.25 13890.82 22858.53 25687.13 12790.49 156
TAPA-MVS73.13 979.15 15777.94 16282.79 16489.59 10662.99 21788.16 12791.51 10265.77 23677.14 15691.09 9360.91 16193.21 15250.26 29587.05 12892.17 110
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
PAPM77.68 19476.40 19981.51 18787.29 18861.85 22983.78 23489.59 15564.74 24871.23 24288.70 14562.59 13193.66 13752.66 28587.03 12989.01 210
test_yl81.17 11080.47 11183.24 13989.13 12863.62 19786.21 17889.95 14672.43 13981.78 9189.61 12357.50 18693.58 13870.75 14986.90 13092.52 96
DCV-MVSNet81.17 11080.47 11183.24 13989.13 12863.62 19786.21 17889.95 14672.43 13981.78 9189.61 12357.50 18693.58 13870.75 14986.90 13092.52 96
BH-untuned79.47 14978.60 14682.05 17689.19 12665.91 15586.07 18388.52 19172.18 14175.42 19187.69 17161.15 15793.54 14260.38 23886.83 13286.70 266
BH-RMVSNet79.61 14578.44 15183.14 14489.38 11565.93 15484.95 20787.15 21673.56 12478.19 13389.79 11956.67 19593.36 14859.53 24586.74 13390.13 168
LS3D76.95 20574.82 21683.37 13490.45 8967.36 13489.15 9086.94 21861.87 27769.52 26390.61 10451.71 23794.53 9746.38 31586.71 13488.21 233
Fast-Effi-MVS+80.81 11979.92 11983.47 12988.85 13564.51 18185.53 19789.39 16070.79 16278.49 12685.06 24267.54 8293.58 13867.03 18786.58 13592.32 103
EPNet_dtu75.46 22674.86 21577.23 26782.57 26954.60 30586.89 15883.09 26671.64 14866.25 29185.86 22355.99 19788.04 27154.92 27686.55 13689.05 208
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
OPM-MVS83.50 7582.95 7885.14 7888.79 14170.95 6389.13 9191.52 10177.55 4180.96 10291.75 7560.71 16394.50 9979.67 7786.51 13789.97 182
OMC-MVS82.69 8781.97 9384.85 8888.75 14367.42 13187.98 12990.87 12074.92 9779.72 11091.65 7762.19 14093.96 11775.26 11486.42 13893.16 79
HQP_MVS83.64 7383.14 7485.14 7890.08 9768.71 10791.25 4292.44 6479.12 2378.92 11991.00 9860.42 16995.38 6578.71 8186.32 13991.33 129
plane_prior592.44 6495.38 6578.71 8186.32 13991.33 129
thisisatest051577.33 20075.38 21083.18 14285.27 21463.80 19582.11 25583.27 26265.06 24475.91 18083.84 25649.54 25994.27 10467.24 18386.19 14191.48 127
plane_prior68.71 10790.38 6077.62 3686.16 142
mvs_anonymous79.42 15179.11 13880.34 21384.45 22757.97 26882.59 25087.62 20867.40 21976.17 17888.56 15268.47 7589.59 24670.65 15286.05 14393.47 66
HQP3-MVS92.19 7485.99 144
HQP-MVS82.61 8982.02 9184.37 10189.33 11666.98 13989.17 8692.19 7476.41 6777.23 15390.23 11060.17 17295.11 7577.47 9385.99 14491.03 136
BH-w/o78.21 17877.33 17980.84 20488.81 13965.13 17384.87 20887.85 20569.75 18274.52 21184.74 24661.34 15293.11 16058.24 25985.84 14684.27 295
CHOSEN 1792x268877.63 19575.69 20383.44 13089.98 9968.58 11378.70 28887.50 21156.38 31475.80 18386.84 19258.67 17791.40 21361.58 23085.75 14790.34 161
Anonymous20240521178.25 17677.01 18381.99 17891.03 8060.67 24284.77 21083.90 25170.65 16780.00 10891.20 9041.08 30891.43 21265.21 19985.26 14893.85 45
cascas76.72 20874.64 21782.99 15285.78 20765.88 15682.33 25389.21 16860.85 28372.74 22581.02 28647.28 27393.75 13467.48 17985.02 14989.34 200
FIs82.07 9582.42 8381.04 20188.80 14058.34 26288.26 12393.49 2476.93 5478.47 12791.04 9569.92 6392.34 18569.87 16084.97 15092.44 100
test-LLR72.94 25272.43 24174.48 28881.35 28858.04 26678.38 28977.46 31066.66 22469.95 25879.00 30348.06 26979.24 31366.13 19084.83 15186.15 274
test-mter71.41 26170.39 26074.48 28881.35 28858.04 26678.38 28977.46 31060.32 28669.95 25879.00 30336.08 32579.24 31366.13 19084.83 15186.15 274
EI-MVSNet-Vis-set84.19 6883.81 6985.31 7288.18 15867.85 12587.66 13889.73 15380.05 1682.95 7489.59 12570.74 5594.82 9080.66 7084.72 15393.28 73
thisisatest053079.40 15277.76 17084.31 10587.69 17665.10 17487.36 14584.26 24770.04 17577.42 14788.26 16149.94 25594.79 9270.20 15584.70 15493.03 83
GG-mvs-BLEND75.38 28281.59 28355.80 29979.32 28069.63 33167.19 28073.67 32343.24 29588.90 26250.41 29284.50 15581.45 317
FC-MVSNet-test81.52 10582.02 9180.03 21888.42 15355.97 29887.95 13193.42 2877.10 5077.38 14890.98 10069.96 6291.79 20268.46 17284.50 15592.33 102
PVSNet64.34 1872.08 25870.87 25775.69 27786.21 20356.44 29174.37 31380.73 28762.06 27670.17 25382.23 27742.86 29883.31 30154.77 27784.45 15787.32 251
MS-PatchMatch73.83 24172.67 23977.30 26583.87 23766.02 15281.82 25684.66 24161.37 28168.61 27082.82 26947.29 27288.21 26859.27 24684.32 15877.68 327
ET-MVSNet_ETH3D78.63 16976.63 19684.64 9486.73 19869.47 9085.01 20584.61 24269.54 18666.51 28986.59 20550.16 25291.75 20376.26 10584.24 15992.69 93
TESTMET0.1,169.89 27569.00 26672.55 29779.27 31356.85 28378.38 28974.71 32257.64 30668.09 27277.19 31437.75 32076.70 32463.92 20884.09 16084.10 299
EI-MVSNet-UG-set83.81 7083.38 7285.09 8087.87 16767.53 12987.44 14489.66 15479.74 1882.23 8489.41 13470.24 6094.74 9379.95 7483.92 16192.99 86
LPG-MVS_test82.08 9481.27 9984.50 9789.23 12468.76 10390.22 6591.94 8675.37 8976.64 16591.51 8254.29 20994.91 8478.44 8383.78 16289.83 187
LGP-MVS_train84.50 9789.23 12468.76 10391.94 8675.37 8976.64 16591.51 8254.29 20994.91 8478.44 8383.78 16289.83 187
thres100view90076.50 21075.55 20679.33 23289.52 10956.99 28285.83 18983.23 26373.94 11676.32 17287.12 18851.89 23491.95 19748.33 30383.75 16489.07 203
tfpn200view976.42 21375.37 21179.55 23189.13 12857.65 27485.17 20083.60 25473.41 12776.45 16786.39 21352.12 22791.95 19748.33 30383.75 16489.07 203
thres40076.50 21075.37 21179.86 22189.13 12857.65 27485.17 20083.60 25473.41 12776.45 16786.39 21352.12 22791.95 19748.33 30383.75 16490.00 178
thres600view776.50 21075.44 20779.68 22589.40 11357.16 27985.53 19783.23 26373.79 12076.26 17387.09 18951.89 23491.89 20048.05 30883.72 16790.00 178
thres20075.55 22574.47 22178.82 24187.78 17357.85 27183.07 24783.51 25772.44 13875.84 18284.42 24852.08 22991.75 20347.41 31083.64 16886.86 262
XVG-OURS80.41 13179.23 13683.97 12085.64 20969.02 9683.03 24890.39 13171.09 15877.63 14491.49 8454.62 20891.35 21475.71 10983.47 16991.54 123
CNLPA78.08 18276.79 19081.97 17990.40 9171.07 6187.59 14084.55 24366.03 23472.38 23189.64 12257.56 18586.04 28659.61 24483.35 17088.79 221
MVP-Stereo76.12 21774.46 22281.13 19985.37 21369.79 8284.42 22387.95 20165.03 24567.46 27785.33 23553.28 21891.73 20558.01 26183.27 17181.85 315
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
131476.53 20975.30 21380.21 21683.93 23662.32 22384.66 21288.81 18260.23 28770.16 25484.07 25355.30 20090.73 23167.37 18083.21 17287.59 245
tttt051779.40 15277.91 16383.90 12388.10 16163.84 19488.37 11884.05 24971.45 15476.78 16189.12 13749.93 25794.89 8770.18 15683.18 17392.96 87
mvs-test180.88 11479.40 13185.29 7385.13 21869.75 8489.28 8388.10 19674.99 9576.44 17086.72 19657.27 18994.26 10873.53 12583.18 17391.87 116
HyFIR lowres test77.53 19675.40 20983.94 12289.59 10666.62 14380.36 27088.64 18956.29 31576.45 16785.17 23957.64 18493.28 15061.34 23383.10 17591.91 115
ACMP74.13 681.51 10780.57 10884.36 10289.42 11268.69 11089.97 7091.50 10574.46 10675.04 20590.41 10753.82 21494.54 9677.56 9282.91 17689.86 186
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
ACMM73.20 880.78 12479.84 12183.58 12789.31 12168.37 11589.99 6991.60 9970.28 17277.25 15189.66 12153.37 21793.53 14374.24 12082.85 17788.85 218
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
PMMVS69.34 27768.67 26871.35 30375.67 32562.03 22675.17 30773.46 32450.00 32868.68 26879.05 30152.07 23078.13 31861.16 23482.77 17873.90 330
PLCcopyleft70.83 1178.05 18476.37 20083.08 14791.88 7267.80 12688.19 12589.46 15964.33 25469.87 26088.38 15653.66 21593.58 13858.86 25282.73 17987.86 239
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
TR-MVS77.44 19776.18 20181.20 19688.24 15763.24 20984.61 21686.40 22567.55 21677.81 14086.48 21154.10 21193.15 15757.75 26382.72 18087.20 254
Anonymous2024052980.19 13778.89 14284.10 11190.60 8764.75 17888.95 9490.90 11965.97 23580.59 10591.17 9149.97 25493.73 13669.16 16782.70 18193.81 49
ab-mvs79.51 14778.97 14181.14 19888.46 15160.91 23983.84 23389.24 16770.36 17079.03 11688.87 14363.23 12190.21 23765.12 20082.57 18292.28 105
HY-MVS69.67 1277.95 18777.15 18180.36 21287.57 18160.21 24983.37 24387.78 20666.11 23175.37 19387.06 19163.27 11990.48 23461.38 23282.43 18390.40 160
PS-MVSNAJss82.07 9581.31 9884.34 10486.51 20067.27 13589.27 8491.51 10271.75 14779.37 11390.22 11163.15 12394.27 10477.69 9182.36 18491.49 126
UniMVSNet_ETH3D79.10 15978.24 15781.70 18386.85 19460.24 24887.28 14888.79 18374.25 11076.84 15890.53 10649.48 26091.56 20867.98 17482.15 18593.29 72
PVSNet_BlendedMVS80.60 12780.02 11782.36 17388.85 13565.40 16486.16 18092.00 8269.34 19078.11 13586.09 21966.02 9894.27 10471.52 14382.06 18687.39 248
WTY-MVS75.65 22475.68 20475.57 27986.40 20156.82 28477.92 29582.40 27265.10 24376.18 17687.72 16963.13 12680.90 30960.31 23981.96 18789.00 212
ACMMP++_ref81.95 188
DP-MVS76.78 20774.57 21883.42 13193.29 4269.46 9288.55 11083.70 25363.98 25870.20 25188.89 14254.01 21394.80 9146.66 31281.88 18986.01 278
CMPMVSbinary51.72 2170.19 27268.16 27376.28 27373.15 33357.55 27679.47 27983.92 25048.02 32956.48 32784.81 24443.13 29686.42 28462.67 21981.81 19084.89 289
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
XVG-OURS-SEG-HR80.81 11979.76 12383.96 12185.60 21068.78 10283.54 24190.50 12970.66 16676.71 16391.66 7660.69 16491.26 21676.94 9981.58 19191.83 117
MIMVSNet70.69 26669.30 26374.88 28584.52 22556.35 29475.87 30579.42 30164.59 24967.76 27382.41 27341.10 30781.54 30846.64 31481.34 19286.75 265
ACMMP++81.25 193
D2MVS74.82 23173.21 23479.64 22879.81 30562.56 22080.34 27187.35 21464.37 25368.86 26782.66 27146.37 27890.10 23967.91 17581.24 19486.25 271
GA-MVS76.87 20675.17 21481.97 17982.75 26462.58 21981.44 26486.35 22772.16 14374.74 20982.89 26746.20 28192.02 19568.85 17081.09 19591.30 131
sss73.60 24373.64 23073.51 29482.80 26355.01 30476.12 30181.69 28062.47 27274.68 21085.85 22457.32 18878.11 31960.86 23680.93 19687.39 248
Effi-MVS+-dtu80.03 13978.57 14884.42 10085.13 21868.74 10588.77 10188.10 19674.99 9574.97 20683.49 26257.27 18993.36 14873.53 12580.88 19791.18 133
EG-PatchMatch MVS74.04 23971.82 24780.71 20784.92 22167.42 13185.86 18888.08 19866.04 23364.22 30383.85 25535.10 32792.56 17757.44 26580.83 19882.16 314
jajsoiax79.29 15577.96 16183.27 13784.68 22466.57 14589.25 8590.16 14169.20 19575.46 18989.49 12745.75 28693.13 15976.84 10180.80 19990.11 170
1112_ss77.40 19976.43 19880.32 21489.11 13260.41 24783.65 23687.72 20762.13 27573.05 22386.72 19662.58 13289.97 24062.11 22580.80 19990.59 153
mvs_tets79.13 15877.77 16983.22 14184.70 22366.37 14889.17 8690.19 14069.38 18975.40 19289.46 13044.17 29293.15 15776.78 10280.70 20190.14 167
PatchMatch-RL72.38 25670.90 25576.80 27188.60 14667.38 13379.53 27876.17 31662.75 26969.36 26582.00 28045.51 28784.89 29353.62 28180.58 20278.12 326
EI-MVSNet80.52 13079.98 11882.12 17484.28 22863.19 21286.41 17288.95 18074.18 11278.69 12187.54 17666.62 8992.43 18072.57 13880.57 20390.74 146
MVSTER79.01 16177.88 16582.38 17283.07 25364.80 17784.08 23288.95 18069.01 20178.69 12187.17 18754.70 20692.43 18074.69 11680.57 20389.89 185
testing_275.73 22273.34 23382.89 15877.37 31965.22 17084.10 23090.54 12869.09 19760.46 31581.15 28440.48 31092.84 17276.36 10480.54 20590.60 151
XVG-ACMP-BASELINE76.11 21874.27 22481.62 18483.20 24964.67 17983.60 23989.75 15269.75 18271.85 23687.09 18932.78 32992.11 19269.99 15980.43 20688.09 235
Fast-Effi-MVS+-dtu78.02 18576.49 19782.62 16983.16 25266.96 14186.94 15687.45 21372.45 13671.49 24184.17 25154.79 20591.58 20767.61 17780.31 20789.30 201
LTVRE_ROB69.57 1376.25 21674.54 22081.41 18988.60 14664.38 18679.24 28189.12 17370.76 16469.79 26287.86 16849.09 26593.20 15456.21 27380.16 20886.65 267
Andreas Kuhn, Heiko Hirschmüller, Daniel Scharstein, Helmut Mayer: A TV Prior for High-Quality Scalable Multi-View Stereo Reconstruction. International Journal of Computer Vision 2016
Test_1112_low_res76.40 21475.44 20779.27 23389.28 12258.09 26481.69 25987.07 21759.53 29472.48 22986.67 20261.30 15389.33 25060.81 23780.15 20990.41 159
test_djsdf80.30 13479.32 13483.27 13783.98 23565.37 16790.50 5590.38 13268.55 20976.19 17588.70 14556.44 19693.46 14578.98 7980.14 21090.97 139
CHOSEN 280x42066.51 29364.71 29271.90 29881.45 28563.52 20257.98 33868.95 33553.57 32162.59 31176.70 31546.22 28075.29 33155.25 27579.68 21176.88 329
MVS_030472.48 25470.89 25677.24 26682.20 27559.68 25184.11 22983.49 25867.10 22066.87 28480.59 29035.00 32887.40 27659.07 25079.58 21284.63 293
baseline275.70 22373.83 22981.30 19383.26 24761.79 23182.57 25180.65 28866.81 22166.88 28383.42 26357.86 18292.19 19063.47 21079.57 21389.91 183
GBi-Net78.40 17377.40 17781.40 19087.60 17763.01 21488.39 11589.28 16371.63 14975.34 19487.28 18054.80 20291.11 21962.72 21679.57 21390.09 172
test178.40 17377.40 17781.40 19087.60 17763.01 21488.39 11589.28 16371.63 14975.34 19487.28 18054.80 20291.11 21962.72 21679.57 21390.09 172
FMVSNet377.88 18976.85 18880.97 20286.84 19562.36 22186.52 17188.77 18471.13 15675.34 19486.66 20354.07 21291.10 22262.72 21679.57 21389.45 198
FMVSNet278.20 17977.21 18081.20 19687.60 17762.89 21887.47 14389.02 17571.63 14975.29 19887.28 18054.80 20291.10 22262.38 22079.38 21789.61 194
anonymousdsp78.60 17077.15 18182.98 15380.51 29867.08 13787.24 14989.53 15765.66 23875.16 20087.19 18652.52 21992.25 18777.17 9779.34 21889.61 194
nrg03083.88 6983.53 7084.96 8486.77 19769.28 9490.46 5892.67 5774.79 9882.95 7491.33 8772.70 3893.09 16180.79 6979.28 21992.50 98
VPA-MVSNet80.60 12780.55 10980.76 20688.07 16260.80 24186.86 15991.58 10075.67 8480.24 10789.45 13263.34 11790.25 23670.51 15379.22 22091.23 132
F-COLMAP76.38 21574.33 22382.50 17089.28 12266.95 14288.41 11489.03 17464.05 25666.83 28588.61 14946.78 27692.89 16857.48 26478.55 22187.67 242
FMVSNet177.44 19776.12 20281.40 19086.81 19663.01 21488.39 11589.28 16370.49 16974.39 21287.28 18049.06 26691.11 21960.91 23578.52 22290.09 172
MDTV_nov1_ep1369.97 26283.18 25053.48 31277.10 29980.18 29760.45 28469.33 26680.44 29148.89 26786.90 27951.60 28878.51 223
CVMVSNet72.99 25172.58 24074.25 29184.28 22850.85 32386.41 17283.45 26044.56 33073.23 22187.54 17649.38 26185.70 28865.90 19478.44 22486.19 273
tpm273.26 24771.46 24978.63 24383.34 24556.71 28780.65 26880.40 29356.63 31373.55 21782.02 27951.80 23691.24 21756.35 27278.42 22587.95 236
CostFormer75.24 23073.90 22779.27 23382.65 26858.27 26380.80 26582.73 27061.57 27875.33 19783.13 26555.52 19891.07 22564.98 20378.34 22688.45 229
ACMH67.68 1675.89 22073.93 22681.77 18288.71 14466.61 14488.62 10789.01 17669.81 17966.78 28686.70 20141.95 30591.51 21155.64 27478.14 22787.17 255
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
CR-MVSNet73.37 24471.27 25279.67 22681.32 29065.19 17175.92 30380.30 29459.92 29072.73 22681.19 28252.50 22086.69 28059.84 24277.71 22887.11 258
RPMNet71.62 25968.94 26779.67 22681.32 29065.19 17175.92 30378.30 30657.60 30772.73 22676.45 31752.30 22486.69 28048.14 30777.71 22887.11 258
SCA74.22 23772.33 24379.91 22084.05 23462.17 22579.96 27579.29 30266.30 23072.38 23180.13 29451.95 23288.60 26459.25 24777.67 23088.96 214
Anonymous2023121178.97 16377.69 17382.81 16190.54 8864.29 18790.11 6791.51 10265.01 24676.16 17988.13 16650.56 24893.03 16669.68 16277.56 23191.11 135
DWT-MVSNet_test73.70 24271.86 24679.21 23582.91 26058.94 25782.34 25282.17 27465.21 24171.05 24578.31 30544.21 29190.17 23863.29 21477.28 23288.53 228
v114480.03 13979.03 13983.01 15183.78 23864.51 18187.11 15290.57 12771.96 14578.08 13786.20 21761.41 15093.94 12074.93 11577.23 23390.60 151
WR-MVS79.49 14879.22 13780.27 21588.79 14158.35 26185.06 20488.61 19078.56 2977.65 14388.34 15763.81 11590.66 23264.98 20377.22 23491.80 120
v119279.59 14678.43 15283.07 14883.55 24264.52 18086.93 15790.58 12670.83 16077.78 14185.90 22159.15 17593.94 12073.96 12277.19 23590.76 144
VPNet78.69 16878.66 14578.76 24288.31 15655.72 30084.45 22186.63 22276.79 5878.26 13190.55 10559.30 17489.70 24566.63 18877.05 23690.88 141
v124078.99 16277.78 16882.64 16883.21 24863.54 20186.62 16890.30 13869.74 18477.33 14985.68 22757.04 19393.76 13373.13 13376.92 23790.62 149
MSDG73.36 24670.99 25480.49 21084.51 22665.80 15780.71 26786.13 23065.70 23765.46 29483.74 25944.60 28990.91 22751.13 29076.89 23884.74 291
IterMVS-LS80.06 13879.38 13282.11 17585.89 20563.20 21186.79 16289.34 16174.19 11175.45 19086.72 19666.62 8992.39 18272.58 13776.86 23990.75 145
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
v192192079.22 15678.03 16082.80 16283.30 24663.94 19386.80 16190.33 13669.91 17877.48 14685.53 23158.44 17993.75 13473.60 12476.85 24090.71 147
test_normal67.47 28663.56 29679.18 23772.78 33455.71 30140.72 34290.78 12272.12 14448.43 33465.82 32932.32 33092.25 18772.25 14076.85 24089.59 196
XXY-MVS75.41 22875.56 20574.96 28483.59 24157.82 27280.59 26983.87 25266.54 22874.93 20788.31 15863.24 12080.09 31262.16 22376.85 24086.97 260
v2v48280.23 13579.29 13583.05 14983.62 24064.14 18987.04 15389.97 14573.61 12278.18 13487.22 18461.10 15893.82 12776.11 10676.78 24391.18 133
v14419279.47 14978.37 15382.78 16583.35 24463.96 19286.96 15590.36 13569.99 17677.50 14585.67 22860.66 16593.77 13274.27 11976.58 24490.62 149
UniMVSNet (Re)81.60 10481.11 10283.09 14688.38 15464.41 18587.60 13993.02 4078.42 3178.56 12488.16 16269.78 6493.26 15169.58 16376.49 24591.60 121
UniMVSNet_NR-MVSNet81.88 9881.54 9782.92 15588.46 15163.46 20487.13 15092.37 6880.19 1478.38 12889.14 13671.66 4893.05 16370.05 15776.46 24692.25 106
DU-MVS81.12 11280.52 11082.90 15687.80 17063.46 20487.02 15491.87 9079.01 2678.38 12889.07 13865.02 10793.05 16370.05 15776.46 24692.20 108
cl-mvsnet278.07 18377.01 18381.23 19582.37 27461.83 23083.55 24087.98 20068.96 20275.06 20483.87 25461.40 15191.88 20173.53 12576.39 24889.98 181
miper_ehance_all_eth78.59 17177.76 17081.08 20082.66 26761.56 23383.65 23689.15 17068.87 20475.55 18683.79 25866.49 9192.03 19473.25 13176.39 24889.64 193
miper_enhance_ethall77.87 19076.86 18780.92 20381.65 28161.38 23582.68 24988.98 17765.52 24075.47 18782.30 27565.76 10292.00 19672.95 13476.39 24889.39 199
PatchmatchNetpermissive73.12 24971.33 25178.49 24883.18 25060.85 24079.63 27778.57 30464.13 25571.73 23779.81 29951.20 24185.97 28757.40 26676.36 25188.66 224
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
USDC70.33 27068.37 27076.21 27480.60 29656.23 29579.19 28386.49 22360.89 28261.29 31285.47 23331.78 33389.47 24953.37 28276.21 25282.94 311
OpenMVS_ROBcopyleft64.09 1970.56 26868.19 27277.65 25980.26 29959.41 25685.01 20582.96 26858.76 30065.43 29582.33 27437.63 32191.23 21845.34 32076.03 25382.32 312
ACMH+68.96 1476.01 21974.01 22582.03 17788.60 14665.31 16988.86 9787.55 20970.25 17367.75 27487.47 17841.27 30693.19 15558.37 25775.94 25487.60 244
PatchFormer-LS_test74.50 23373.05 23778.86 24082.95 25959.55 25581.65 26082.30 27367.44 21871.62 23978.15 30852.34 22388.92 26165.05 20275.90 25588.12 234
tpm72.37 25771.71 24874.35 29082.19 27652.00 31579.22 28277.29 31264.56 25072.95 22483.68 26151.35 23983.26 30258.33 25875.80 25687.81 240
Anonymous2023120668.60 28067.80 28071.02 30580.23 30050.75 32478.30 29280.47 29156.79 31266.11 29282.63 27246.35 27978.95 31543.62 32375.70 25783.36 304
v7n78.97 16377.58 17583.14 14483.45 24365.51 16288.32 11991.21 11173.69 12172.41 23086.32 21557.93 18193.81 12869.18 16675.65 25890.11 170
NR-MVSNet80.23 13579.38 13282.78 16587.80 17063.34 20786.31 17591.09 11679.01 2672.17 23389.07 13867.20 8692.81 17366.08 19375.65 25892.20 108
v1079.74 14478.67 14482.97 15484.06 23364.95 17587.88 13590.62 12573.11 13075.11 20286.56 20861.46 14994.05 11673.68 12375.55 26089.90 184
IB-MVS68.01 1575.85 22173.36 23283.31 13584.76 22266.03 15183.38 24285.06 23870.21 17469.40 26481.05 28545.76 28594.66 9565.10 20175.49 26189.25 202
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
cl_fuxian78.75 16677.91 16381.26 19482.89 26161.56 23384.09 23189.13 17269.97 17775.56 18584.29 25066.36 9392.09 19373.47 12875.48 26290.12 169
V4279.38 15478.24 15782.83 15981.10 29265.50 16385.55 19589.82 14971.57 15278.21 13286.12 21860.66 16593.18 15675.64 11075.46 26389.81 189
cl-mvsnet_77.72 19276.76 19180.58 20882.49 27160.48 24583.09 24587.87 20369.22 19374.38 21385.22 23862.10 14191.53 20971.09 14775.41 26489.73 192
cl-mvsnet177.72 19276.76 19180.58 20882.48 27260.48 24583.09 24587.86 20469.22 19374.38 21385.24 23762.10 14191.53 20971.09 14775.40 26589.74 191
v879.97 14179.02 14082.80 16284.09 23264.50 18387.96 13090.29 13974.13 11475.24 19986.81 19362.88 12893.89 12674.39 11875.40 26590.00 178
Baseline_NR-MVSNet78.15 18178.33 15577.61 26085.79 20656.21 29686.78 16385.76 23373.60 12377.93 13987.57 17465.02 10788.99 25667.14 18575.33 26787.63 243
pmmvs571.55 26070.20 26175.61 27877.83 31656.39 29281.74 25880.89 28457.76 30567.46 27784.49 24749.26 26485.32 29257.08 26975.29 26885.11 288
EPMVS69.02 27968.16 27371.59 29979.61 30949.80 32877.40 29766.93 33662.82 26870.01 25579.05 30145.79 28477.86 32156.58 27175.26 26987.13 257
TranMVSNet+NR-MVSNet80.84 11680.31 11482.42 17187.85 16862.33 22287.74 13791.33 10880.55 1177.99 13889.86 11765.23 10592.62 17467.05 18675.24 27092.30 104
tfpnnormal74.39 23473.16 23578.08 25286.10 20458.05 26584.65 21587.53 21070.32 17171.22 24385.63 22954.97 20189.86 24143.03 32475.02 27186.32 270
COLMAP_ROBcopyleft66.92 1773.01 25070.41 25980.81 20587.13 19165.63 16088.30 12084.19 24862.96 26563.80 30687.69 17138.04 31992.56 17746.66 31274.91 27284.24 296
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
PatchT68.46 28367.85 27870.29 30780.70 29543.93 33572.47 31674.88 31960.15 28870.55 24676.57 31649.94 25581.59 30750.58 29174.83 27385.34 284
pmmvs474.03 24071.91 24580.39 21181.96 27868.32 11681.45 26382.14 27559.32 29569.87 26085.13 24052.40 22288.13 27060.21 24074.74 27484.73 292
ITE_SJBPF78.22 25081.77 28060.57 24383.30 26169.25 19267.54 27687.20 18536.33 32487.28 27854.34 27874.62 27586.80 263
test0.0.03 168.00 28467.69 28268.90 31277.55 31747.43 33075.70 30672.95 32666.66 22466.56 28782.29 27648.06 26975.87 32844.97 32174.51 27683.41 303
test_040272.79 25370.44 25879.84 22288.13 15965.99 15385.93 18684.29 24565.57 23967.40 27985.49 23246.92 27592.61 17535.88 33374.38 27780.94 318
CP-MVSNet78.22 17778.34 15477.84 25587.83 16954.54 30687.94 13291.17 11377.65 3573.48 21888.49 15362.24 13988.43 26662.19 22274.07 27890.55 154
FMVSNet569.50 27667.96 27674.15 29282.97 25855.35 30380.01 27482.12 27662.56 27163.02 30781.53 28136.92 32281.92 30648.42 30274.06 27985.17 287
MVS-HIRNet59.14 30557.67 30763.57 31981.65 28143.50 33671.73 31865.06 33939.59 33551.43 33257.73 33538.34 31882.58 30539.53 33073.95 28064.62 335
tpmrst72.39 25572.13 24473.18 29680.54 29749.91 32679.91 27679.08 30363.11 26271.69 23879.95 29655.32 19982.77 30465.66 19773.89 28186.87 261
PS-CasMVS78.01 18678.09 15977.77 25787.71 17454.39 30888.02 12891.22 11077.50 4373.26 22088.64 14860.73 16288.41 26761.88 22673.88 28290.53 155
v14878.72 16777.80 16781.47 18882.73 26561.96 22886.30 17688.08 19873.26 12976.18 17685.47 23362.46 13492.36 18471.92 14273.82 28390.09 172
Patchmatch-test64.82 29963.24 29869.57 30979.42 31149.82 32763.49 33669.05 33451.98 32659.95 31880.13 29450.91 24370.98 33740.66 32973.57 28487.90 238
WR-MVS_H78.51 17278.49 14978.56 24588.02 16456.38 29388.43 11192.67 5777.14 4873.89 21687.55 17566.25 9489.24 25258.92 25173.55 28590.06 176
testgi66.67 29266.53 28867.08 31775.62 32641.69 33875.93 30276.50 31566.11 23165.20 29986.59 20535.72 32674.71 33243.71 32273.38 28684.84 290
pm-mvs177.25 20176.68 19578.93 23984.22 23058.62 26086.41 17288.36 19371.37 15573.31 21988.01 16761.22 15689.15 25464.24 20773.01 28789.03 209
eth_miper_zixun_eth77.92 18876.69 19481.61 18683.00 25661.98 22783.15 24489.20 16969.52 18774.86 20884.35 24961.76 14492.56 17771.50 14572.89 28890.28 163
miper_lstm_enhance74.11 23873.11 23677.13 26880.11 30159.62 25272.23 31786.92 21966.76 22270.40 24982.92 26656.93 19482.92 30369.06 16872.63 28988.87 217
tpmvs71.09 26369.29 26476.49 27282.04 27756.04 29778.92 28681.37 28364.05 25667.18 28178.28 30649.74 25889.77 24249.67 29872.37 29083.67 301
PEN-MVS77.73 19177.69 17377.84 25587.07 19253.91 31087.91 13491.18 11277.56 4073.14 22288.82 14461.23 15589.17 25359.95 24172.37 29090.43 158
DSMNet-mixed57.77 30756.90 30860.38 32167.70 33835.61 34169.18 32553.97 34332.30 34057.49 32479.88 29740.39 31268.57 33938.78 33172.37 29076.97 328
IterMVS-SCA-FT75.43 22773.87 22880.11 21782.69 26664.85 17681.57 26283.47 25969.16 19670.49 24884.15 25251.95 23288.15 26969.23 16572.14 29387.34 250
tpm cat170.57 26768.31 27177.35 26482.41 27357.95 26978.08 29380.22 29652.04 32568.54 27177.66 31252.00 23187.84 27351.77 28672.07 29486.25 271
RPSCF73.23 24871.46 24978.54 24682.50 27059.85 25082.18 25482.84 26958.96 29871.15 24489.41 13445.48 28884.77 29458.82 25371.83 29591.02 138
IterMVS74.29 23572.94 23878.35 24981.53 28463.49 20381.58 26182.49 27168.06 21369.99 25783.69 26051.66 23885.54 28965.85 19571.64 29686.01 278
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
AllTest70.96 26468.09 27579.58 22985.15 21663.62 19784.58 21779.83 29862.31 27360.32 31686.73 19432.02 33188.96 25950.28 29371.57 29786.15 274
TestCases79.58 22985.15 21663.62 19779.83 29862.31 27360.32 31686.73 19432.02 33188.96 25950.28 29371.57 29786.15 274
baseline176.98 20476.75 19377.66 25888.13 15955.66 30285.12 20381.89 27773.04 13276.79 16088.90 14162.43 13587.78 27463.30 21371.18 29989.55 197
Patchmtry70.74 26569.16 26575.49 28180.72 29454.07 30974.94 31280.30 29458.34 30270.01 25581.19 28252.50 22086.54 28253.37 28271.09 30085.87 281
DTE-MVSNet76.99 20376.80 18977.54 26286.24 20253.06 31487.52 14190.66 12477.08 5172.50 22888.67 14760.48 16889.52 24757.33 26770.74 30190.05 177
MIMVSNet168.58 28166.78 28773.98 29380.07 30251.82 31680.77 26684.37 24464.40 25259.75 31982.16 27836.47 32383.63 29942.73 32570.33 30286.48 269
pmmvs674.69 23273.39 23178.61 24481.38 28757.48 27786.64 16787.95 20164.99 24770.18 25286.61 20450.43 25089.52 24762.12 22470.18 30388.83 219
TinyColmap67.30 28964.81 29174.76 28781.92 27956.68 28880.29 27281.49 28260.33 28556.27 32883.22 26424.77 33687.66 27545.52 31869.47 30479.95 322
OurMVSNet-221017-074.26 23672.42 24279.80 22383.76 23959.59 25385.92 18786.64 22166.39 22966.96 28287.58 17339.46 31391.60 20665.76 19669.27 30588.22 232
JIA-IIPM66.32 29562.82 30276.82 27077.09 32161.72 23265.34 33375.38 31758.04 30464.51 30162.32 33242.05 30486.51 28351.45 28969.22 30682.21 313
ADS-MVSNet266.20 29663.33 29774.82 28679.92 30358.75 25967.55 33075.19 31853.37 32265.25 29775.86 31842.32 30180.53 31141.57 32768.91 30785.18 285
ADS-MVSNet64.36 30062.88 30168.78 31479.92 30347.17 33167.55 33071.18 32753.37 32265.25 29775.86 31842.32 30173.99 33541.57 32768.91 30785.18 285
test20.0367.45 28766.95 28668.94 31175.48 32744.84 33477.50 29677.67 30966.66 22463.01 30883.80 25747.02 27478.40 31742.53 32668.86 30983.58 302
EU-MVSNet68.53 28267.61 28371.31 30478.51 31547.01 33284.47 21884.27 24642.27 33166.44 29084.79 24540.44 31183.76 29758.76 25468.54 31083.17 305
our_test_369.14 27867.00 28575.57 27979.80 30658.80 25877.96 29477.81 30859.55 29362.90 31078.25 30747.43 27183.97 29651.71 28767.58 31183.93 300
ppachtmachnet_test70.04 27367.34 28478.14 25179.80 30661.13 23679.19 28380.59 28959.16 29765.27 29679.29 30046.75 27787.29 27749.33 29966.72 31286.00 280
LF4IMVS64.02 30162.19 30369.50 31070.90 33653.29 31376.13 30077.18 31352.65 32458.59 32080.98 28723.55 33776.52 32553.06 28466.66 31378.68 325
Patchmatch-RL test70.24 27167.78 28177.61 26077.43 31859.57 25471.16 31970.33 32862.94 26668.65 26972.77 32450.62 24785.49 29069.58 16366.58 31487.77 241
dp66.80 29065.43 29070.90 30679.74 30848.82 32975.12 31074.77 32059.61 29264.08 30477.23 31342.89 29780.72 31048.86 30166.58 31483.16 306
FPMVS53.68 30951.64 31159.81 32265.08 33951.03 32269.48 32469.58 33241.46 33240.67 33672.32 32516.46 34370.00 33824.24 33865.42 31658.40 336
pmmvs-eth3d70.50 26967.83 27978.52 24777.37 31966.18 15081.82 25681.51 28158.90 29963.90 30580.42 29242.69 29986.28 28558.56 25565.30 31783.11 307
N_pmnet52.79 31053.26 31051.40 32678.99 3147.68 35169.52 3233.89 35151.63 32757.01 32574.98 32140.83 30965.96 34037.78 33264.67 31880.56 321
PM-MVS66.41 29464.14 29473.20 29573.92 32856.45 29078.97 28564.96 34063.88 26064.72 30080.24 29319.84 34083.44 30066.24 18964.52 31979.71 323
SixPastTwentyTwo73.37 24471.26 25379.70 22485.08 22057.89 27085.57 19183.56 25671.03 15965.66 29385.88 22242.10 30392.57 17659.11 24963.34 32088.65 225
TransMVSNet (Re)75.39 22974.56 21977.86 25485.50 21257.10 28186.78 16386.09 23172.17 14271.53 24087.34 17963.01 12789.31 25156.84 27061.83 32187.17 255
MDA-MVSNet_test_wron65.03 29762.92 29971.37 30175.93 32356.73 28569.09 32874.73 32157.28 31054.03 33077.89 30945.88 28274.39 33449.89 29761.55 32282.99 310
YYNet165.03 29762.91 30071.38 30075.85 32456.60 28969.12 32774.66 32357.28 31054.12 32977.87 31045.85 28374.48 33349.95 29661.52 32383.05 308
ambc75.24 28373.16 33250.51 32563.05 33787.47 21264.28 30277.81 31117.80 34189.73 24457.88 26260.64 32485.49 282
TDRefinement67.49 28564.34 29376.92 26973.47 33161.07 23784.86 20982.98 26759.77 29158.30 32285.13 24026.06 33587.89 27247.92 30960.59 32581.81 316
Gipumacopyleft45.18 31341.86 31555.16 32477.03 32251.52 31932.50 34580.52 29032.46 33927.12 34035.02 3409.52 34775.50 32922.31 33960.21 32638.45 339
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
new-patchmatchnet61.73 30361.73 30461.70 32072.74 33524.50 34869.16 32678.03 30761.40 27956.72 32675.53 32038.42 31776.48 32645.95 31757.67 32784.13 298
MDA-MVSNet-bldmvs66.68 29163.66 29575.75 27679.28 31260.56 24473.92 31478.35 30564.43 25150.13 33379.87 29844.02 29383.67 29846.10 31656.86 32883.03 309
new_pmnet50.91 31150.29 31252.78 32568.58 33734.94 34363.71 33556.63 34239.73