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 bysorted bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort by
MSP-MVS81.06 381.40 480.02 186.21 3162.73 986.09 1786.83 865.51 1183.81 1090.51 2263.71 1289.23 1981.51 288.44 2788.09 20
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
SteuartSystems-ACMMP79.48 1079.31 1079.98 283.01 7262.18 1687.60 985.83 1966.69 878.03 2690.98 1554.26 5190.06 1278.42 1889.02 2387.69 32
Skip Steuart: Steuart Systems R&D Blog.
MSC_two_6792asdad79.95 387.24 1461.04 3185.62 2390.96 179.31 890.65 887.85 26
No_MVS79.95 387.24 1461.04 3185.62 2390.96 179.31 890.65 887.85 26
SMA-MVScopyleft80.28 680.39 779.95 386.60 2361.95 1986.33 1385.75 2162.49 6182.20 1592.28 156.53 3389.70 1579.85 491.48 188.19 17
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
OPU-MVS79.83 687.54 1160.93 3587.82 789.89 4167.01 190.33 1173.16 4491.15 488.23 15
DeepC-MVS69.38 278.56 1778.14 2179.83 683.60 6361.62 2384.17 4186.85 663.23 4573.84 5790.25 3157.68 2789.96 1374.62 3389.03 2287.89 23
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
3Dnovator+66.72 475.84 4474.57 5279.66 882.40 7659.92 4785.83 2186.32 1666.92 667.80 14789.24 5042.03 18789.38 1864.07 10686.50 5489.69 2
DVP-MVS++81.67 182.40 179.47 987.24 1459.15 5988.18 187.15 365.04 1584.26 591.86 667.01 190.84 379.48 591.38 288.42 10
CNVR-MVS79.84 979.97 979.45 1087.90 262.17 1784.37 3585.03 3466.96 477.58 2790.06 3559.47 2089.13 2178.67 1389.73 1687.03 52
NCCC78.58 1678.31 1879.39 1187.51 1262.61 1385.20 3084.42 4266.73 774.67 4789.38 4855.30 4189.18 2074.19 3687.34 4286.38 68
SED-MVS81.56 282.30 279.32 1287.77 458.90 6887.82 786.78 1064.18 3185.97 191.84 866.87 390.83 578.63 1690.87 588.23 15
ZNCC-MVS78.82 1278.67 1679.30 1386.43 2862.05 1886.62 1186.01 1863.32 4275.08 3890.47 2553.96 5588.68 2676.48 2489.63 2087.16 50
DPE-MVScopyleft80.56 580.98 579.29 1487.27 1360.56 4185.71 2586.42 1463.28 4383.27 1391.83 1064.96 790.47 1076.41 2589.67 1886.84 58
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
test_0728_SECOND79.19 1587.82 359.11 6287.85 587.15 390.84 378.66 1490.61 1187.62 36
ACMMPR77.71 2477.23 2779.16 1686.75 1862.93 786.29 1484.24 4562.82 5473.55 6090.56 2149.80 9988.24 3274.02 3887.03 4486.32 76
region2R77.67 2677.18 2879.15 1786.76 1762.95 686.29 1484.16 4762.81 5673.30 6290.58 2049.90 9788.21 3373.78 4087.03 4486.29 79
DeepPCF-MVS69.58 179.03 1179.00 1279.13 1884.92 5660.32 4483.03 5685.33 2762.86 5380.17 1790.03 3761.76 1488.95 2374.21 3588.67 2688.12 19
DeepC-MVS_fast68.24 377.25 2976.63 3279.12 1986.15 3460.86 3684.71 3284.85 3861.98 7373.06 7088.88 5453.72 5889.06 2268.27 6888.04 3787.42 42
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
HFP-MVS78.01 2377.65 2479.10 2086.71 1962.81 886.29 1484.32 4462.82 5473.96 5590.50 2353.20 6488.35 3074.02 3887.05 4386.13 82
HPM-MVS++copyleft79.88 880.14 879.10 2088.17 164.80 186.59 1283.70 6065.37 1278.78 2290.64 1858.63 2487.24 5079.00 1190.37 1485.26 120
XVS77.17 3076.56 3379.00 2286.32 2962.62 1185.83 2183.92 5164.55 2272.17 8290.01 3947.95 11988.01 3771.55 5586.74 5186.37 70
X-MVStestdata70.21 11367.28 16179.00 2286.32 2962.62 1185.83 2183.92 5164.55 2272.17 826.49 38147.95 11988.01 3771.55 5586.74 5186.37 70
GST-MVS78.14 2177.85 2378.99 2486.05 3861.82 2285.84 2085.21 2963.56 4074.29 5190.03 3752.56 6888.53 2874.79 3288.34 2986.63 64
TSAR-MVS + MP.78.44 1878.28 1978.90 2584.96 5261.41 2684.03 4483.82 5859.34 11679.37 1989.76 4459.84 1687.62 4676.69 2386.74 5187.68 33
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
PGM-MVS76.77 3476.06 3778.88 2686.14 3562.73 982.55 6683.74 5961.71 7572.45 8190.34 2848.48 11588.13 3472.32 4886.85 4985.78 93
APDe-MVS80.16 780.59 678.86 2786.64 2160.02 4588.12 386.42 1462.94 5082.40 1492.12 259.64 1889.76 1478.70 1288.32 3186.79 60
ACMMP_NAP78.77 1478.78 1378.74 2885.44 4561.04 3183.84 4885.16 3062.88 5278.10 2491.26 1352.51 6988.39 2979.34 790.52 1386.78 61
MVS_030478.73 1578.75 1478.66 2980.82 10057.62 8285.31 2981.31 11170.51 174.17 5291.24 1454.99 4489.56 1682.29 188.13 3488.80 6
MP-MVScopyleft78.35 1978.26 2078.64 3086.54 2563.47 486.02 1983.55 6463.89 3673.60 5990.60 1954.85 4786.72 6777.20 2188.06 3685.74 99
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
HPM-MVScopyleft77.28 2876.85 2978.54 3185.00 5160.81 3882.91 5985.08 3162.57 5973.09 6989.97 4050.90 9387.48 4875.30 2886.85 4987.33 48
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
CP-MVS77.12 3176.68 3178.43 3286.05 3863.18 587.55 1083.45 6762.44 6372.68 7590.50 2348.18 11787.34 4973.59 4285.71 5784.76 135
DVP-MVScopyleft80.84 481.64 378.42 3387.75 759.07 6387.85 585.03 3464.26 2883.82 892.00 364.82 890.75 878.66 1490.61 1185.45 110
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
MTAPA76.90 3376.42 3478.35 3486.08 3763.57 274.92 19880.97 12265.13 1475.77 3490.88 1648.63 11286.66 6977.23 2088.17 3384.81 132
mPP-MVS76.54 3575.93 3978.34 3586.47 2663.50 385.74 2482.28 8962.90 5171.77 8590.26 3046.61 14386.55 7371.71 5385.66 5884.97 128
CDPH-MVS76.31 3775.67 4378.22 3685.35 4859.14 6181.31 8684.02 4856.32 16874.05 5388.98 5353.34 6387.92 4069.23 6688.42 2887.59 37
ACMMPcopyleft76.02 4275.33 4578.07 3785.20 4961.91 2085.49 2884.44 4163.04 4869.80 10989.74 4545.43 15687.16 5472.01 5082.87 8285.14 121
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
CANet76.46 3675.93 3978.06 3881.29 9257.53 8482.35 6883.31 7367.78 270.09 9986.34 9454.92 4688.90 2472.68 4784.55 6487.76 31
MP-MVS-pluss78.35 1978.46 1778.03 3984.96 5259.52 5282.93 5885.39 2662.15 6676.41 3291.51 1152.47 7186.78 6680.66 389.64 1987.80 29
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
APD-MVScopyleft78.02 2278.04 2277.98 4086.44 2760.81 3885.52 2684.36 4360.61 8879.05 2190.30 2955.54 4088.32 3173.48 4387.03 4484.83 131
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
SD-MVS77.70 2577.62 2577.93 4184.47 5961.88 2184.55 3383.87 5660.37 9579.89 1889.38 4854.97 4585.58 9676.12 2684.94 6186.33 74
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
test1277.76 4284.52 5858.41 7483.36 7172.93 7254.61 4988.05 3688.12 3586.81 59
SF-MVS78.82 1279.22 1177.60 4382.88 7457.83 7984.99 3188.13 261.86 7479.16 2090.75 1757.96 2587.09 5977.08 2290.18 1587.87 25
MCST-MVS77.48 2777.45 2677.54 4486.67 2058.36 7583.22 5486.93 556.91 15674.91 4288.19 6059.15 2287.68 4573.67 4187.45 4186.57 65
CSCG76.92 3276.75 3077.41 4583.96 6259.60 5082.95 5786.50 1360.78 8675.27 3684.83 12360.76 1586.56 7267.86 7487.87 4086.06 84
PHI-MVS75.87 4375.36 4477.41 4580.62 10655.91 11284.28 3885.78 2056.08 17473.41 6186.58 8950.94 9288.54 2770.79 5889.71 1787.79 30
SR-MVS76.13 4175.70 4277.40 4785.87 4061.20 2985.52 2682.19 9059.99 10475.10 3790.35 2747.66 12486.52 7471.64 5482.99 7784.47 141
TSAR-MVS + GP.74.90 4974.15 5677.17 4882.00 8058.77 7181.80 7878.57 16158.58 12774.32 5084.51 13355.94 3887.22 5167.11 8284.48 6685.52 106
CS-MVS76.25 3975.98 3877.06 4980.15 11555.63 11784.51 3483.90 5363.24 4473.30 6287.27 7555.06 4386.30 8271.78 5284.58 6389.25 4
DPM-MVS75.47 4775.00 4876.88 5081.38 9159.16 5879.94 10185.71 2256.59 16472.46 7986.76 8056.89 3187.86 4266.36 8788.91 2583.64 173
HPM-MVS_fast74.30 5973.46 6476.80 5184.45 6059.04 6583.65 5181.05 11960.15 10170.43 9589.84 4241.09 20385.59 9567.61 7882.90 8185.77 96
test_prior76.69 5284.20 6157.27 8784.88 3786.43 7786.38 68
APD-MVS_3200maxsize74.96 4874.39 5476.67 5382.20 7858.24 7683.67 5083.29 7458.41 13073.71 5890.14 3245.62 14985.99 8669.64 6282.85 8385.78 93
train_agg76.27 3876.15 3676.64 5485.58 4361.59 2481.62 8181.26 11455.86 17674.93 4088.81 5553.70 5984.68 11775.24 3088.33 3083.65 172
SR-MVS-dyc-post74.57 5573.90 5876.58 5583.49 6559.87 4884.29 3681.36 10658.07 13673.14 6790.07 3344.74 16385.84 9068.20 6981.76 9384.03 151
CS-MVS-test75.62 4675.31 4676.56 5680.63 10555.13 12683.88 4785.22 2862.05 7071.49 8986.03 10253.83 5786.36 8067.74 7586.91 4888.19 17
h-mvs3372.71 7271.49 7976.40 5781.99 8159.58 5176.92 15776.74 19960.40 9274.81 4385.95 10645.54 15285.76 9270.41 6070.61 22483.86 160
DP-MVS Recon72.15 8370.73 9476.40 5786.57 2457.99 7881.15 8882.96 8057.03 15366.78 16585.56 11344.50 16688.11 3551.77 20580.23 10983.10 186
ETV-MVS74.46 5773.84 6076.33 5979.27 13155.24 12579.22 11485.00 3664.97 2072.65 7679.46 23853.65 6287.87 4167.45 8082.91 8085.89 90
OPM-MVS74.73 5274.25 5576.19 6080.81 10159.01 6682.60 6583.64 6163.74 3872.52 7887.49 7047.18 13485.88 8969.47 6480.78 9883.66 171
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
HQP_MVS74.31 5873.73 6176.06 6181.41 8956.31 10184.22 3984.01 4964.52 2469.27 11786.10 9945.26 16087.21 5268.16 7180.58 10284.65 136
mvsmamba71.15 9569.54 11275.99 6277.61 18353.46 14481.95 7775.11 22257.73 14666.95 16385.96 10537.14 24087.56 4767.94 7375.49 16686.97 53
Effi-MVS+-dtu69.64 12967.53 15075.95 6376.10 21362.29 1580.20 9776.06 20759.83 10965.26 19977.09 26841.56 19584.02 12960.60 13971.09 22081.53 210
EPNet73.09 6872.16 7275.90 6475.95 21556.28 10383.05 5572.39 25266.53 965.27 19687.00 7750.40 9585.47 10162.48 12386.32 5585.94 86
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
3Dnovator64.47 572.49 7571.39 8275.79 6577.70 17558.99 6780.66 9383.15 7862.24 6565.46 19286.59 8842.38 18585.52 9759.59 14884.72 6282.85 191
LPG-MVS_test72.74 7171.74 7675.76 6680.22 11057.51 8582.55 6683.40 6961.32 7866.67 16987.33 7339.15 21786.59 7067.70 7677.30 14883.19 183
LGP-MVS_train75.76 6680.22 11057.51 8583.40 6961.32 7866.67 16987.33 7339.15 21786.59 7067.70 7677.30 14883.19 183
EC-MVSNet75.84 4475.87 4175.74 6878.86 14152.65 15883.73 4986.08 1763.47 4172.77 7487.25 7653.13 6587.93 3971.97 5185.57 5986.66 63
MVS_111021_HR74.02 6073.46 6475.69 6983.01 7260.63 4077.29 14878.40 17261.18 8170.58 9485.97 10454.18 5384.00 13067.52 7982.98 7982.45 197
casdiffmvs_mvgpermissive76.14 4076.30 3575.66 7076.46 20951.83 17679.67 10885.08 3165.02 1875.84 3388.58 5959.42 2185.08 10772.75 4683.93 7190.08 1
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
DELS-MVS74.76 5174.46 5375.65 7177.84 17252.25 16875.59 18284.17 4663.76 3773.15 6682.79 16459.58 1986.80 6567.24 8186.04 5687.89 23
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
Effi-MVS+73.31 6672.54 7075.62 7277.87 17153.64 13979.62 11079.61 14061.63 7672.02 8482.61 16956.44 3485.97 8763.99 10979.07 12687.25 49
MAR-MVS71.51 9170.15 10475.60 7381.84 8359.39 5481.38 8582.90 8254.90 20468.08 13878.70 24747.73 12285.51 9851.68 20784.17 6981.88 207
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
ACMP63.53 672.30 7871.20 8775.59 7480.28 10857.54 8382.74 6282.84 8460.58 8965.24 20086.18 9639.25 21586.03 8566.95 8576.79 15583.22 181
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
HQP-MVS73.45 6472.80 6875.40 7580.66 10254.94 12782.31 7083.90 5362.10 6767.85 14285.54 11645.46 15486.93 6167.04 8380.35 10684.32 143
PCF-MVS61.88 870.95 9969.49 11475.35 7677.63 17855.71 11476.04 17581.81 9650.30 25469.66 11085.40 11952.51 6984.89 11351.82 20480.24 10885.45 110
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
PS-MVSNAJss72.24 7971.21 8675.31 7778.50 15055.93 11181.63 8082.12 9156.24 17170.02 10385.68 11247.05 13684.34 12365.27 9974.41 17285.67 100
EIA-MVS71.78 8670.60 9575.30 7879.85 11953.54 14277.27 14983.26 7657.92 14266.49 17179.39 23952.07 7786.69 6860.05 14279.14 12585.66 101
CLD-MVS73.33 6572.68 6975.29 7978.82 14353.33 14878.23 12684.79 3961.30 8070.41 9681.04 20652.41 7287.12 5764.61 10582.49 8785.41 114
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
iter_conf_final69.82 12168.02 14075.23 8079.38 12852.91 15580.11 9873.96 23954.99 20268.04 13983.59 15129.05 31087.16 5465.41 9877.62 14285.63 103
RRT_MVS69.42 13567.49 15375.21 8178.01 16852.56 16282.23 7478.15 17555.84 17865.65 18885.07 12030.86 29686.83 6461.56 13470.00 23586.24 81
PAPM_NR72.63 7371.80 7575.13 8281.72 8453.42 14679.91 10383.28 7559.14 11866.31 17685.90 10751.86 7986.06 8357.45 15780.62 10085.91 88
EI-MVSNet-Vis-set72.42 7771.59 7774.91 8378.47 15254.02 13577.05 15379.33 14665.03 1771.68 8779.35 24152.75 6784.89 11366.46 8674.23 17385.83 92
MVSFormer71.50 9270.38 10074.88 8478.76 14457.15 9382.79 6078.48 16551.26 24469.49 11283.22 15843.99 17183.24 14366.06 8979.37 11884.23 146
CPTT-MVS72.78 7072.08 7474.87 8584.88 5761.41 2684.15 4277.86 17955.27 19167.51 15388.08 6341.93 18981.85 17569.04 6780.01 11081.35 217
iter_conf0569.40 13667.62 14674.73 8677.84 17251.13 18079.28 11373.71 24254.62 20668.17 13483.59 15128.68 31587.16 5465.74 9576.95 15285.91 88
EPP-MVSNet72.16 8271.31 8574.71 8778.68 14749.70 20582.10 7581.65 9860.40 9265.94 18185.84 10851.74 8286.37 7955.93 16679.55 11788.07 22
原ACMM174.69 8885.39 4759.40 5383.42 6851.47 24070.27 9886.61 8748.61 11386.51 7553.85 18787.96 3878.16 258
ET-MVSNet_ETH3D67.96 16565.72 19274.68 8976.67 20355.62 11975.11 19274.74 22752.91 22460.03 25980.12 22433.68 27182.64 16261.86 12976.34 15885.78 93
MSLP-MVS++73.77 6373.47 6374.66 9083.02 7159.29 5782.30 7381.88 9459.34 11671.59 8886.83 7845.94 14783.65 13665.09 10085.22 6081.06 224
PVSNet_Blended_VisFu71.45 9370.39 9974.65 9182.01 7958.82 7079.93 10280.35 13255.09 19665.82 18782.16 18449.17 10682.64 16260.34 14078.62 13482.50 196
114514_t70.83 10169.56 11174.64 9286.21 3154.63 13282.34 6981.81 9648.22 27363.01 22985.83 10940.92 20487.10 5857.91 15479.79 11182.18 200
Vis-MVSNetpermissive72.18 8071.37 8374.61 9381.29 9255.41 12280.90 8978.28 17460.73 8769.23 12088.09 6244.36 16882.65 16157.68 15581.75 9585.77 96
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
hse-mvs271.04 9769.86 10774.60 9479.58 12357.12 9573.96 21475.25 21760.40 9274.81 4381.95 18945.54 15282.90 15070.41 6066.83 27283.77 165
test_djsdf69.45 13467.74 14274.58 9574.57 23854.92 12982.79 6078.48 16551.26 24465.41 19383.49 15638.37 22483.24 14366.06 8969.25 25185.56 105
AUN-MVS68.45 15566.41 17874.57 9679.53 12557.08 9673.93 21775.23 21854.44 21266.69 16881.85 19137.10 24282.89 15162.07 12666.84 27183.75 166
casdiffmvspermissive74.80 5074.89 5074.53 9775.59 22150.37 19478.17 12785.06 3362.80 5774.40 4987.86 6757.88 2683.61 13769.46 6582.79 8489.59 3
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
EI-MVSNet-UG-set71.92 8471.06 9074.52 9877.98 16953.56 14176.62 16179.16 14764.40 2671.18 9078.95 24652.19 7584.66 11965.47 9773.57 18385.32 117
API-MVS72.17 8171.41 8174.45 9981.95 8257.22 8884.03 4480.38 13159.89 10868.40 12982.33 17849.64 10087.83 4351.87 20384.16 7078.30 256
PAPR71.72 8970.82 9374.41 10081.20 9651.17 17979.55 11183.33 7255.81 18066.93 16484.61 12950.95 9186.06 8355.79 16979.20 12386.00 85
baseline74.61 5474.70 5174.34 10175.70 21749.99 20277.54 14084.63 4062.73 5873.98 5487.79 6957.67 2883.82 13369.49 6382.74 8589.20 5
thisisatest053067.92 16665.78 19174.33 10276.29 21051.03 18176.89 15874.25 23553.67 21865.59 19081.76 19335.15 25685.50 9955.94 16572.47 20286.47 67
tttt051767.83 16865.66 19374.33 10276.69 20250.82 18677.86 13273.99 23854.54 21064.64 21282.53 17435.06 25785.50 9955.71 17069.91 23886.67 62
MG-MVS73.96 6173.89 5974.16 10485.65 4249.69 20781.59 8381.29 11361.45 7771.05 9188.11 6151.77 8187.73 4461.05 13683.09 7585.05 125
ACMM61.98 770.80 10369.73 10974.02 10580.59 10758.59 7382.68 6382.02 9355.46 18867.18 15884.39 13538.51 22283.17 14560.65 13876.10 16080.30 235
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
v7n69.01 14267.36 15873.98 10672.51 26752.65 15878.54 12481.30 11260.26 10062.67 23381.62 19543.61 17384.49 12057.01 15968.70 25984.79 133
AdaColmapbinary69.99 11768.66 12873.97 10784.94 5457.83 7982.63 6478.71 15756.28 17064.34 21484.14 13841.57 19487.06 6046.45 24678.88 12777.02 273
v119269.97 11868.68 12773.85 10873.19 25250.94 18277.68 13681.36 10657.51 14868.95 12380.85 21345.28 15985.33 10562.97 11970.37 22885.27 119
FA-MVS(test-final)69.82 12168.48 13073.84 10978.44 15350.04 20075.58 18478.99 15158.16 13467.59 15182.14 18542.66 18085.63 9356.60 16176.19 15985.84 91
v1070.21 11369.02 12273.81 11073.51 25050.92 18478.74 11881.39 10460.05 10366.39 17481.83 19247.58 12685.41 10462.80 12068.86 25785.09 124
QAPM70.05 11568.81 12573.78 11176.54 20753.43 14583.23 5383.48 6552.89 22565.90 18386.29 9541.55 19686.49 7651.01 21078.40 13681.42 211
OMC-MVS71.40 9470.60 9573.78 11176.60 20553.15 15179.74 10779.78 13658.37 13168.75 12486.45 9245.43 15680.60 20362.58 12177.73 14187.58 38
UA-Net73.13 6772.93 6773.76 11383.58 6451.66 17778.75 11777.66 18367.75 372.61 7789.42 4649.82 9883.29 14253.61 18983.14 7486.32 76
v114470.42 10969.31 11773.76 11373.22 25150.64 18977.83 13381.43 10358.58 12769.40 11581.16 20347.53 12785.29 10664.01 10870.64 22285.34 116
VDD-MVS72.50 7472.09 7373.75 11581.58 8549.69 20777.76 13577.63 18463.21 4673.21 6589.02 5242.14 18683.32 14161.72 13082.50 8688.25 14
Fast-Effi-MVS+70.28 11269.12 12173.73 11678.50 15051.50 17875.01 19579.46 14456.16 17368.59 12579.55 23653.97 5484.05 12653.34 19177.53 14485.65 102
canonicalmvs74.67 5374.98 4973.71 11778.94 14050.56 19280.23 9583.87 5660.30 9977.15 2986.56 9059.65 1782.00 17366.01 9182.12 8888.58 9
HyFIR lowres test65.67 20563.01 22373.67 11879.97 11855.65 11669.07 27875.52 21342.68 32463.53 22477.95 25640.43 20581.64 17846.01 25071.91 21183.73 167
jajsoiax68.25 15866.45 17473.66 11975.62 21955.49 12180.82 9078.51 16452.33 23064.33 21584.11 13928.28 31781.81 17763.48 11570.62 22383.67 169
v2v48270.50 10869.45 11673.66 11972.62 26350.03 20177.58 13780.51 12959.90 10569.52 11182.14 18547.53 12784.88 11565.07 10170.17 23286.09 83
cascas65.98 20163.42 21773.64 12177.26 19152.58 16172.26 24277.21 19248.56 26861.21 25274.60 29832.57 28985.82 9150.38 21576.75 15682.52 195
FE-MVS65.91 20263.33 21973.63 12277.36 18951.95 17572.62 23575.81 20853.70 21765.31 19478.96 24528.81 31486.39 7843.93 26973.48 18682.55 193
mvs_tets68.18 16066.36 18073.63 12275.61 22055.35 12480.77 9178.56 16252.48 22964.27 21784.10 14027.45 32381.84 17663.45 11670.56 22583.69 168
GeoE71.01 9870.15 10473.60 12479.57 12452.17 16978.93 11678.12 17658.02 13867.76 15083.87 14552.36 7382.72 15956.90 16075.79 16285.92 87
anonymousdsp67.00 18664.82 20373.57 12570.09 29856.13 10676.35 16677.35 19048.43 27164.99 20880.84 21433.01 27880.34 20864.66 10367.64 26684.23 146
test_fmvsm_n_192071.73 8871.14 8873.50 12672.52 26656.53 10075.60 18176.16 20348.11 27577.22 2885.56 11353.10 6677.43 25174.86 3177.14 15086.55 66
v870.33 11169.28 11873.49 12773.15 25350.22 19678.62 12180.78 12560.79 8566.45 17382.11 18749.35 10284.98 11063.58 11468.71 25885.28 118
Fast-Effi-MVS+-dtu67.37 17565.33 19873.48 12872.94 25857.78 8177.47 14276.88 19557.60 14761.97 24476.85 27239.31 21380.49 20754.72 17970.28 23182.17 202
alignmvs73.86 6273.99 5773.45 12978.20 16050.50 19378.57 12282.43 8759.40 11476.57 3086.71 8456.42 3581.23 18965.84 9381.79 9288.62 7
lupinMVS69.57 13068.28 13673.44 13078.76 14457.15 9376.57 16273.29 24646.19 29569.49 11282.18 18143.99 17179.23 22264.66 10379.37 11883.93 155
jason69.65 12868.39 13573.43 13178.27 15956.88 9777.12 15173.71 24246.53 29269.34 11683.22 15843.37 17579.18 22364.77 10279.20 12384.23 146
jason: jason.
IB-MVS56.42 1265.40 21062.73 22773.40 13274.89 22852.78 15773.09 22975.13 22155.69 18358.48 28073.73 30332.86 28086.32 8150.63 21370.11 23381.10 223
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
v192192069.47 13368.17 13773.36 13373.06 25550.10 19977.39 14380.56 12756.58 16568.59 12580.37 21844.72 16484.98 11062.47 12469.82 24085.00 126
v14419269.71 12468.51 12973.33 13473.10 25450.13 19877.54 14080.64 12656.65 15868.57 12780.55 21646.87 14184.96 11262.98 11869.66 24584.89 130
IS-MVSNet71.57 9071.00 9173.27 13578.86 14145.63 25580.22 9678.69 15864.14 3466.46 17287.36 7249.30 10385.60 9450.26 21683.71 7388.59 8
VDDNet71.81 8571.33 8473.26 13682.80 7547.60 23578.74 11875.27 21659.59 11372.94 7189.40 4741.51 19783.91 13158.75 15282.99 7788.26 13
v124069.24 13967.91 14173.25 13773.02 25749.82 20377.21 15080.54 12856.43 16768.34 13180.51 21743.33 17684.99 10862.03 12869.77 24384.95 129
UGNet68.81 14467.39 15673.06 13878.33 15754.47 13379.77 10575.40 21560.45 9163.22 22684.40 13432.71 28580.91 19851.71 20680.56 10483.81 161
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
BH-RMVSNet68.81 14467.42 15572.97 13980.11 11652.53 16374.26 20976.29 20258.48 12968.38 13084.20 13642.59 18183.83 13246.53 24575.91 16182.56 192
PS-MVSNAJ70.51 10769.70 11072.93 14081.52 8655.79 11374.92 19879.00 15055.04 20169.88 10778.66 24847.05 13682.19 17061.61 13179.58 11580.83 227
XVG-OURS68.76 14767.37 15772.90 14174.32 24457.22 8870.09 27178.81 15455.24 19267.79 14885.81 11136.54 24778.28 23962.04 12775.74 16383.19 183
xiu_mvs_v2_base70.52 10669.75 10872.84 14281.21 9555.63 11775.11 19278.92 15254.92 20369.96 10679.68 23347.00 14082.09 17261.60 13279.37 11880.81 228
nrg03072.96 6973.01 6672.84 14275.41 22450.24 19580.02 9982.89 8358.36 13274.44 4886.73 8258.90 2380.83 19965.84 9374.46 17087.44 41
thisisatest051565.83 20363.50 21672.82 14473.75 24849.50 21071.32 25373.12 24849.39 26063.82 22176.50 28034.95 25984.84 11653.20 19375.49 16684.13 150
XVG-OURS-SEG-HR68.81 14467.47 15472.82 14474.40 24256.87 9870.59 26479.04 14954.77 20566.99 16186.01 10339.57 21178.21 24062.54 12273.33 18983.37 177
OpenMVScopyleft61.03 968.85 14367.56 14772.70 14674.26 24553.99 13681.21 8781.34 11052.70 22662.75 23285.55 11538.86 22084.14 12548.41 23283.01 7679.97 240
Anonymous2024052969.91 11969.02 12272.56 14780.19 11347.65 23377.56 13980.99 12155.45 18969.88 10786.76 8039.24 21682.18 17154.04 18477.10 15187.85 26
V4268.65 14867.35 15972.56 14768.93 31250.18 19772.90 23179.47 14356.92 15569.45 11480.26 22246.29 14582.99 14764.07 10667.82 26484.53 138
dcpmvs_274.55 5675.23 4772.48 14982.34 7753.34 14777.87 13181.46 10257.80 14575.49 3586.81 7962.22 1377.75 24771.09 5782.02 9086.34 72
xiu_mvs_v1_base_debu68.58 15067.28 16172.48 14978.19 16157.19 9075.28 18775.09 22351.61 23570.04 10081.41 20032.79 28179.02 23063.81 11177.31 14581.22 219
xiu_mvs_v1_base68.58 15067.28 16172.48 14978.19 16157.19 9075.28 18775.09 22351.61 23570.04 10081.41 20032.79 28179.02 23063.81 11177.31 14581.22 219
xiu_mvs_v1_base_debi68.58 15067.28 16172.48 14978.19 16157.19 9075.28 18775.09 22351.61 23570.04 10081.41 20032.79 28179.02 23063.81 11177.31 14581.22 219
MVS_Test72.45 7672.46 7172.42 15374.88 22948.50 22376.28 16883.14 7959.40 11472.46 7984.68 12555.66 3981.12 19065.98 9279.66 11487.63 35
LFMVS71.78 8671.59 7772.32 15483.40 6746.38 24479.75 10671.08 26164.18 3172.80 7388.64 5842.58 18283.72 13457.41 15884.49 6586.86 57
ACMH+57.40 1166.12 20064.06 20772.30 15577.79 17452.83 15680.39 9478.03 17757.30 14957.47 28682.55 17127.68 32184.17 12445.54 25669.78 24179.90 241
test_fmvsmvis_n_192070.84 10070.38 10072.22 15671.16 28555.39 12375.86 17872.21 25449.03 26473.28 6486.17 9751.83 8077.29 25475.80 2778.05 13883.98 154
UniMVSNet (Re)70.63 10570.20 10271.89 15778.55 14945.29 25875.94 17782.92 8163.68 3968.16 13583.59 15153.89 5683.49 14053.97 18571.12 21986.89 56
MVSTER67.16 18265.58 19571.88 15870.37 29449.70 20570.25 27078.45 16851.52 23869.16 12180.37 21838.45 22382.50 16560.19 14171.46 21683.44 176
CHOSEN 1792x268865.08 21562.84 22571.82 15981.49 8856.26 10466.32 29074.20 23640.53 33563.16 22878.65 24941.30 19877.80 24645.80 25274.09 17481.40 214
DP-MVS65.68 20463.66 21471.75 16084.93 5556.87 9880.74 9273.16 24753.06 22259.09 27382.35 17736.79 24685.94 8832.82 33569.96 23772.45 316
Anonymous2023121169.28 13768.47 13271.73 16180.28 10847.18 23979.98 10082.37 8854.61 20767.24 15684.01 14239.43 21282.41 16855.45 17472.83 19785.62 104
EI-MVSNet69.27 13868.44 13471.73 16174.47 23949.39 21275.20 19078.45 16859.60 11069.16 12176.51 27851.29 8582.50 16559.86 14771.45 21783.30 178
eth_miper_zixun_eth67.63 17166.28 18471.67 16371.60 27848.33 22573.68 22377.88 17855.80 18165.91 18278.62 25147.35 13382.88 15259.45 14966.25 27683.81 161
MVS_111021_LR69.50 13268.78 12671.65 16478.38 15459.33 5574.82 20070.11 26858.08 13567.83 14684.68 12541.96 18876.34 26565.62 9677.54 14379.30 250
PAPM67.92 16666.69 17171.63 16578.09 16449.02 21577.09 15281.24 11651.04 24860.91 25383.98 14347.71 12384.99 10840.81 29279.32 12180.90 226
NR-MVSNet69.54 13168.85 12471.59 16678.05 16643.81 27174.20 21080.86 12465.18 1362.76 23184.52 13152.35 7483.59 13850.96 21270.78 22187.37 45
diffmvspermissive70.69 10470.43 9871.46 16769.45 30648.95 21772.93 23078.46 16757.27 15071.69 8683.97 14451.48 8477.92 24470.70 5977.95 14087.53 39
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
UniMVSNet_NR-MVSNet71.11 9671.00 9171.44 16879.20 13344.13 26776.02 17682.60 8666.48 1068.20 13284.60 13056.82 3282.82 15754.62 18070.43 22687.36 47
DU-MVS70.01 11669.53 11371.44 16878.05 16644.13 26775.01 19581.51 10164.37 2768.20 13284.52 13149.12 10982.82 15754.62 18070.43 22687.37 45
IterMVS-LS69.22 14068.48 13071.43 17074.44 24149.40 21176.23 16977.55 18559.60 11065.85 18681.59 19851.28 8681.58 18159.87 14669.90 23983.30 178
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
v14868.24 15967.19 16771.40 17170.43 29247.77 23275.76 18077.03 19458.91 12067.36 15480.10 22548.60 11481.89 17460.01 14366.52 27584.53 138
test_yl69.69 12569.13 11971.36 17278.37 15545.74 25174.71 20280.20 13357.91 14370.01 10483.83 14642.44 18382.87 15354.97 17679.72 11285.48 108
DCV-MVSNet69.69 12569.13 11971.36 17278.37 15545.74 25174.71 20280.20 13357.91 14370.01 10483.83 14642.44 18382.87 15354.97 17679.72 11285.48 108
LS3D64.71 21862.50 22971.34 17479.72 12255.71 11479.82 10474.72 22848.50 27056.62 29184.62 12833.59 27382.34 16929.65 35475.23 16875.97 281
TAMVS66.78 19165.27 19971.33 17579.16 13653.67 13873.84 22169.59 27252.32 23165.28 19581.72 19444.49 16777.40 25342.32 28478.66 13382.92 188
BH-untuned68.27 15767.29 16071.21 17679.74 12053.22 15076.06 17377.46 18857.19 15166.10 17881.61 19645.37 15883.50 13945.42 26076.68 15776.91 277
PVSNet_Blended68.59 14967.72 14371.19 17777.03 19750.57 19072.51 23881.52 9951.91 23364.22 21977.77 26449.13 10782.87 15355.82 16779.58 11580.14 238
TranMVSNet+NR-MVSNet70.36 11070.10 10671.17 17878.64 14842.97 27976.53 16381.16 11866.95 568.53 12885.42 11851.61 8383.07 14652.32 19769.70 24487.46 40
TR-MVS66.59 19665.07 20171.17 17879.18 13449.63 20973.48 22475.20 22052.95 22367.90 14080.33 22139.81 20983.68 13543.20 27773.56 18480.20 236
CDS-MVSNet66.80 19065.37 19671.10 18078.98 13953.13 15373.27 22771.07 26252.15 23264.72 21080.23 22343.56 17477.10 25645.48 25878.88 12783.05 187
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
PVSNet_BlendedMVS68.56 15367.72 14371.07 18177.03 19750.57 19074.50 20681.52 9953.66 21964.22 21979.72 23249.13 10782.87 15355.82 16773.92 17679.77 245
GA-MVS65.53 20763.70 21371.02 18270.87 28748.10 22770.48 26674.40 23156.69 15764.70 21176.77 27333.66 27281.10 19155.42 17570.32 23083.87 159
RPMNet61.53 25058.42 26170.86 18369.96 30052.07 17165.31 30081.36 10643.20 32059.36 26970.15 32735.37 25485.47 10136.42 32064.65 28875.06 290
TAPA-MVS59.36 1066.60 19465.20 20070.81 18476.63 20448.75 21976.52 16480.04 13550.64 25165.24 20084.93 12239.15 21778.54 23636.77 31376.88 15485.14 121
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
新几何170.76 18585.66 4161.13 3066.43 29344.68 30670.29 9786.64 8541.29 19975.23 26949.72 22081.75 9575.93 282
XVG-ACMP-BASELINE64.36 22362.23 23270.74 18672.35 26952.45 16670.80 26378.45 16853.84 21659.87 26281.10 20516.24 35679.32 22155.64 17371.76 21280.47 231
PLCcopyleft56.13 1465.09 21463.21 22170.72 18781.04 9854.87 13078.57 12277.47 18648.51 26955.71 29681.89 19033.71 27079.71 21441.66 28970.37 22877.58 265
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
c3_l68.33 15667.56 14770.62 18870.87 28746.21 24774.47 20778.80 15556.22 17266.19 17778.53 25351.88 7881.40 18362.08 12569.04 25484.25 145
K. test v360.47 25757.11 26970.56 18973.74 24948.22 22675.10 19462.55 31758.27 13353.62 32176.31 28127.81 32081.59 18047.42 23639.18 36681.88 207
cl2267.47 17466.45 17470.54 19069.85 30246.49 24373.85 22077.35 19055.07 19965.51 19177.92 25847.64 12581.10 19161.58 13369.32 24884.01 153
MVS67.37 17566.33 18170.51 19175.46 22350.94 18273.95 21581.85 9541.57 33062.54 23778.57 25247.98 11885.47 10152.97 19482.05 8975.14 289
miper_ehance_all_eth68.03 16267.24 16570.40 19270.54 29046.21 24773.98 21378.68 15955.07 19966.05 17977.80 26252.16 7681.31 18661.53 13569.32 24883.67 169
MVP-Stereo65.41 20963.80 21270.22 19377.62 18255.53 12076.30 16778.53 16350.59 25256.47 29378.65 24939.84 20882.68 16044.10 26872.12 21072.44 317
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
EG-PatchMatch MVS64.71 21862.87 22470.22 19377.68 17653.48 14377.99 13078.82 15353.37 22156.03 29577.41 26724.75 34084.04 12746.37 24773.42 18873.14 308
SixPastTwentyTwo61.65 24958.80 25870.20 19575.80 21647.22 23875.59 18269.68 27054.61 20754.11 31579.26 24227.07 32682.96 14843.27 27549.79 35380.41 233
miper_enhance_ethall67.11 18366.09 18770.17 19669.21 30945.98 24972.85 23278.41 17151.38 24165.65 18875.98 28651.17 8881.25 18760.82 13769.32 24883.29 180
ACMH55.70 1565.20 21363.57 21570.07 19778.07 16552.01 17479.48 11279.69 13755.75 18256.59 29280.98 20827.12 32580.94 19542.90 28171.58 21577.25 271
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
test_040263.25 23361.01 24669.96 19880.00 11754.37 13476.86 15972.02 25654.58 20958.71 27680.79 21535.00 25884.36 12226.41 36364.71 28771.15 332
cl____67.18 18066.26 18569.94 19970.20 29545.74 25173.30 22576.83 19755.10 19465.27 19679.57 23547.39 13180.53 20459.41 15169.22 25283.53 175
DIV-MVS_self_test67.18 18066.26 18569.94 19970.20 29545.74 25173.29 22676.83 19755.10 19465.27 19679.58 23447.38 13280.53 20459.43 15069.22 25283.54 174
lessismore_v069.91 20171.42 28247.80 23050.90 35650.39 33775.56 28927.43 32481.33 18545.91 25134.10 37280.59 230
BH-w/o66.85 18865.83 19069.90 20279.29 12952.46 16574.66 20476.65 20054.51 21164.85 20978.12 25445.59 15182.95 14943.26 27675.54 16574.27 302
baseline263.42 22961.26 24369.89 20372.55 26547.62 23471.54 25068.38 28250.11 25554.82 30775.55 29043.06 17880.96 19448.13 23367.16 27081.11 222
bld_raw_dy_0_6464.87 21663.22 22069.83 20474.79 23353.32 14978.15 12862.02 32151.20 24660.17 25783.12 16224.15 34274.20 27663.08 11772.33 20581.96 204
CNLPA65.43 20864.02 20869.68 20578.73 14658.07 7777.82 13470.71 26551.49 23961.57 25083.58 15438.23 22770.82 28843.90 27070.10 23480.16 237
OurMVSNet-221017-061.37 25358.63 26069.61 20672.05 27348.06 22873.93 21772.51 25147.23 28854.74 30880.92 21021.49 35081.24 18848.57 23156.22 33579.53 247
CANet_DTU68.18 16067.71 14569.59 20774.83 23146.24 24678.66 12076.85 19659.60 11063.45 22582.09 18835.25 25577.41 25259.88 14578.76 13185.14 121
mvs_anonymous68.03 16267.51 15169.59 20772.08 27244.57 26571.99 24575.23 21851.67 23467.06 16082.57 17054.68 4877.94 24356.56 16275.71 16486.26 80
F-COLMAP63.05 23660.87 24969.58 20976.99 19953.63 14078.12 12976.16 20347.97 27852.41 32681.61 19627.87 31978.11 24140.07 29566.66 27377.00 274
MSDG61.81 24859.23 25469.55 21072.64 26252.63 16070.45 26775.81 20851.38 24153.70 31876.11 28229.52 30681.08 19337.70 30765.79 28074.93 294
Anonymous20240521166.84 18965.99 18869.40 21180.19 11342.21 28571.11 25971.31 26058.80 12267.90 14086.39 9329.83 30579.65 21549.60 22378.78 13086.33 74
tt080567.77 16967.24 16569.34 21274.87 23040.08 29977.36 14481.37 10555.31 19066.33 17584.65 12737.35 23582.55 16455.65 17272.28 20885.39 115
GBi-Net67.21 17766.55 17269.19 21377.63 17843.33 27477.31 14577.83 18056.62 16165.04 20582.70 16541.85 19080.33 20947.18 24072.76 19883.92 156
test167.21 17766.55 17269.19 21377.63 17843.33 27477.31 14577.83 18056.62 16165.04 20582.70 16541.85 19080.33 20947.18 24072.76 19883.92 156
FMVSNet166.70 19265.87 18969.19 21377.49 18643.33 27477.31 14577.83 18056.45 16664.60 21382.70 16538.08 22980.33 20946.08 24972.31 20783.92 156
UniMVSNet_ETH3D67.60 17267.07 16969.18 21677.39 18842.29 28374.18 21175.59 21260.37 9566.77 16686.06 10137.64 23178.93 23552.16 19973.49 18586.32 76
FIs70.82 10271.43 8068.98 21778.33 15738.14 31576.96 15583.59 6361.02 8267.33 15586.73 8255.07 4281.64 17854.61 18279.22 12287.14 51
LTVRE_ROB55.42 1663.15 23561.23 24468.92 21876.57 20647.80 23059.92 32876.39 20154.35 21358.67 27782.46 17629.44 30881.49 18242.12 28571.14 21877.46 266
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
131464.61 22063.21 22168.80 21971.87 27647.46 23673.95 21578.39 17342.88 32359.97 26076.60 27738.11 22879.39 22054.84 17872.32 20679.55 246
FMVSNet266.93 18766.31 18368.79 22077.63 17842.98 27876.11 17177.47 18656.62 16165.22 20282.17 18341.85 19080.18 21247.05 24372.72 20183.20 182
COLMAP_ROBcopyleft52.97 1761.27 25458.81 25768.64 22174.63 23652.51 16478.42 12573.30 24549.92 25850.96 33181.51 19923.06 34479.40 21931.63 34365.85 27874.01 305
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
CostFormer64.04 22462.51 22868.61 22271.88 27545.77 25071.30 25470.60 26647.55 28264.31 21676.61 27641.63 19379.62 21749.74 21969.00 25580.42 232
FMVSNet366.32 19965.61 19468.46 22376.48 20842.34 28274.98 19777.15 19355.83 17965.04 20581.16 20339.91 20780.14 21347.18 24072.76 19882.90 190
WR-MVS68.47 15468.47 13268.44 22480.20 11239.84 30173.75 22276.07 20664.68 2168.11 13783.63 15050.39 9679.14 22849.78 21769.66 24586.34 72
ECVR-MVScopyleft67.72 17067.51 15168.35 22579.46 12636.29 33874.79 20166.93 29058.72 12367.19 15788.05 6436.10 24881.38 18452.07 20084.25 6787.39 43
D2MVS62.30 24260.29 25168.34 22666.46 32848.42 22465.70 29373.42 24447.71 28058.16 28275.02 29430.51 29877.71 24853.96 18671.68 21478.90 254
VNet69.68 12770.19 10368.16 22779.73 12141.63 29270.53 26577.38 18960.37 9570.69 9386.63 8651.08 8977.09 25753.61 18981.69 9785.75 98
tpm262.07 24460.10 25267.99 22872.79 26043.86 27071.05 26166.85 29143.14 32162.77 23075.39 29238.32 22580.80 20041.69 28868.88 25679.32 249
SDMVSNet68.03 16268.10 13967.84 22977.13 19348.72 22165.32 29979.10 14858.02 13865.08 20382.55 17147.83 12173.40 27763.92 11073.92 17681.41 212
pmmvs461.48 25259.39 25367.76 23071.57 27953.86 13771.42 25165.34 29944.20 31159.46 26877.92 25835.90 25074.71 27143.87 27164.87 28674.71 298
VPA-MVSNet69.02 14169.47 11567.69 23177.42 18741.00 29774.04 21279.68 13860.06 10269.26 11984.81 12451.06 9077.58 24954.44 18374.43 17184.48 140
test250665.33 21164.61 20467.50 23279.46 12634.19 34874.43 20851.92 35158.72 12366.75 16788.05 6425.99 33380.92 19751.94 20284.25 6787.39 43
FC-MVSNet-test69.80 12370.58 9767.46 23377.61 18334.73 34476.05 17483.19 7760.84 8465.88 18586.46 9154.52 5080.76 20252.52 19678.12 13786.91 55
test111167.21 17767.14 16867.42 23479.24 13234.76 34373.89 21965.65 29758.71 12566.96 16287.95 6636.09 24980.53 20452.03 20183.79 7286.97 53
ab-mvs66.65 19366.42 17767.37 23576.17 21241.73 28970.41 26876.14 20553.99 21465.98 18083.51 15549.48 10176.24 26648.60 23073.46 18784.14 149
IterMVS62.79 23761.27 24267.35 23669.37 30752.04 17371.17 25668.24 28352.63 22859.82 26376.91 27137.32 23672.36 28152.80 19563.19 30077.66 264
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
WR-MVS_H67.02 18566.92 17067.33 23777.95 17037.75 31977.57 13882.11 9262.03 7262.65 23482.48 17550.57 9479.46 21842.91 28064.01 29184.79 133
PEN-MVS66.60 19466.45 17467.04 23877.11 19536.56 33277.03 15480.42 13062.95 4962.51 23984.03 14146.69 14279.07 22944.22 26463.08 30185.51 107
SCA60.49 25658.38 26266.80 23974.14 24748.06 22863.35 30963.23 31349.13 26359.33 27272.10 31037.45 23374.27 27444.17 26562.57 30478.05 260
thres40063.31 23062.18 23366.72 24076.85 20039.62 30371.96 24769.44 27456.63 15962.61 23579.83 22837.18 23779.17 22431.84 33973.25 19181.36 215
CP-MVSNet66.49 19766.41 17866.72 24077.67 17736.33 33576.83 16079.52 14262.45 6262.54 23783.47 15746.32 14478.37 23745.47 25963.43 29885.45 110
PS-CasMVS66.42 19866.32 18266.70 24277.60 18536.30 33776.94 15679.61 14062.36 6462.43 24183.66 14945.69 14878.37 23745.35 26163.26 29985.42 113
HY-MVS56.14 1364.55 22163.89 20966.55 24374.73 23541.02 29469.96 27274.43 23049.29 26161.66 24880.92 21047.43 13076.68 26144.91 26371.69 21381.94 205
thres600view763.30 23162.27 23166.41 24477.18 19238.87 30972.35 24069.11 27856.98 15462.37 24280.96 20937.01 24479.00 23331.43 34673.05 19581.36 215
DTE-MVSNet65.58 20665.34 19766.31 24576.06 21434.79 34176.43 16579.38 14562.55 6061.66 24883.83 14645.60 15079.15 22741.64 29160.88 31585.00 126
pmmvs-eth3d58.81 26556.31 27966.30 24667.61 31952.42 16772.30 24164.76 30343.55 31754.94 30674.19 30128.95 31172.60 28043.31 27457.21 33073.88 306
pmmvs663.69 22762.82 22666.27 24770.63 28939.27 30773.13 22875.47 21452.69 22759.75 26682.30 17939.71 21077.03 25847.40 23764.35 29082.53 194
tfpn200view963.18 23462.18 23366.21 24876.85 20039.62 30371.96 24769.44 27456.63 15962.61 23579.83 22837.18 23779.17 22431.84 33973.25 19179.83 243
patch_mono-269.85 12071.09 8966.16 24979.11 13754.80 13171.97 24674.31 23353.50 22070.90 9284.17 13757.63 2963.31 32066.17 8882.02 9080.38 234
Patchmatch-RL test58.16 26955.49 28366.15 25067.92 31848.89 21860.66 32651.07 35547.86 27959.36 26962.71 35534.02 26872.27 28356.41 16359.40 32277.30 268
tpm cat159.25 26356.95 27266.15 25072.19 27146.96 24068.09 28165.76 29640.03 33957.81 28470.56 32238.32 22574.51 27238.26 30561.50 31277.00 274
ppachtmachnet_test58.06 27155.38 28466.10 25269.51 30448.99 21668.01 28266.13 29544.50 30854.05 31670.74 32132.09 29272.34 28236.68 31656.71 33476.99 276
pm-mvs165.24 21264.97 20266.04 25372.38 26839.40 30672.62 23575.63 21155.53 18762.35 24383.18 16047.45 12976.47 26349.06 22766.54 27482.24 199
CR-MVSNet59.91 25957.90 26765.96 25469.96 30052.07 17165.31 30063.15 31442.48 32559.36 26974.84 29535.83 25170.75 28945.50 25764.65 28875.06 290
1112_ss64.00 22563.36 21865.93 25579.28 13042.58 28171.35 25272.36 25346.41 29360.55 25577.89 26046.27 14673.28 27846.18 24869.97 23681.92 206
thres100view90063.28 23262.41 23065.89 25677.31 19038.66 31172.65 23369.11 27857.07 15262.45 24081.03 20737.01 24479.17 22431.84 33973.25 19179.83 243
TransMVSNet (Re)64.72 21764.33 20665.87 25775.22 22638.56 31274.66 20475.08 22658.90 12161.79 24782.63 16851.18 8778.07 24243.63 27355.87 33680.99 225
VPNet67.52 17368.11 13865.74 25879.18 13436.80 33072.17 24372.83 24962.04 7167.79 14885.83 10948.88 11176.60 26251.30 20872.97 19683.81 161
OpenMVS_ROBcopyleft52.78 1860.03 25858.14 26565.69 25970.47 29144.82 26075.33 18670.86 26445.04 30356.06 29476.00 28326.89 32879.65 21535.36 32567.29 26872.60 313
Baseline_NR-MVSNet67.05 18467.56 14765.50 26075.65 21837.70 32175.42 18574.65 22959.90 10568.14 13683.15 16149.12 10977.20 25552.23 19869.78 24181.60 209
miper_lstm_enhance62.03 24560.88 24865.49 26166.71 32546.25 24556.29 34275.70 21050.68 24961.27 25175.48 29140.21 20668.03 30256.31 16465.25 28382.18 200
IterMVS-SCA-FT62.49 23861.52 23965.40 26271.99 27450.80 18771.15 25869.63 27145.71 30160.61 25477.93 25737.45 23365.99 31355.67 17163.50 29779.42 248
thres20062.20 24361.16 24565.34 26375.38 22539.99 30069.60 27469.29 27655.64 18661.87 24676.99 26937.07 24378.96 23431.28 34773.28 19077.06 272
MS-PatchMatch62.42 24061.46 24065.31 26475.21 22752.10 17072.05 24474.05 23746.41 29357.42 28874.36 29934.35 26577.57 25045.62 25573.67 18066.26 349
ambc65.13 26563.72 34237.07 32747.66 36078.78 15654.37 31471.42 31611.24 36780.94 19545.64 25453.85 34377.38 267
tfpnnormal62.47 23961.63 23864.99 26674.81 23239.01 30871.22 25573.72 24155.22 19360.21 25680.09 22641.26 20176.98 25930.02 35268.09 26278.97 253
testdata64.66 26781.52 8652.93 15465.29 30046.09 29673.88 5687.46 7138.08 22966.26 31253.31 19278.48 13574.78 297
PatchmatchNetpermissive59.84 26058.24 26364.65 26873.05 25646.70 24269.42 27662.18 31947.55 28258.88 27571.96 31234.49 26369.16 29742.99 27963.60 29578.07 259
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
sd_testset64.46 22264.45 20564.51 26977.13 19342.25 28462.67 31272.11 25558.02 13865.08 20382.55 17141.22 20269.88 29547.32 23873.92 17681.41 212
AllTest57.08 27754.65 28864.39 27071.44 28049.03 21369.92 27367.30 28545.97 29847.16 34579.77 23017.47 35267.56 30433.65 33059.16 32376.57 278
TestCases64.39 27071.44 28049.03 21367.30 28545.97 29847.16 34579.77 23017.47 35267.56 30433.65 33059.16 32376.57 278
Test_1112_low_res62.32 24161.77 23664.00 27279.08 13839.53 30568.17 28070.17 26743.25 31959.03 27479.90 22744.08 16971.24 28743.79 27268.42 26081.25 218
baseline163.81 22663.87 21163.62 27376.29 21036.36 33371.78 24967.29 28756.05 17564.23 21882.95 16347.11 13574.41 27347.30 23961.85 30980.10 239
LCM-MVSNet-Re61.88 24761.35 24163.46 27474.58 23731.48 36061.42 31958.14 33358.71 12553.02 32579.55 23643.07 17776.80 26045.69 25377.96 13982.11 203
CMPMVSbinary42.80 2157.81 27355.97 28063.32 27560.98 35347.38 23764.66 30469.50 27332.06 35146.83 34777.80 26229.50 30771.36 28648.68 22973.75 17971.21 331
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
CL-MVSNet_self_test61.53 25060.94 24763.30 27668.95 31136.93 32967.60 28472.80 25055.67 18459.95 26176.63 27445.01 16272.22 28439.74 29962.09 30880.74 229
JIA-IIPM51.56 30847.68 32263.21 27764.61 33750.73 18847.71 35958.77 33142.90 32248.46 34251.72 36524.97 33870.24 29436.06 32253.89 34268.64 347
Vis-MVSNet (Re-imp)63.69 22763.88 21063.14 27874.75 23431.04 36171.16 25763.64 31056.32 16859.80 26484.99 12144.51 16575.46 26839.12 30180.62 10082.92 188
MDA-MVSNet-bldmvs53.87 29750.81 30963.05 27966.25 32948.58 22256.93 34063.82 30948.09 27641.22 36070.48 32530.34 30068.00 30334.24 32845.92 35872.57 314
tpmvs58.47 26656.95 27263.03 28070.20 29541.21 29367.90 28367.23 28849.62 25954.73 30970.84 32034.14 26676.24 26636.64 31761.29 31371.64 326
USDC56.35 28354.24 29462.69 28164.74 33640.31 29865.05 30273.83 24043.93 31547.58 34377.71 26515.36 35875.05 27038.19 30661.81 31072.70 312
our_test_356.49 28054.42 29062.68 28269.51 30445.48 25666.08 29161.49 32344.11 31450.73 33569.60 33233.05 27768.15 30138.38 30456.86 33174.40 300
GG-mvs-BLEND62.34 28371.36 28437.04 32869.20 27757.33 33754.73 30965.48 34930.37 29977.82 24534.82 32674.93 16972.17 322
gg-mvs-nofinetune57.86 27256.43 27862.18 28472.62 26335.35 34066.57 28756.33 34050.65 25057.64 28557.10 36130.65 29776.36 26437.38 30978.88 12774.82 296
ITE_SJBPF62.09 28566.16 33044.55 26664.32 30647.36 28555.31 30180.34 22019.27 35162.68 32336.29 32162.39 30679.04 251
EPNet_dtu61.90 24661.97 23561.68 28672.89 25939.78 30275.85 17965.62 29855.09 19654.56 31179.36 24037.59 23267.02 30739.80 29876.95 15278.25 257
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
TDRefinement53.44 30150.72 31061.60 28764.31 33946.96 24070.89 26265.27 30141.78 32644.61 35477.98 25511.52 36666.36 31128.57 35851.59 34771.49 329
PVSNet50.76 1958.40 26757.39 26861.42 28875.53 22244.04 26961.43 31863.45 31147.04 29056.91 28973.61 30427.00 32764.76 31639.12 30172.40 20375.47 287
TinyColmap54.14 29451.72 30561.40 28966.84 32441.97 28666.52 28868.51 28144.81 30442.69 35975.77 28711.66 36472.94 27931.96 33756.77 33369.27 345
PatchMatch-RL56.25 28454.55 28961.32 29077.06 19656.07 10865.57 29554.10 34844.13 31353.49 32471.27 31925.20 33766.78 30836.52 31963.66 29461.12 353
CVMVSNet59.63 26259.14 25561.08 29174.47 23938.84 31075.20 19068.74 28031.15 35258.24 28176.51 27832.39 29068.58 30049.77 21865.84 27975.81 283
RPSCF55.80 28754.22 29560.53 29265.13 33542.91 28064.30 30557.62 33636.84 34558.05 28382.28 18028.01 31856.24 35037.14 31158.61 32582.44 198
KD-MVS_2432*160053.45 29951.50 30759.30 29362.82 34337.14 32555.33 34371.79 25847.34 28655.09 30470.52 32321.91 34870.45 29135.72 32342.97 36170.31 337
miper_refine_blended53.45 29951.50 30759.30 29362.82 34337.14 32555.33 34371.79 25847.34 28655.09 30470.52 32321.91 34870.45 29135.72 32342.97 36170.31 337
Patchmtry57.16 27656.47 27759.23 29569.17 31034.58 34562.98 31063.15 31444.53 30756.83 29074.84 29535.83 25168.71 29940.03 29660.91 31474.39 301
KD-MVS_self_test55.22 29153.89 29759.21 29657.80 36127.47 37057.75 33774.32 23247.38 28450.90 33270.00 32828.45 31670.30 29340.44 29457.92 32779.87 242
EU-MVSNet55.61 28854.41 29159.19 29765.41 33433.42 35272.44 23971.91 25728.81 35451.27 32973.87 30224.76 33969.08 29843.04 27858.20 32675.06 290
ADS-MVSNet251.33 31048.76 31759.07 29866.02 33244.60 26450.90 35359.76 32836.90 34350.74 33366.18 34726.38 32963.11 32127.17 35954.76 33969.50 343
pmmvs556.47 28155.68 28258.86 29961.41 35036.71 33166.37 28962.75 31640.38 33653.70 31876.62 27534.56 26167.05 30640.02 29765.27 28272.83 311
PM-MVS52.33 30550.19 31358.75 30062.10 34745.14 25965.75 29240.38 37243.60 31653.52 32272.65 3079.16 37265.87 31450.41 21454.18 34165.24 351
FMVSNet555.86 28654.93 28658.66 30171.05 28636.35 33464.18 30762.48 31846.76 29150.66 33674.73 29725.80 33464.04 31833.11 33365.57 28175.59 286
test_vis1_n_192058.86 26459.06 25658.25 30263.76 34043.14 27767.49 28566.36 29440.22 33765.89 18471.95 31331.04 29459.75 33459.94 14464.90 28571.85 325
test-LLR58.15 27058.13 26658.22 30368.57 31344.80 26165.46 29657.92 33450.08 25655.44 29969.82 32932.62 28657.44 34249.66 22173.62 18172.41 318
test-mter56.42 28255.82 28158.22 30368.57 31344.80 26165.46 29657.92 33439.94 34055.44 29969.82 32921.92 34757.44 34249.66 22173.62 18172.41 318
MIMVSNet57.35 27457.07 27058.22 30374.21 24637.18 32462.46 31360.88 32648.88 26655.29 30275.99 28531.68 29362.04 32531.87 33872.35 20475.43 288
Anonymous2024052155.30 28954.41 29157.96 30660.92 35541.73 28971.09 26071.06 26341.18 33148.65 34173.31 30516.93 35459.25 33642.54 28264.01 29172.90 310
WTY-MVS59.75 26160.39 25057.85 30772.32 27037.83 31861.05 32464.18 30745.95 30061.91 24579.11 24447.01 13960.88 32842.50 28369.49 24774.83 295
MIMVSNet155.17 29254.31 29357.77 30870.03 29932.01 35865.68 29464.81 30249.19 26246.75 34876.00 28325.53 33664.04 31828.65 35762.13 30777.26 270
XXY-MVS60.68 25561.67 23757.70 30970.43 29238.45 31364.19 30666.47 29248.05 27763.22 22680.86 21249.28 10460.47 32945.25 26267.28 26974.19 303
test_cas_vis1_n_192056.91 27856.71 27557.51 31059.13 35845.40 25763.58 30861.29 32436.24 34667.14 15971.85 31429.89 30456.69 34657.65 15663.58 29670.46 336
tpmrst58.24 26858.70 25956.84 31166.97 32234.32 34669.57 27561.14 32547.17 28958.58 27971.60 31541.28 20060.41 33049.20 22562.84 30275.78 284
dmvs_re56.77 27956.83 27456.61 31269.23 30841.02 29458.37 33364.18 30750.59 25257.45 28771.42 31635.54 25358.94 33737.23 31067.45 26769.87 341
TESTMET0.1,155.28 29054.90 28756.42 31366.56 32643.67 27265.46 29656.27 34139.18 34253.83 31767.44 34124.21 34155.46 35348.04 23473.11 19470.13 339
PMMVS53.96 29553.26 30156.04 31462.60 34650.92 18461.17 32256.09 34232.81 35053.51 32366.84 34534.04 26759.93 33344.14 26768.18 26157.27 359
YYNet150.73 31248.96 31456.03 31561.10 35241.78 28851.94 35156.44 33940.94 33444.84 35267.80 33930.08 30255.08 35436.77 31350.71 34971.22 330
MDA-MVSNet_test_wron50.71 31348.95 31556.00 31661.17 35141.84 28751.90 35256.45 33840.96 33344.79 35367.84 33830.04 30355.07 35536.71 31550.69 35071.11 333
UnsupCasMVSNet_eth53.16 30452.47 30255.23 31759.45 35733.39 35359.43 33069.13 27745.98 29750.35 33872.32 30929.30 30958.26 34042.02 28744.30 35974.05 304
sss56.17 28556.57 27654.96 31866.93 32336.32 33657.94 33561.69 32241.67 32858.64 27875.32 29338.72 22156.25 34942.04 28666.19 27772.31 321
tpm57.34 27558.16 26454.86 31971.80 27734.77 34267.47 28656.04 34348.20 27460.10 25876.92 27037.17 23953.41 35840.76 29365.01 28476.40 280
EPMVS53.96 29553.69 29854.79 32066.12 33131.96 35962.34 31549.05 35844.42 31055.54 29771.33 31830.22 30156.70 34541.65 29062.54 30575.71 285
Anonymous2023120655.10 29355.30 28554.48 32169.81 30333.94 35062.91 31162.13 32041.08 33255.18 30375.65 28832.75 28456.59 34830.32 35167.86 26372.91 309
EGC-MVSNET42.47 32738.48 33454.46 32274.33 24348.73 22070.33 26951.10 3540.03 3840.18 38567.78 34013.28 36166.49 31018.91 37050.36 35148.15 366
test_fmvs1_n51.37 30950.35 31254.42 32352.85 36437.71 32061.16 32351.93 35028.15 35663.81 22269.73 33113.72 35953.95 35651.16 20960.65 31871.59 327
pmmvs344.92 32441.95 32953.86 32452.58 36643.55 27362.11 31646.90 36626.05 36140.63 36160.19 35711.08 36957.91 34131.83 34246.15 35760.11 354
test_fmvs151.32 31150.48 31153.81 32553.57 36337.51 32260.63 32751.16 35328.02 35863.62 22369.23 33416.41 35553.93 35751.01 21060.70 31769.99 340
UnsupCasMVSNet_bld50.07 31548.87 31653.66 32660.97 35433.67 35157.62 33864.56 30539.47 34147.38 34464.02 35327.47 32259.32 33534.69 32743.68 36067.98 348
LCM-MVSNet40.30 33135.88 33753.57 32742.24 37529.15 36545.21 36560.53 32722.23 36828.02 37050.98 3683.72 38161.78 32631.22 34838.76 36769.78 342
test_vis1_n49.89 31648.69 31853.50 32853.97 36237.38 32361.53 31747.33 36428.54 35559.62 26767.10 34413.52 36052.27 36149.07 22657.52 32870.84 334
test20.0353.87 29754.02 29653.41 32961.47 34928.11 36861.30 32059.21 32951.34 24352.09 32777.43 26633.29 27658.55 33929.76 35360.27 32073.58 307
ANet_high41.38 32937.47 33653.11 33039.73 38024.45 37656.94 33969.69 26947.65 28126.04 37252.32 36412.44 36262.38 32421.80 36710.61 38172.49 315
PVSNet_043.31 2047.46 32245.64 32552.92 33167.60 32044.65 26354.06 34754.64 34441.59 32946.15 35058.75 35830.99 29558.66 33832.18 33624.81 37455.46 361
dp51.89 30751.60 30652.77 33268.44 31632.45 35762.36 31454.57 34544.16 31249.31 34067.91 33728.87 31356.61 34733.89 32954.89 33869.24 346
test0.0.03 153.32 30253.59 29952.50 33362.81 34529.45 36459.51 32954.11 34750.08 25654.40 31374.31 30032.62 28655.92 35130.50 35063.95 29372.15 323
PatchT53.17 30353.44 30052.33 33468.29 31725.34 37558.21 33454.41 34644.46 30954.56 31169.05 33533.32 27560.94 32736.93 31261.76 31170.73 335
test_fmvs248.69 31847.49 32352.29 33548.63 37033.06 35557.76 33648.05 36225.71 36259.76 26569.60 33211.57 36552.23 36249.45 22456.86 33171.58 328
CHOSEN 280x42047.83 32046.36 32452.24 33667.37 32149.78 20438.91 37143.11 37035.00 34843.27 35863.30 35428.95 31149.19 36536.53 31860.80 31657.76 358
Patchmatch-test49.08 31748.28 31951.50 33764.40 33830.85 36245.68 36348.46 36135.60 34746.10 35172.10 31034.47 26446.37 36827.08 36160.65 31877.27 269
ADS-MVSNet48.48 31947.77 32050.63 33866.02 33229.92 36350.90 35350.87 35736.90 34350.74 33366.18 34726.38 32952.47 36027.17 35954.76 33969.50 343
testgi51.90 30652.37 30350.51 33960.39 35623.55 37858.42 33258.15 33249.03 26451.83 32879.21 24322.39 34555.59 35229.24 35662.64 30372.40 320
test_fmvs344.30 32542.55 32749.55 34042.83 37427.15 37153.03 34944.93 36722.03 36953.69 32064.94 3504.21 37949.63 36447.47 23549.82 35271.88 324
MVS-HIRNet45.52 32344.48 32648.65 34168.49 31534.05 34959.41 33144.50 36827.03 35937.96 36650.47 36926.16 33264.10 31726.74 36259.52 32147.82 368
new-patchmatchnet47.56 32147.73 32147.06 34258.81 3599.37 38648.78 35759.21 32943.28 31844.22 35568.66 33625.67 33557.20 34431.57 34549.35 35474.62 299
test_vis1_rt41.35 33039.45 33247.03 34346.65 37337.86 31747.76 35838.65 37323.10 36544.21 35651.22 36711.20 36844.08 37039.27 30053.02 34459.14 355
FPMVS42.18 32841.11 33045.39 34458.03 36041.01 29649.50 35553.81 34930.07 35333.71 36764.03 35111.69 36352.08 36314.01 37455.11 33743.09 370
LF4IMVS42.95 32642.26 32845.04 34548.30 37132.50 35654.80 34548.49 36028.03 35740.51 36270.16 3269.24 37143.89 37131.63 34349.18 35558.72 356
PMVScopyleft28.69 2236.22 33633.29 34045.02 34636.82 38235.98 33954.68 34648.74 35926.31 36021.02 37551.61 3662.88 38460.10 3329.99 38047.58 35638.99 375
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
dmvs_testset50.16 31451.90 30444.94 34766.49 32711.78 38461.01 32551.50 35251.17 24750.30 33967.44 34139.28 21460.29 33122.38 36657.49 32962.76 352
APD_test137.39 33534.94 33844.72 34848.88 36933.19 35452.95 35044.00 36919.49 37027.28 37158.59 3593.18 38352.84 35918.92 36941.17 36448.14 367
Gipumacopyleft34.77 33731.91 34143.33 34962.05 34837.87 31620.39 37667.03 28923.23 36418.41 37725.84 3774.24 37862.73 32214.71 37351.32 34829.38 376
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
mvsany_test139.38 33238.16 33543.02 35049.05 36834.28 34744.16 36725.94 38322.74 36746.57 34962.21 35623.85 34341.16 37533.01 33435.91 36953.63 362
DSMNet-mixed39.30 33438.72 33341.03 35151.22 36719.66 38145.53 36431.35 37915.83 37639.80 36467.42 34322.19 34645.13 36922.43 36552.69 34558.31 357
testf131.46 34228.89 34539.16 35241.99 37728.78 36646.45 36137.56 37414.28 37721.10 37348.96 3701.48 38747.11 36613.63 37534.56 37041.60 371
APD_test231.46 34228.89 34539.16 35241.99 37728.78 36646.45 36137.56 37414.28 37721.10 37348.96 3701.48 38747.11 36613.63 37534.56 37041.60 371
mvsany_test332.62 33930.57 34338.77 35436.16 38324.20 37738.10 37220.63 38519.14 37140.36 36357.43 3605.06 37636.63 37829.59 35528.66 37355.49 360
test_vis3_rt32.09 34030.20 34437.76 35535.36 38427.48 36940.60 37028.29 38216.69 37432.52 36840.53 3731.96 38537.40 37733.64 33242.21 36348.39 365
N_pmnet39.35 33340.28 33136.54 35663.76 3401.62 39049.37 3560.76 39034.62 34943.61 35766.38 34626.25 33142.57 37226.02 36451.77 34665.44 350
test_f31.86 34131.05 34234.28 35732.33 38621.86 37932.34 37330.46 38016.02 37539.78 36555.45 3624.80 37732.36 38030.61 34937.66 36848.64 364
new_pmnet34.13 33834.29 33933.64 35852.63 36518.23 38344.43 36633.90 37822.81 36630.89 36953.18 36310.48 37035.72 37920.77 36839.51 36546.98 369
MVEpermissive17.77 2321.41 34717.77 35232.34 35934.34 38525.44 37416.11 37724.11 38411.19 37913.22 37931.92 3751.58 38630.95 38110.47 37817.03 37740.62 374
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
PMMVS227.40 34425.91 34731.87 36039.46 3816.57 38731.17 37428.52 38123.96 36320.45 37648.94 3724.20 38037.94 37616.51 37119.97 37651.09 363
E-PMN23.77 34522.73 34926.90 36142.02 37620.67 38042.66 36835.70 37617.43 37210.28 38225.05 3786.42 37442.39 37310.28 37914.71 37817.63 377
EMVS22.97 34621.84 35026.36 36240.20 37919.53 38241.95 36934.64 37717.09 3739.73 38322.83 3797.29 37342.22 3749.18 38113.66 37917.32 378
test_method19.68 34818.10 35124.41 36313.68 3883.11 38912.06 37942.37 3712.00 38211.97 38036.38 3745.77 37529.35 38215.06 37223.65 37540.76 373
wuyk23d13.32 35012.52 35315.71 36447.54 37226.27 37231.06 3751.98 3894.93 3815.18 3841.94 3840.45 38918.54 3836.81 38312.83 3802.33 381
DeepMVS_CXcopyleft12.03 36517.97 38710.91 38510.60 3887.46 38011.07 38128.36 3763.28 38211.29 3848.01 3829.74 38313.89 379
tmp_tt9.43 35111.14 3544.30 3662.38 3894.40 38813.62 37816.08 3870.39 38315.89 37813.06 38015.80 3575.54 38512.63 37710.46 3822.95 380
test1234.73 3536.30 3560.02 3670.01 3900.01 39156.36 3410.00 3910.01 3850.04 3860.21 3860.01 3900.00 3860.03 3850.00 3840.04 382
testmvs4.52 3546.03 3570.01 3680.01 3900.00 39253.86 3480.00 3910.01 3850.04 3860.27 3850.00 3910.00 3860.04 3840.00 3840.03 383
test_blank0.00 3560.00 3590.00 3690.00 3920.00 3920.00 3800.00 3910.00 3870.00 3880.00 3870.00 3910.00 3860.00 3860.00 3840.00 384
uanet_test0.00 3560.00 3590.00 3690.00 3920.00 3920.00 3800.00 3910.00 3870.00 3880.00 3870.00 3910.00 3860.00 3860.00 3840.00 384
DCPMVS0.00 3560.00 3590.00 3690.00 3920.00 3920.00 3800.00 3910.00 3870.00 3880.00 3870.00 3910.00 3860.00 3860.00 3840.00 384
cdsmvs_eth3d_5k17.50 34923.34 3480.00 3690.00 3920.00 3920.00 38078.63 1600.00 3870.00 38882.18 18149.25 1050.00 3860.00 3860.00 3840.00 384
pcd_1.5k_mvsjas3.92 3555.23 3580.00 3690.00 3920.00 3920.00 3800.00 3910.00 3870.00 3880.00 38747.05 1360.00 3860.00 3860.00 3840.00 384
sosnet-low-res0.00 3560.00 3590.00 3690.00 3920.00 3920.00 3800.00 3910.00 3870.00 3880.00 3870.00 3910.00 3860.00 3860.00 3840.00 384
sosnet0.00 3560.00 3590.00 3690.00 3920.00 3920.00 3800.00 3910.00 3870.00 3880.00 3870.00 3910.00 3860.00 3860.00 3840.00 384
uncertanet0.00 3560.00 3590.00 3690.00 3920.00 3920.00 3800.00 3910.00 3870.00 3880.00 3870.00 3910.00 3860.00 3860.00 3840.00 384
Regformer0.00 3560.00 3590.00 3690.00 3920.00 3920.00 3800.00 3910.00 3870.00 3880.00 3870.00 3910.00 3860.00 3860.00 3840.00 384
ab-mvs-re6.49 3528.65 3550.00 3690.00 3920.00 3920.00 3800.00 3910.00 3870.00 38877.89 2600.00 3910.00 3860.00 3860.00 3840.00 384
uanet0.00 3560.00 3590.00 3690.00 3920.00 3920.00 3800.00 3910.00 3870.00 3880.00 3870.00 3910.00 3860.00 3860.00 3840.00 384
FOURS186.12 3660.82 3788.18 183.61 6260.87 8381.50 16
PC_three_145255.09 19684.46 489.84 4266.68 589.41 1774.24 3491.38 288.42 10
test_one_060187.58 959.30 5686.84 765.01 1983.80 1191.86 664.03 11
eth-test20.00 392
eth-test0.00 392
ZD-MVS86.64 2160.38 4382.70 8557.95 14178.10 2490.06 3556.12 3788.84 2574.05 3787.00 47
RE-MVS-def73.71 6283.49 6559.87 4884.29 3681.36 10658.07 13673.14 6790.07 3343.06 17868.20 6981.76 9384.03 151
IU-MVS87.77 459.15 5985.53 2553.93 21584.64 379.07 1090.87 588.37 12
test_241102_TWO86.73 1264.18 3184.26 591.84 865.19 690.83 578.63 1690.70 787.65 34
test_241102_ONE87.77 458.90 6886.78 1064.20 3085.97 191.34 1266.87 390.78 7
9.1478.75 1483.10 6984.15 4288.26 159.90 10578.57 2390.36 2657.51 3086.86 6377.39 1989.52 21
save fliter86.17 3361.30 2883.98 4679.66 13959.00 119
test_0728_THIRD65.04 1583.82 892.00 364.69 1090.75 879.48 590.63 1088.09 20
test072687.75 759.07 6387.86 486.83 864.26 2884.19 791.92 564.82 8
GSMVS78.05 260
test_part287.58 960.47 4283.42 12
sam_mvs134.74 26078.05 260
sam_mvs33.43 274
MTGPAbinary80.97 122
test_post168.67 2793.64 38232.39 29069.49 29644.17 265
test_post3.55 38333.90 26966.52 309
patchmatchnet-post64.03 35134.50 26274.27 274
MTMP86.03 1817.08 386
gm-plane-assit71.40 28341.72 29148.85 26773.31 30582.48 16748.90 228
test9_res75.28 2988.31 3283.81 161
TEST985.58 4361.59 2481.62 8181.26 11455.65 18574.93 4088.81 5553.70 5984.68 117
test_885.40 4660.96 3481.54 8481.18 11755.86 17674.81 4388.80 5753.70 5984.45 121
agg_prior273.09 4587.93 3984.33 142
agg_prior85.04 5059.96 4681.04 12074.68 4684.04 127
test_prior462.51 1482.08 76
test_prior281.75 7960.37 9575.01 3989.06 5156.22 3672.19 4988.96 24
旧先验276.08 17245.32 30276.55 3165.56 31558.75 152
新几何276.12 170
旧先验183.04 7053.15 15167.52 28487.85 6844.08 16980.76 9978.03 263
无先验79.66 10974.30 23448.40 27280.78 20153.62 18879.03 252
原ACMM279.02 115
test22283.14 6858.68 7272.57 23763.45 31141.78 32667.56 15286.12 9837.13 24178.73 13274.98 293
testdata272.18 28546.95 244
segment_acmp54.23 52
testdata172.65 23360.50 90
plane_prior781.41 8955.96 110
plane_prior681.20 9656.24 10545.26 160
plane_prior584.01 4987.21 5268.16 7180.58 10284.65 136
plane_prior486.10 99
plane_prior356.09 10763.92 3569.27 117
plane_prior284.22 3964.52 24
plane_prior181.27 94
plane_prior56.31 10183.58 5263.19 4780.48 105
n20.00 391
nn0.00 391
door-mid47.19 365
test1183.47 66
door47.60 363
HQP5-MVS54.94 127
HQP-NCC80.66 10282.31 7062.10 6767.85 142
ACMP_Plane80.66 10282.31 7062.10 6767.85 142
BP-MVS67.04 83
HQP4-MVS67.85 14286.93 6184.32 143
HQP3-MVS83.90 5380.35 106
HQP2-MVS45.46 154
NP-MVS80.98 9956.05 10985.54 116
MDTV_nov1_ep13_2view25.89 37361.22 32140.10 33851.10 33032.97 27938.49 30378.61 255
MDTV_nov1_ep1357.00 27172.73 26138.26 31465.02 30364.73 30444.74 30555.46 29872.48 30832.61 28870.47 29037.47 30867.75 265
ACMMP++_ref74.07 175
ACMMP++72.16 209
Test By Simon48.33 116