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-MVScopyleft95.20 895.07 1195.59 598.14 3588.48 896.26 4697.28 3085.90 14397.67 398.10 288.41 2099.56 1194.66 1699.19 198.71 18
Yufeng Yin; Xiaoyan Liu; Zichao Zhang: SMA-MVS: Segmentation-Guided Multi-Scale Anchor Deformation Patch Multi-View Stereo. IEEE Transactions on Circuits and Systems for Video Technology
DPE-MVScopyleft95.57 495.67 495.25 998.36 2587.28 1695.56 8597.51 589.13 6097.14 997.91 1191.64 799.62 194.61 1799.17 298.86 10
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
SED-MVS95.91 296.28 294.80 3198.77 585.99 5097.13 1497.44 1590.31 2797.71 198.07 492.31 499.58 995.66 799.13 398.84 13
IU-MVS98.77 586.00 4896.84 6481.26 25097.26 795.50 1399.13 399.03 7
test_0728_THIRD90.75 1897.04 1198.05 892.09 699.55 1595.64 999.13 399.13 2
test_241102_TWO97.44 1590.31 2797.62 598.07 491.46 1099.58 995.66 799.12 698.98 9
DVP-MVScopyleft95.67 396.02 394.64 3798.78 385.93 5397.09 1696.73 7790.27 3097.04 1198.05 891.47 899.55 1595.62 1199.08 798.45 35
Zhenlong Yuan, Jinguo Luo, Fei Shen, Zhaoxin Li, Cong Liu, Tianlu Mao, Zhaoqi Wang: DVP-MVS: Synergize Depth-Edge and Visibility Prior for Multi-View Stereo. AAAI2025
test_0728_SECOND95.01 1698.79 286.43 3797.09 1697.49 699.61 395.62 1199.08 798.99 8
MSC_two_6792asdad96.52 197.78 5190.86 196.85 6299.61 396.03 499.06 999.07 5
No_MVS96.52 197.78 5190.86 196.85 6299.61 396.03 499.06 999.07 5
APDe-MVS95.46 595.64 594.91 2098.26 2886.29 4497.46 697.40 2089.03 6396.20 1798.10 289.39 1699.34 3395.88 699.03 1199.10 4
DVP-MVS++95.98 196.36 194.82 2997.78 5186.00 4898.29 197.49 690.75 1897.62 598.06 692.59 299.61 395.64 999.02 1298.86 10
PC_three_145282.47 21997.09 1097.07 4192.72 198.04 14992.70 4599.02 1298.86 10
OPU-MVS96.21 398.00 4290.85 397.13 1497.08 3992.59 298.94 7492.25 5398.99 1498.84 13
ACMMP_NAP94.74 1594.56 1795.28 898.02 4187.70 1095.68 7797.34 2288.28 8795.30 2497.67 1685.90 4499.54 1993.91 2498.95 1598.60 22
HPM-MVS++copyleft95.14 1094.91 1395.83 498.25 2989.65 495.92 6596.96 5191.75 894.02 3696.83 5188.12 2499.55 1593.41 3298.94 1698.28 49
MP-MVS-pluss94.21 2994.00 3694.85 2498.17 3386.65 2994.82 12697.17 3886.26 13592.83 6197.87 1385.57 4799.56 1194.37 2098.92 1798.34 41
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
SteuartSystems-ACMMP95.20 895.32 994.85 2496.99 7286.33 4097.33 797.30 2891.38 1195.39 2297.46 2088.98 1999.40 2994.12 2198.89 1898.82 15
Skip Steuart: Steuart Systems R&D Blog.
SD-MVS94.96 1295.33 893.88 5597.25 6986.69 2696.19 4997.11 4290.42 2696.95 1397.27 2889.53 1496.91 23894.38 1998.85 1998.03 69
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
CNVR-MVS95.40 795.37 795.50 798.11 3688.51 795.29 9596.96 5192.09 595.32 2397.08 3989.49 1599.33 3695.10 1498.85 1998.66 19
CP-MVS94.34 2594.21 2994.74 3598.39 2386.64 3097.60 497.24 3188.53 8092.73 6797.23 3185.20 5299.32 3792.15 5798.83 2198.25 54
ZNCC-MVS94.47 1994.28 2595.03 1598.52 1586.96 1896.85 2897.32 2688.24 8893.15 5197.04 4286.17 4199.62 192.40 4998.81 2298.52 25
MP-MVScopyleft94.25 2694.07 3494.77 3398.47 1886.31 4296.71 3196.98 4889.04 6291.98 8397.19 3485.43 4999.56 1192.06 6398.79 2398.44 36
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
PHI-MVS93.89 3893.65 4694.62 3996.84 7586.43 3796.69 3297.49 685.15 16393.56 4596.28 7485.60 4699.31 3892.45 4698.79 2398.12 63
SF-MVS94.97 1194.90 1495.20 1197.84 4787.76 996.65 3497.48 1087.76 10695.71 2097.70 1588.28 2399.35 3293.89 2598.78 2598.48 29
ACMMPR94.43 2294.28 2594.91 2098.63 986.69 2696.94 2097.32 2688.63 7693.53 4697.26 3085.04 5499.54 1992.35 5198.78 2598.50 26
HFP-MVS94.52 1894.40 2094.86 2398.61 1086.81 2396.94 2097.34 2288.63 7693.65 4197.21 3286.10 4299.49 2592.35 5198.77 2798.30 46
MVS_030494.60 1794.38 2195.23 1095.41 12887.49 1496.53 3792.75 26793.82 193.07 5597.84 1483.66 7099.59 797.61 198.76 2898.61 21
MTAPA94.42 2494.22 2895.00 1798.42 2186.95 1994.36 16096.97 4991.07 1293.14 5297.56 1784.30 6399.56 1193.43 3098.75 2998.47 32
region2R94.43 2294.27 2794.92 1998.65 886.67 2896.92 2497.23 3388.60 7893.58 4397.27 2885.22 5199.54 1992.21 5498.74 3098.56 24
test9_res91.91 6898.71 3198.07 65
DeepPCF-MVS89.96 194.20 3194.77 1592.49 10496.52 8780.00 20994.00 18497.08 4390.05 3495.65 2197.29 2789.66 1398.97 7193.95 2398.71 3198.50 26
9.1494.47 1897.79 4996.08 5697.44 1586.13 14195.10 2597.40 2388.34 2299.22 4393.25 3498.70 33
train_agg93.44 4793.08 5394.52 4297.53 5886.49 3594.07 17696.78 7081.86 23692.77 6496.20 7787.63 2999.12 5092.14 5898.69 3497.94 72
DeepC-MVS_fast89.43 294.04 3393.79 4094.80 3197.48 6186.78 2495.65 8196.89 5989.40 5292.81 6296.97 4485.37 5099.24 4290.87 8798.69 3498.38 40
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
TSAR-MVS + MP.94.85 1394.94 1294.58 4098.25 2986.33 4096.11 5596.62 8688.14 9496.10 1896.96 4589.09 1898.94 7494.48 1898.68 3698.48 29
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
agg_prior290.54 9298.68 3698.27 51
test_prior294.12 17087.67 10892.63 6996.39 7286.62 3691.50 7598.67 38
MSLP-MVS++93.72 4294.08 3392.65 9697.31 6583.43 10695.79 7197.33 2490.03 3593.58 4396.96 4584.87 5897.76 16492.19 5698.66 3996.76 121
CDPH-MVS92.83 5992.30 6594.44 4397.79 4986.11 4794.06 17896.66 8380.09 26392.77 6496.63 6386.62 3699.04 5687.40 12698.66 3998.17 59
HPM-MVScopyleft94.02 3493.88 3894.43 4598.39 2385.78 6097.25 1097.07 4486.90 12492.62 7096.80 5584.85 5999.17 4692.43 4798.65 4198.33 42
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
mPP-MVS93.99 3693.78 4194.63 3898.50 1685.90 5796.87 2696.91 5788.70 7491.83 9297.17 3683.96 6799.55 1591.44 7698.64 4298.43 37
CS-MVS-test94.02 3494.29 2493.24 6796.69 7883.24 11197.49 596.92 5692.14 492.90 5795.77 9885.02 5598.33 12193.03 3798.62 4398.13 61
MCST-MVS94.45 2094.20 3095.19 1298.46 1987.50 1395.00 11597.12 4087.13 11692.51 7396.30 7389.24 1799.34 3393.46 2998.62 4398.73 16
APD-MVScopyleft94.24 2794.07 3494.75 3498.06 3986.90 2195.88 6696.94 5485.68 14995.05 2697.18 3587.31 3399.07 5291.90 7098.61 4598.28 49
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
PGM-MVS93.96 3793.72 4394.68 3698.43 2086.22 4595.30 9397.78 187.45 11293.26 4897.33 2684.62 6199.51 2390.75 8998.57 4698.32 45
XVS94.45 2094.32 2294.85 2498.54 1386.60 3296.93 2297.19 3490.66 2392.85 5997.16 3785.02 5599.49 2591.99 6498.56 4798.47 32
X-MVStestdata88.31 16486.13 21094.85 2498.54 1386.60 3296.93 2297.19 3490.66 2392.85 5923.41 38185.02 5599.49 2591.99 6498.56 4798.47 32
DELS-MVS93.43 5093.25 5093.97 5295.42 12785.04 6893.06 22697.13 3990.74 2091.84 9095.09 12386.32 3999.21 4491.22 7898.45 4997.65 85
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
ZD-MVS98.15 3486.62 3197.07 4483.63 19294.19 3296.91 4787.57 3199.26 4191.99 6498.44 50
GST-MVS94.21 2993.97 3794.90 2298.41 2286.82 2296.54 3697.19 3488.24 8893.26 4896.83 5185.48 4899.59 791.43 7798.40 5198.30 46
HPM-MVS_fast93.40 5193.22 5193.94 5498.36 2584.83 7097.15 1396.80 6985.77 14692.47 7497.13 3882.38 8299.07 5290.51 9498.40 5197.92 75
NCCC94.81 1494.69 1695.17 1397.83 4887.46 1595.66 7996.93 5592.34 393.94 3796.58 6687.74 2799.44 2892.83 4098.40 5198.62 20
DeepC-MVS88.79 393.31 5292.99 5594.26 5096.07 10285.83 5894.89 12196.99 4789.02 6589.56 12297.37 2582.51 8199.38 3092.20 5598.30 5497.57 90
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
CSCG93.23 5593.05 5493.76 6098.04 4084.07 9096.22 4897.37 2184.15 18090.05 11895.66 10287.77 2699.15 4989.91 9798.27 5598.07 65
原ACMM192.01 12097.34 6481.05 17596.81 6878.89 27790.45 11095.92 9082.65 7998.84 8480.68 22798.26 5696.14 141
CS-MVS94.12 3294.44 1993.17 7096.55 8483.08 11997.63 396.95 5391.71 1093.50 4796.21 7685.61 4598.24 12693.64 2798.17 5798.19 57
MVS_111021_HR93.45 4693.31 4993.84 5696.99 7284.84 6993.24 21997.24 3188.76 7191.60 9795.85 9386.07 4398.66 9291.91 6898.16 5898.03 69
EC-MVSNet93.44 4793.71 4492.63 9795.21 13582.43 14097.27 996.71 8090.57 2592.88 5895.80 9683.16 7498.16 13293.68 2698.14 5997.31 97
test1294.34 4897.13 7086.15 4696.29 10291.04 10585.08 5399.01 6298.13 6097.86 78
新几何193.10 7397.30 6684.35 8695.56 15971.09 35191.26 10396.24 7582.87 7898.86 8079.19 24898.10 6196.07 147
patch_mono-293.74 4194.32 2292.01 12097.54 5778.37 24793.40 20897.19 3488.02 9694.99 2797.21 3288.35 2198.44 11294.07 2298.09 6299.23 1
dcpmvs_293.49 4594.19 3191.38 15597.69 5476.78 27994.25 16396.29 10288.33 8494.46 2896.88 4888.07 2598.64 9493.62 2898.09 6298.73 16
test_fmvsm_n_192094.71 1695.11 1093.50 6395.79 11484.62 7396.15 5297.64 289.85 3997.19 897.89 1286.28 4098.71 9197.11 298.08 6497.17 104
MSP-MVS95.42 695.56 694.98 1898.49 1786.52 3496.91 2597.47 1191.73 996.10 1896.69 5689.90 1299.30 3994.70 1598.04 6599.13 2
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
SR-MVS94.23 2894.17 3294.43 4598.21 3285.78 6096.40 4096.90 5888.20 9294.33 3097.40 2384.75 6099.03 5793.35 3397.99 6698.48 29
3Dnovator86.66 591.73 7590.82 8694.44 4394.59 16586.37 3997.18 1297.02 4689.20 5784.31 24496.66 5973.74 18999.17 4686.74 13697.96 6797.79 82
CANet93.54 4493.20 5294.55 4195.65 12085.73 6294.94 11896.69 8291.89 790.69 10895.88 9281.99 9399.54 1993.14 3697.95 6898.39 38
DPM-MVS92.58 6391.74 7195.08 1496.19 9589.31 592.66 23796.56 9183.44 19891.68 9695.04 12486.60 3898.99 6885.60 15097.92 6996.93 117
APD-MVS_3200maxsize93.78 4093.77 4293.80 5997.92 4384.19 8896.30 4296.87 6186.96 12093.92 3897.47 1983.88 6898.96 7392.71 4497.87 7098.26 53
CPTT-MVS91.99 6991.80 7092.55 10198.24 3181.98 15096.76 3096.49 9381.89 23590.24 11396.44 7178.59 12698.61 9889.68 9897.85 7197.06 109
SR-MVS-dyc-post93.82 3993.82 3993.82 5797.92 4384.57 7596.28 4496.76 7387.46 11093.75 3997.43 2184.24 6499.01 6292.73 4197.80 7297.88 76
RE-MVS-def93.68 4597.92 4384.57 7596.28 4496.76 7387.46 11093.75 3997.43 2182.94 7792.73 4197.80 7297.88 76
test22296.55 8481.70 15692.22 25395.01 19268.36 35790.20 11496.14 8280.26 10597.80 7296.05 149
3Dnovator+87.14 492.42 6691.37 7495.55 695.63 12188.73 697.07 1896.77 7290.84 1584.02 24896.62 6475.95 15399.34 3387.77 12097.68 7598.59 23
旧先验196.79 7681.81 15495.67 15196.81 5386.69 3597.66 7696.97 115
EPNet91.79 7291.02 8294.10 5190.10 31785.25 6796.03 6092.05 28792.83 287.39 16195.78 9779.39 11799.01 6288.13 11697.48 7798.05 67
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
test_fmvsmvis_n_192093.44 4793.55 4793.10 7393.67 20784.26 8795.83 6996.14 11589.00 6692.43 7597.50 1883.37 7398.72 9096.61 397.44 7896.32 134
testdata90.49 19296.40 8977.89 25995.37 17772.51 34493.63 4296.69 5682.08 9097.65 17283.08 18097.39 7995.94 151
MVS_111021_LR92.47 6592.29 6692.98 8095.99 10884.43 8493.08 22496.09 11988.20 9291.12 10495.72 10181.33 9897.76 16491.74 7197.37 8096.75 122
MVSFormer91.68 7791.30 7592.80 8793.86 19883.88 9595.96 6395.90 13584.66 17591.76 9394.91 12777.92 13497.30 20889.64 9997.11 8197.24 100
lupinMVS90.92 8890.21 9293.03 7893.86 19883.88 9592.81 23493.86 24479.84 26591.76 9394.29 15477.92 13498.04 14990.48 9597.11 8197.17 104
EIA-MVS91.95 7091.94 6891.98 12495.16 13780.01 20895.36 8896.73 7788.44 8189.34 12692.16 22983.82 6998.45 11189.35 10197.06 8397.48 93
MG-MVS91.77 7391.70 7292.00 12397.08 7180.03 20793.60 20295.18 18587.85 10490.89 10696.47 7082.06 9198.36 11685.07 15497.04 8497.62 86
test250687.21 20986.28 20690.02 21795.62 12273.64 31096.25 4771.38 38187.89 10290.45 11096.65 6055.29 34198.09 14486.03 14596.94 8598.33 42
ECVR-MVScopyleft89.09 14088.53 13790.77 18395.62 12275.89 29196.16 5084.22 36187.89 10290.20 11496.65 6063.19 30098.10 13685.90 14696.94 8598.33 42
test111189.10 13888.64 13390.48 19495.53 12574.97 29896.08 5684.89 35988.13 9590.16 11696.65 6063.29 29898.10 13686.14 14196.90 8798.39 38
jason90.80 8990.10 9692.90 8493.04 22483.53 10493.08 22494.15 23380.22 26091.41 10094.91 12776.87 14197.93 15890.28 9696.90 8797.24 100
jason: jason.
Vis-MVSNetpermissive91.75 7491.23 7793.29 6595.32 13083.78 9796.14 5395.98 12789.89 3790.45 11096.58 6675.09 16598.31 12484.75 16096.90 8797.78 83
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
114514_t89.51 12488.50 13992.54 10298.11 3681.99 14995.16 10696.36 9970.19 35485.81 19295.25 11476.70 14598.63 9682.07 20096.86 9097.00 114
Vis-MVSNet (Re-imp)89.59 12289.44 11190.03 21595.74 11675.85 29295.61 8390.80 32287.66 10987.83 15095.40 11076.79 14396.46 26578.37 25296.73 9197.80 81
API-MVS90.66 9590.07 9792.45 10696.36 9184.57 7596.06 5995.22 18482.39 22089.13 12894.27 15780.32 10398.46 10880.16 23596.71 9294.33 220
MAR-MVS90.30 10189.37 11493.07 7796.61 8184.48 8095.68 7795.67 15182.36 22287.85 14992.85 20676.63 14798.80 8680.01 23696.68 9395.91 152
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
OpenMVScopyleft83.78 1188.74 15387.29 17093.08 7592.70 23585.39 6596.57 3596.43 9578.74 28280.85 29396.07 8469.64 23999.01 6278.01 25996.65 9494.83 194
ETV-MVS92.74 6192.66 6092.97 8195.20 13684.04 9295.07 11196.51 9290.73 2192.96 5691.19 26384.06 6598.34 11991.72 7296.54 9596.54 130
QAPM89.51 12488.15 15093.59 6294.92 14984.58 7496.82 2996.70 8178.43 28783.41 26396.19 8073.18 19699.30 3977.11 26896.54 9596.89 119
IS-MVSNet91.43 7991.09 8192.46 10595.87 11381.38 16796.95 1993.69 25089.72 4689.50 12495.98 8878.57 12797.77 16383.02 18296.50 9798.22 56
DP-MVS Recon91.95 7091.28 7693.96 5398.33 2785.92 5594.66 13796.66 8382.69 21790.03 11995.82 9582.30 8599.03 5784.57 16296.48 9896.91 118
CANet_DTU90.26 10389.41 11392.81 8693.46 21383.01 12293.48 20594.47 22089.43 5187.76 15394.23 15870.54 22999.03 5784.97 15596.39 9996.38 133
UGNet89.95 11288.95 12492.95 8294.51 17183.31 11095.70 7695.23 18289.37 5387.58 15593.94 17064.00 29398.78 8783.92 17196.31 10096.74 123
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
TSAR-MVS + GP.93.66 4393.41 4894.41 4796.59 8286.78 2494.40 15393.93 24089.77 4494.21 3195.59 10587.35 3298.61 9892.72 4396.15 10197.83 80
PVSNet_Blended90.73 9290.32 9191.98 12496.12 9781.25 16992.55 24196.83 6582.04 22989.10 12992.56 21781.04 10098.85 8286.72 13895.91 10295.84 156
PS-MVSNAJ91.18 8590.92 8391.96 12695.26 13382.60 13992.09 25895.70 14986.27 13491.84 9092.46 21979.70 11298.99 6889.08 10595.86 10394.29 223
ACMMPcopyleft93.24 5492.88 5794.30 4998.09 3885.33 6696.86 2797.45 1488.33 8490.15 11797.03 4381.44 9699.51 2390.85 8895.74 10498.04 68
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
casdiffmvs_mvgpermissive92.96 5892.83 5893.35 6494.59 16583.40 10895.00 11596.34 10090.30 2992.05 8196.05 8583.43 7198.15 13392.07 6095.67 10598.49 28
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
LCM-MVSNet-Re88.30 16588.32 14688.27 26694.71 16072.41 32793.15 22090.98 31787.77 10579.25 31491.96 24178.35 13095.75 29783.04 18195.62 10696.65 125
CHOSEN 1792x268888.84 14987.69 16092.30 11496.14 9681.42 16690.01 29995.86 13974.52 32687.41 15893.94 17075.46 16298.36 11680.36 23195.53 10797.12 108
AdaColmapbinary89.89 11589.07 12192.37 11097.41 6283.03 12094.42 15295.92 13282.81 21486.34 18594.65 14273.89 18599.02 6080.69 22695.51 10895.05 182
MVS87.44 19686.10 21391.44 15392.61 23783.62 10292.63 23895.66 15367.26 35881.47 28592.15 23077.95 13398.22 12979.71 23995.48 10992.47 299
UA-Net92.83 5992.54 6293.68 6196.10 10084.71 7295.66 7996.39 9791.92 693.22 5096.49 6983.16 7498.87 7884.47 16495.47 11097.45 95
xiu_mvs_v2_base91.13 8690.89 8591.86 13494.97 14582.42 14192.24 25295.64 15686.11 14291.74 9593.14 19979.67 11598.89 7789.06 10695.46 11194.28 224
casdiffmvspermissive92.51 6492.43 6492.74 9194.41 17781.98 15094.54 14396.23 10989.57 4891.96 8596.17 8182.58 8098.01 15190.95 8595.45 11298.23 55
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
PVSNet_Blended_VisFu91.38 8090.91 8492.80 8796.39 9083.17 11494.87 12396.66 8383.29 20289.27 12794.46 14880.29 10499.17 4687.57 12495.37 11396.05 149
PAPM_NR91.22 8490.78 8792.52 10397.60 5681.46 16494.37 15996.24 10886.39 13387.41 15894.80 13582.06 9198.48 10582.80 18895.37 11397.61 87
CHOSEN 280x42085.15 25883.99 26188.65 25892.47 23878.40 24679.68 36992.76 26674.90 32381.41 28789.59 30069.85 23795.51 30479.92 23895.29 11592.03 310
TAPA-MVS84.62 688.16 16887.01 17891.62 14496.64 8080.65 18694.39 15596.21 11376.38 30686.19 18895.44 10779.75 11098.08 14662.75 35395.29 11596.13 142
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
baseline92.39 6792.29 6692.69 9594.46 17481.77 15594.14 16996.27 10489.22 5691.88 8896.00 8682.35 8397.99 15391.05 8095.27 11798.30 46
LS3D87.89 17486.32 20492.59 9996.07 10282.92 12695.23 9994.92 20075.66 31382.89 27095.98 8872.48 20599.21 4468.43 32795.23 11895.64 165
test_vis1_n_192089.39 13389.84 10488.04 27392.97 22872.64 32294.71 13496.03 12686.18 13891.94 8796.56 6861.63 30795.74 29893.42 3195.11 11995.74 161
MVS_Test91.31 8291.11 7991.93 12894.37 17880.14 20093.46 20795.80 14286.46 13191.35 10293.77 18082.21 8798.09 14487.57 12494.95 12097.55 92
test_cas_vis1_n_192088.83 15288.85 13088.78 25291.15 28476.72 28093.85 19294.93 19983.23 20592.81 6296.00 8661.17 31594.45 31891.67 7394.84 12195.17 179
PAPR90.02 10889.27 11992.29 11595.78 11580.95 17992.68 23696.22 11081.91 23386.66 17893.75 18282.23 8698.44 11279.40 24794.79 12297.48 93
test_fmvs187.34 20087.56 16386.68 30690.59 30771.80 33194.01 18294.04 23878.30 28991.97 8495.22 11556.28 33693.71 33292.89 3994.71 12394.52 207
xiu_mvs_v1_base_debu90.64 9690.05 9892.40 10793.97 19584.46 8193.32 21095.46 16685.17 16092.25 7694.03 16270.59 22598.57 10190.97 8294.67 12494.18 225
xiu_mvs_v1_base90.64 9690.05 9892.40 10793.97 19584.46 8193.32 21095.46 16685.17 16092.25 7694.03 16270.59 22598.57 10190.97 8294.67 12494.18 225
xiu_mvs_v1_base_debi90.64 9690.05 9892.40 10793.97 19584.46 8193.32 21095.46 16685.17 16092.25 7694.03 16270.59 22598.57 10190.97 8294.67 12494.18 225
gg-mvs-nofinetune81.77 29079.37 30388.99 25090.85 29977.73 26786.29 34179.63 37274.88 32483.19 26869.05 37160.34 31996.11 28175.46 28294.64 12793.11 280
BH-RMVSNet88.37 16287.48 16591.02 17395.28 13179.45 22292.89 23193.07 25985.45 15686.91 17094.84 13470.35 23097.76 16473.97 29594.59 12895.85 155
test_fmvs1_n87.03 21687.04 17786.97 29889.74 32571.86 32994.55 14294.43 22178.47 28591.95 8695.50 10651.16 35393.81 33093.02 3894.56 12995.26 176
diffmvspermissive91.37 8191.23 7791.77 14093.09 22180.27 19592.36 24695.52 16487.03 11991.40 10194.93 12680.08 10697.44 19292.13 5994.56 12997.61 87
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
BH-untuned88.60 15788.13 15190.01 21895.24 13478.50 24393.29 21594.15 23384.75 17284.46 23493.40 18775.76 15697.40 20177.59 26294.52 13194.12 229
Effi-MVS+91.59 7891.11 7993.01 7994.35 18183.39 10994.60 13995.10 18987.10 11790.57 10993.10 20181.43 9798.07 14789.29 10394.48 13297.59 89
PCF-MVS84.11 1087.74 17986.08 21492.70 9494.02 18984.43 8489.27 30995.87 13873.62 33584.43 23694.33 15178.48 12998.86 8070.27 31394.45 13394.81 195
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
EI-MVSNet-Vis-set93.01 5792.92 5693.29 6595.01 14283.51 10594.48 14595.77 14490.87 1492.52 7296.67 5884.50 6299.00 6691.99 6494.44 13497.36 96
MS-PatchMatch85.05 26084.16 25787.73 27891.42 27278.51 24291.25 27593.53 25177.50 29680.15 30291.58 25461.99 30595.51 30475.69 28094.35 13589.16 348
FE-MVS87.40 19886.02 21691.57 14794.56 16979.69 21790.27 28893.72 24980.57 25888.80 13491.62 25265.32 28598.59 10074.97 28994.33 13696.44 131
mvs_anonymous89.37 13489.32 11689.51 23893.47 21274.22 30591.65 26894.83 20782.91 21285.45 20893.79 17881.23 9996.36 27286.47 14094.09 13797.94 72
test_vis1_n86.56 23086.49 19986.78 30588.51 33472.69 31994.68 13593.78 24879.55 26990.70 10795.31 11148.75 35893.28 33893.15 3593.99 13894.38 219
MVP-Stereo85.97 24184.86 24889.32 24090.92 29582.19 14692.11 25794.19 23178.76 28178.77 31791.63 25168.38 25996.56 25775.01 28893.95 13989.20 347
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
LFMVS90.08 10689.13 12092.95 8296.71 7782.32 14596.08 5689.91 33786.79 12592.15 8096.81 5362.60 30298.34 11987.18 13093.90 14098.19 57
PVSNet78.82 1885.55 24884.65 25288.23 26994.72 15971.93 32887.12 33692.75 26778.80 28084.95 22490.53 28264.43 29196.71 24574.74 29093.86 14196.06 148
CNLPA89.07 14287.98 15492.34 11196.87 7484.78 7194.08 17593.24 25581.41 24684.46 23495.13 12275.57 16196.62 24977.21 26693.84 14295.61 168
EPNet_dtu86.49 23585.94 22188.14 27190.24 31572.82 31794.11 17192.20 28186.66 12979.42 31392.36 22373.52 19095.81 29571.26 30793.66 14395.80 159
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
GeoE90.05 10789.43 11291.90 13395.16 13780.37 19495.80 7094.65 21783.90 18587.55 15794.75 13778.18 13297.62 17781.28 21593.63 14497.71 84
EI-MVSNet-UG-set92.74 6192.62 6193.12 7294.86 15383.20 11394.40 15395.74 14790.71 2292.05 8196.60 6584.00 6698.99 6891.55 7493.63 14497.17 104
Fast-Effi-MVS+89.41 13088.64 13391.71 14294.74 15780.81 18393.54 20395.10 18983.11 20686.82 17690.67 28079.74 11197.75 16780.51 23093.55 14696.57 128
FA-MVS(test-final)89.66 11988.91 12691.93 12894.57 16880.27 19591.36 27294.74 21384.87 16889.82 12092.61 21674.72 17298.47 10783.97 17093.53 14797.04 111
131487.51 19386.57 19590.34 20392.42 24079.74 21692.63 23895.35 17978.35 28880.14 30391.62 25274.05 18297.15 22181.05 21793.53 14794.12 229
BH-w/o87.57 19187.05 17689.12 24594.90 15177.90 25892.41 24393.51 25282.89 21383.70 25591.34 25775.75 15797.07 22875.49 28193.49 14992.39 303
PMMVS85.71 24784.96 24587.95 27588.90 33277.09 27588.68 31990.06 33372.32 34586.47 17990.76 27972.15 20894.40 32081.78 20893.49 14992.36 304
PatchMatch-RL86.77 22585.54 23190.47 19795.88 11182.71 13490.54 28592.31 27879.82 26684.32 24291.57 25668.77 25496.39 26973.16 30093.48 15192.32 306
PLCcopyleft84.53 789.06 14388.03 15392.15 11897.27 6882.69 13594.29 16195.44 17179.71 26784.01 24994.18 15976.68 14698.75 8877.28 26593.41 15295.02 183
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
VNet92.24 6891.91 6993.24 6796.59 8283.43 10694.84 12596.44 9489.19 5894.08 3595.90 9177.85 13798.17 13188.90 10793.38 15398.13 61
test-LLR85.87 24385.41 23487.25 29090.95 29171.67 33389.55 30389.88 33983.41 19984.54 23187.95 32467.25 26495.11 31381.82 20693.37 15494.97 184
test-mter84.54 26783.64 26687.25 29090.95 29171.67 33389.55 30389.88 33979.17 27384.54 23187.95 32455.56 33895.11 31381.82 20693.37 15494.97 184
EPP-MVSNet91.70 7691.56 7392.13 11995.88 11180.50 19197.33 795.25 18186.15 13989.76 12195.60 10483.42 7298.32 12387.37 12893.25 15697.56 91
CDS-MVSNet89.45 12788.51 13892.29 11593.62 20883.61 10393.01 22794.68 21681.95 23187.82 15193.24 19578.69 12496.99 23380.34 23293.23 15796.28 137
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
PAPM86.68 22685.39 23590.53 18893.05 22379.33 22989.79 30294.77 21278.82 27981.95 28193.24 19576.81 14297.30 20866.94 33693.16 15894.95 190
alignmvs93.08 5692.50 6394.81 3095.62 12287.61 1295.99 6196.07 12189.77 4494.12 3394.87 12980.56 10298.66 9292.42 4893.10 15998.15 60
thisisatest051587.33 20185.99 21791.37 15693.49 21179.55 21990.63 28489.56 34480.17 26187.56 15690.86 27467.07 26898.28 12581.50 21393.02 16096.29 136
TAMVS89.21 13688.29 14791.96 12693.71 20482.62 13893.30 21494.19 23182.22 22487.78 15293.94 17078.83 12196.95 23577.70 26192.98 16196.32 134
OMC-MVS91.23 8390.62 8893.08 7596.27 9384.07 9093.52 20495.93 13186.95 12189.51 12396.13 8378.50 12898.35 11885.84 14892.90 16296.83 120
canonicalmvs93.27 5392.75 5994.85 2495.70 11987.66 1196.33 4196.41 9690.00 3694.09 3494.60 14482.33 8498.62 9792.40 4992.86 16398.27 51
TESTMET0.1,183.74 27782.85 27686.42 30989.96 32171.21 33789.55 30387.88 34977.41 29783.37 26487.31 33256.71 33493.65 33480.62 22892.85 16494.40 218
thisisatest053088.67 15487.61 16291.86 13494.87 15280.07 20394.63 13889.90 33884.00 18388.46 13993.78 17966.88 27198.46 10883.30 17892.65 16597.06 109
VDD-MVS90.74 9189.92 10393.20 6996.27 9383.02 12195.73 7493.86 24488.42 8392.53 7196.84 5062.09 30498.64 9490.95 8592.62 16697.93 74
test_yl90.69 9390.02 10192.71 9295.72 11782.41 14394.11 17195.12 18785.63 15191.49 9894.70 13874.75 16998.42 11486.13 14392.53 16797.31 97
DCV-MVSNet90.69 9390.02 10192.71 9295.72 11782.41 14394.11 17195.12 18785.63 15191.49 9894.70 13874.75 16998.42 11486.13 14392.53 16797.31 97
VDDNet89.56 12388.49 14192.76 8995.07 14182.09 14796.30 4293.19 25781.05 25591.88 8896.86 4961.16 31698.33 12188.43 11392.49 16997.84 79
DP-MVS87.25 20585.36 23792.90 8497.65 5583.24 11194.81 12792.00 28974.99 32181.92 28295.00 12572.66 20299.05 5466.92 33892.33 17096.40 132
GG-mvs-BLEND87.94 27689.73 32677.91 25787.80 32778.23 37680.58 29783.86 35159.88 32395.33 31071.20 30892.22 17190.60 336
tttt051788.61 15687.78 15991.11 16894.96 14677.81 26295.35 8989.69 34185.09 16588.05 14694.59 14566.93 26998.48 10583.27 17992.13 17297.03 112
HyFIR lowres test88.09 17086.81 18291.93 12896.00 10580.63 18790.01 29995.79 14373.42 33687.68 15492.10 23573.86 18697.96 15580.75 22591.70 17397.19 103
sss88.93 14788.26 14990.94 17994.05 18880.78 18491.71 26595.38 17581.55 24488.63 13693.91 17475.04 16695.47 30882.47 19291.61 17496.57 128
cascas86.43 23684.98 24490.80 18292.10 24980.92 18090.24 29295.91 13473.10 33983.57 26088.39 31765.15 28797.46 18984.90 15891.43 17594.03 236
Effi-MVS+-dtu88.65 15588.35 14389.54 23593.33 21576.39 28694.47 14894.36 22587.70 10785.43 21189.56 30273.45 19297.26 21485.57 15191.28 17694.97 184
thres100view90087.63 18586.71 18790.38 20196.12 9778.55 24095.03 11491.58 30187.15 11588.06 14592.29 22668.91 25298.10 13670.13 31791.10 17794.48 215
tfpn200view987.58 19086.64 19090.41 19895.99 10878.64 23894.58 14091.98 29186.94 12288.09 14291.77 24569.18 24998.10 13670.13 31791.10 17794.48 215
thres600view787.65 18286.67 18990.59 18596.08 10178.72 23694.88 12291.58 30187.06 11888.08 14492.30 22568.91 25298.10 13670.05 32091.10 17794.96 187
thres40087.62 18786.64 19090.57 18695.99 10878.64 23894.58 14091.98 29186.94 12288.09 14291.77 24569.18 24998.10 13670.13 31791.10 17794.96 187
F-COLMAP87.95 17386.80 18391.40 15496.35 9280.88 18194.73 13295.45 16979.65 26882.04 28094.61 14371.13 21698.50 10476.24 27791.05 18194.80 196
thres20087.21 20986.24 20890.12 21195.36 12978.53 24193.26 21792.10 28586.42 13288.00 14791.11 26969.24 24898.00 15269.58 32191.04 18293.83 246
WTY-MVS89.60 12188.92 12591.67 14395.47 12681.15 17392.38 24594.78 21183.11 20689.06 13194.32 15278.67 12596.61 25281.57 21290.89 18397.24 100
HY-MVS83.01 1289.03 14487.94 15692.29 11594.86 15382.77 12892.08 25994.49 21981.52 24586.93 16892.79 21278.32 13198.23 12779.93 23790.55 18495.88 154
CLD-MVS89.47 12688.90 12791.18 16394.22 18382.07 14892.13 25696.09 11987.90 10085.37 21792.45 22074.38 17597.56 18087.15 13190.43 18593.93 238
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
CVMVSNet84.69 26684.79 25084.37 32791.84 25664.92 36393.70 19991.47 30666.19 36086.16 18995.28 11267.18 26693.33 33780.89 22390.42 18694.88 192
SCA86.32 23785.18 24089.73 23092.15 24576.60 28291.12 27791.69 29883.53 19685.50 20488.81 31066.79 27296.48 26276.65 27190.35 18796.12 143
Fast-Effi-MVS+-dtu87.44 19686.72 18689.63 23392.04 25077.68 26894.03 18093.94 23985.81 14482.42 27491.32 26070.33 23197.06 22980.33 23390.23 18894.14 228
OPM-MVS90.12 10589.56 10891.82 13793.14 21983.90 9494.16 16895.74 14788.96 6787.86 14895.43 10972.48 20597.91 15988.10 11890.18 18993.65 259
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
HQP_MVS90.60 9990.19 9391.82 13794.70 16182.73 13295.85 6796.22 11090.81 1686.91 17094.86 13074.23 17798.12 13488.15 11489.99 19094.63 199
plane_prior596.22 11098.12 13488.15 11489.99 19094.63 199
XVG-OURS89.40 13288.70 13191.52 14894.06 18781.46 16491.27 27496.07 12186.14 14088.89 13395.77 9868.73 25597.26 21487.39 12789.96 19295.83 157
baseline286.50 23385.39 23589.84 22391.12 28576.70 28191.88 26088.58 34782.35 22379.95 30790.95 27373.42 19397.63 17680.27 23489.95 19395.19 178
Anonymous20240521187.68 18086.13 21092.31 11396.66 7980.74 18594.87 12391.49 30580.47 25989.46 12595.44 10754.72 34398.23 12782.19 19889.89 19497.97 71
plane_prior82.73 13295.21 10189.66 4789.88 195
SDMVSNet90.19 10489.61 10791.93 12896.00 10583.09 11892.89 23195.98 12788.73 7286.85 17495.20 11872.09 20997.08 22688.90 10789.85 19695.63 166
sd_testset88.59 15887.85 15890.83 18096.00 10580.42 19392.35 24794.71 21488.73 7286.85 17495.20 11867.31 26296.43 26779.64 24189.85 19695.63 166
TR-MVS86.78 22285.76 22889.82 22494.37 17878.41 24592.47 24292.83 26481.11 25486.36 18492.40 22168.73 25597.48 18773.75 29889.85 19693.57 261
HQP3-MVS96.04 12489.77 199
HQP-MVS89.80 11789.28 11891.34 15794.17 18481.56 15894.39 15596.04 12488.81 6885.43 21193.97 16973.83 18797.96 15587.11 13389.77 19994.50 212
XVG-OURS-SEG-HR89.95 11289.45 11091.47 15294.00 19381.21 17291.87 26196.06 12385.78 14588.55 13795.73 10074.67 17397.27 21288.71 11089.64 20195.91 152
GA-MVS86.61 22785.27 23990.66 18491.33 27778.71 23790.40 28793.81 24785.34 15885.12 22189.57 30161.25 31297.11 22580.99 22189.59 20296.15 140
1112_ss88.42 16087.33 16991.72 14194.92 14980.98 17792.97 22994.54 21878.16 29383.82 25293.88 17578.78 12397.91 15979.45 24389.41 20396.26 138
ab-mvs89.41 13088.35 14392.60 9895.15 13982.65 13792.20 25495.60 15883.97 18488.55 13793.70 18374.16 18198.21 13082.46 19389.37 20496.94 116
CR-MVSNet85.35 25383.76 26490.12 21190.58 30879.34 22685.24 34991.96 29378.27 29085.55 19887.87 32771.03 21895.61 30073.96 29689.36 20595.40 172
RPMNet83.95 27481.53 28391.21 16190.58 30879.34 22685.24 34996.76 7371.44 34985.55 19882.97 35770.87 22198.91 7661.01 35789.36 20595.40 172
DSMNet-mixed76.94 32476.29 32378.89 34383.10 36556.11 37887.78 32879.77 37160.65 36675.64 33688.71 31361.56 30988.34 36660.07 36089.29 20792.21 309
LPG-MVS_test89.45 12788.90 12791.12 16594.47 17281.49 16295.30 9396.14 11586.73 12785.45 20895.16 12069.89 23598.10 13687.70 12289.23 20893.77 252
LGP-MVS_train91.12 16594.47 17281.49 16296.14 11586.73 12785.45 20895.16 12069.89 23598.10 13687.70 12289.23 20893.77 252
Test_1112_low_res87.65 18286.51 19791.08 16994.94 14879.28 23091.77 26394.30 22776.04 31183.51 26192.37 22277.86 13697.73 16878.69 25189.13 21096.22 139
PatchmatchNetpermissive85.85 24484.70 25189.29 24191.76 26075.54 29588.49 32191.30 30981.63 24285.05 22288.70 31471.71 21096.24 27674.61 29289.05 21196.08 146
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
iter_conf_final89.42 12988.69 13291.60 14595.12 14082.93 12595.75 7392.14 28487.32 11487.12 16594.07 16067.09 26797.55 18190.61 9189.01 21294.32 221
iter_conf0588.85 14888.08 15291.17 16494.27 18281.64 15795.18 10392.15 28386.23 13787.28 16294.07 16063.89 29697.55 18190.63 9089.00 21394.32 221
MDTV_nov1_ep1383.56 26791.69 26569.93 34787.75 32991.54 30378.60 28484.86 22588.90 30969.54 24096.03 28370.25 31488.93 214
MIMVSNet82.59 28480.53 28988.76 25391.51 26878.32 24886.57 34090.13 33179.32 27080.70 29588.69 31552.98 35093.07 34266.03 34188.86 21594.90 191
ACMM84.12 989.14 13788.48 14291.12 16594.65 16481.22 17195.31 9196.12 11885.31 15985.92 19194.34 15070.19 23398.06 14885.65 14988.86 21594.08 233
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
mvsmamba89.96 11189.50 10991.33 15892.90 23181.82 15396.68 3392.37 27589.03 6387.00 16694.85 13273.05 19797.65 17291.03 8188.63 21794.51 209
ACMP84.23 889.01 14688.35 14390.99 17694.73 15881.27 16895.07 11195.89 13786.48 13083.67 25694.30 15369.33 24497.99 15387.10 13588.55 21893.72 256
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
test_djsdf89.03 14488.64 13390.21 20590.74 30379.28 23095.96 6395.90 13584.66 17585.33 21992.94 20574.02 18397.30 20889.64 9988.53 21994.05 235
jajsoiax88.24 16687.50 16490.48 19490.89 29780.14 20095.31 9195.65 15584.97 16784.24 24594.02 16565.31 28697.42 19488.56 11188.52 22093.89 239
PatchT82.68 28381.27 28586.89 30290.09 31870.94 34184.06 35690.15 33074.91 32285.63 19783.57 35369.37 24294.87 31765.19 34388.50 22194.84 193
MSDG84.86 26383.09 27290.14 21093.80 20180.05 20589.18 31293.09 25878.89 27778.19 31891.91 24265.86 28497.27 21268.47 32688.45 22293.11 280
MVS-HIRNet73.70 32972.20 33278.18 34691.81 25956.42 37782.94 36282.58 36555.24 36868.88 36066.48 37255.32 34095.13 31258.12 36288.42 22383.01 363
mvs_tets88.06 17287.28 17190.38 20190.94 29379.88 21295.22 10095.66 15385.10 16484.21 24693.94 17063.53 29797.40 20188.50 11288.40 22493.87 242
ET-MVSNet_ETH3D87.51 19385.91 22292.32 11293.70 20683.93 9392.33 24990.94 31884.16 17972.09 35292.52 21869.90 23495.85 29289.20 10488.36 22597.17 104
FIs90.51 10090.35 9090.99 17693.99 19480.98 17795.73 7497.54 489.15 5986.72 17794.68 14081.83 9597.24 21685.18 15388.31 22694.76 197
PS-MVSNAJss89.97 11089.62 10691.02 17391.90 25480.85 18295.26 9895.98 12786.26 13586.21 18794.29 15479.70 11297.65 17288.87 10988.10 22794.57 204
CMPMVSbinary59.16 2180.52 30579.20 30784.48 32683.98 36267.63 35689.95 30193.84 24664.79 36266.81 36391.14 26857.93 33195.17 31176.25 27688.10 22790.65 333
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
FC-MVSNet-test90.27 10290.18 9490.53 18893.71 20479.85 21495.77 7297.59 389.31 5486.27 18694.67 14181.93 9497.01 23284.26 16688.09 22994.71 198
ACMMP++88.01 230
D2MVS85.90 24285.09 24288.35 26490.79 30077.42 27191.83 26295.70 14980.77 25780.08 30590.02 29266.74 27496.37 27081.88 20587.97 23191.26 324
UniMVSNet_ETH3D87.53 19286.37 20191.00 17592.44 23978.96 23594.74 13195.61 15784.07 18285.36 21894.52 14759.78 32497.34 20682.93 18387.88 23296.71 124
PVSNet_BlendedMVS89.98 10989.70 10590.82 18196.12 9781.25 16993.92 18996.83 6583.49 19789.10 12992.26 22781.04 10098.85 8286.72 13887.86 23392.35 305
bld_raw_dy_0_6487.60 18986.73 18590.21 20591.72 26180.26 19795.09 11088.61 34685.68 14985.55 19894.38 14963.93 29596.66 24687.73 12187.84 23493.72 256
anonymousdsp87.84 17587.09 17490.12 21189.13 32980.54 19094.67 13695.55 16082.05 22783.82 25292.12 23271.47 21497.15 22187.15 13187.80 23592.67 293
Anonymous2024052988.09 17086.59 19492.58 10096.53 8681.92 15295.99 6195.84 14074.11 33089.06 13195.21 11761.44 31098.81 8583.67 17687.47 23697.01 113
ACMMP++_ref87.47 236
XVG-ACMP-BASELINE86.00 24084.84 24989.45 23991.20 27978.00 25591.70 26695.55 16085.05 16682.97 26992.25 22854.49 34497.48 18782.93 18387.45 23892.89 288
EI-MVSNet89.10 13888.86 12989.80 22791.84 25678.30 24993.70 19995.01 19285.73 14787.15 16395.28 11279.87 10997.21 21983.81 17387.36 23993.88 241
MVSTER88.84 14988.29 14790.51 19192.95 22980.44 19293.73 19695.01 19284.66 17587.15 16393.12 20072.79 20197.21 21987.86 11987.36 23993.87 242
EG-PatchMatch MVS82.37 28680.34 29288.46 26190.27 31479.35 22592.80 23594.33 22677.14 30173.26 34990.18 28847.47 36196.72 24370.25 31487.32 24189.30 345
EPMVS83.90 27682.70 27887.51 28290.23 31672.67 32088.62 32081.96 36781.37 24785.01 22388.34 31866.31 27994.45 31875.30 28487.12 24295.43 171
tpm284.08 27182.94 27487.48 28591.39 27371.27 33589.23 31190.37 32671.95 34784.64 22889.33 30367.30 26396.55 25975.17 28587.09 24394.63 199
CostFormer85.77 24684.94 24688.26 26791.16 28372.58 32589.47 30791.04 31676.26 30986.45 18289.97 29470.74 22396.86 24182.35 19587.07 24495.34 175
Patchmatch-test81.37 29879.30 30487.58 28190.92 29574.16 30780.99 36587.68 35270.52 35376.63 33088.81 31071.21 21592.76 34460.01 36186.93 24595.83 157
RRT_MVS89.09 14088.62 13690.49 19292.85 23279.65 21896.41 3894.41 22388.22 9085.50 20494.77 13669.36 24397.31 20789.33 10286.73 24694.51 209
mvsany_test185.42 25185.30 23885.77 31687.95 34575.41 29787.61 33380.97 36976.82 30388.68 13595.83 9477.44 13890.82 35785.90 14686.51 24791.08 331
test_fmvs283.98 27284.03 25983.83 33287.16 34867.53 35793.93 18892.89 26277.62 29586.89 17393.53 18547.18 36292.02 34990.54 9286.51 24791.93 312
LTVRE_ROB82.13 1386.26 23884.90 24790.34 20394.44 17681.50 16092.31 25194.89 20183.03 20879.63 31192.67 21369.69 23897.79 16271.20 30886.26 24991.72 315
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
COLMAP_ROBcopyleft80.39 1683.96 27382.04 28089.74 22895.28 13179.75 21594.25 16392.28 27975.17 31978.02 32193.77 18058.60 32997.84 16165.06 34685.92 25091.63 317
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
RPSCF85.07 25984.27 25687.48 28592.91 23070.62 34391.69 26792.46 27376.20 31082.67 27395.22 11563.94 29497.29 21177.51 26485.80 25194.53 206
USDC82.76 28181.26 28687.26 28991.17 28174.55 30189.27 30993.39 25478.26 29175.30 33892.08 23654.43 34596.63 24871.64 30585.79 25290.61 334
dmvs_re84.20 27083.22 27187.14 29691.83 25877.81 26290.04 29890.19 32984.70 17481.49 28489.17 30564.37 29291.13 35571.58 30685.65 25392.46 300
GBi-Net87.26 20385.98 21891.08 16994.01 19083.10 11595.14 10794.94 19583.57 19384.37 23791.64 24866.59 27696.34 27378.23 25685.36 25493.79 247
test187.26 20385.98 21891.08 16994.01 19083.10 11595.14 10794.94 19583.57 19384.37 23791.64 24866.59 27696.34 27378.23 25685.36 25493.79 247
FMVSNet387.40 19886.11 21291.30 15993.79 20383.64 10194.20 16794.81 20983.89 18684.37 23791.87 24468.45 25896.56 25778.23 25685.36 25493.70 258
FMVSNet287.19 21185.82 22491.30 15994.01 19083.67 10094.79 12894.94 19583.57 19383.88 25192.05 23966.59 27696.51 26077.56 26385.01 25793.73 255
ACMH80.38 1785.36 25283.68 26590.39 19994.45 17580.63 18794.73 13294.85 20582.09 22677.24 32592.65 21460.01 32297.58 17872.25 30484.87 25892.96 285
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
ITE_SJBPF88.24 26891.88 25577.05 27692.92 26185.54 15480.13 30493.30 19257.29 33396.20 27772.46 30384.71 25991.49 319
JIA-IIPM81.04 30178.98 31187.25 29088.64 33373.48 31281.75 36489.61 34373.19 33882.05 27973.71 36866.07 28395.87 29171.18 31084.60 26092.41 302
tt080586.92 21885.74 23090.48 19492.22 24379.98 21095.63 8294.88 20383.83 18884.74 22792.80 21157.61 33297.67 16985.48 15284.42 26193.79 247
OpenMVS_ROBcopyleft74.94 1979.51 31377.03 32086.93 29987.00 34976.23 28992.33 24990.74 32368.93 35674.52 34388.23 32149.58 35696.62 24957.64 36384.29 26287.94 357
AllTest83.42 27881.39 28489.52 23695.01 14277.79 26493.12 22190.89 32077.41 29776.12 33393.34 18854.08 34697.51 18568.31 32884.27 26393.26 271
TestCases89.52 23695.01 14277.79 26490.89 32077.41 29776.12 33393.34 18854.08 34697.51 18568.31 32884.27 26393.26 271
tpm84.73 26484.02 26086.87 30390.33 31368.90 35089.06 31489.94 33680.85 25685.75 19389.86 29668.54 25795.97 28677.76 26084.05 26595.75 160
FMVSNet185.85 24484.11 25891.08 16992.81 23383.10 11595.14 10794.94 19581.64 24182.68 27291.64 24859.01 32896.34 27375.37 28383.78 26693.79 247
ADS-MVSNet281.66 29379.71 30187.50 28391.35 27574.19 30683.33 35988.48 34872.90 34182.24 27785.77 34464.98 28893.20 34064.57 34783.74 26795.12 180
ADS-MVSNet81.56 29579.78 29986.90 30191.35 27571.82 33083.33 35989.16 34572.90 34182.24 27785.77 34464.98 28893.76 33164.57 34783.74 26795.12 180
XXY-MVS87.65 18286.85 18190.03 21592.14 24680.60 18993.76 19595.23 18282.94 21184.60 22994.02 16574.27 17695.49 30781.04 21883.68 26994.01 237
test_040281.30 30079.17 30887.67 27993.19 21878.17 25292.98 22891.71 29675.25 31876.02 33590.31 28659.23 32696.37 27050.22 36983.63 27088.47 354
tpmvs83.35 28082.07 27987.20 29491.07 28771.00 34088.31 32491.70 29778.91 27680.49 29987.18 33469.30 24797.08 22668.12 33183.56 27193.51 265
pmmvs584.21 26982.84 27788.34 26588.95 33176.94 27792.41 24391.91 29575.63 31480.28 30091.18 26564.59 29095.57 30177.09 26983.47 27292.53 297
pmmvs485.43 25083.86 26390.16 20890.02 32082.97 12490.27 28892.67 27075.93 31280.73 29491.74 24771.05 21795.73 29978.85 25083.46 27391.78 314
test0.0.03 182.41 28581.69 28184.59 32588.23 34072.89 31690.24 29287.83 35083.41 19979.86 30889.78 29867.25 26488.99 36565.18 34483.42 27491.90 313
tpmrst85.35 25384.99 24386.43 30890.88 29867.88 35488.71 31891.43 30780.13 26286.08 19088.80 31273.05 19796.02 28482.48 19183.40 27595.40 172
nrg03091.08 8790.39 8993.17 7093.07 22286.91 2096.41 3896.26 10588.30 8688.37 14194.85 13282.19 8897.64 17591.09 7982.95 27694.96 187
cl2286.78 22285.98 21889.18 24492.34 24177.62 26990.84 28194.13 23581.33 24883.97 25090.15 28973.96 18496.60 25484.19 16782.94 27793.33 269
miper_ehance_all_eth87.22 20886.62 19389.02 24992.13 24777.40 27290.91 28094.81 20981.28 24984.32 24290.08 29179.26 11896.62 24983.81 17382.94 27793.04 283
miper_enhance_ethall86.90 21986.18 20989.06 24791.66 26677.58 27090.22 29494.82 20879.16 27484.48 23389.10 30679.19 11996.66 24684.06 16882.94 27792.94 286
ACMH+81.04 1485.05 26083.46 26889.82 22494.66 16379.37 22494.44 15094.12 23682.19 22578.04 32092.82 20958.23 33097.54 18373.77 29782.90 28092.54 296
VPA-MVSNet89.62 12088.96 12391.60 14593.86 19882.89 12795.46 8697.33 2487.91 9988.43 14093.31 19174.17 18097.40 20187.32 12982.86 28194.52 207
IterMVS-LS88.36 16387.91 15789.70 23193.80 20178.29 25093.73 19695.08 19185.73 14784.75 22691.90 24379.88 10896.92 23783.83 17282.51 28293.89 239
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
testgi80.94 30480.20 29583.18 33387.96 34466.29 35891.28 27390.70 32483.70 19078.12 31992.84 20751.37 35290.82 35763.34 35082.46 28392.43 301
test_vis1_rt77.96 32176.46 32182.48 33785.89 35571.74 33290.25 29078.89 37371.03 35271.30 35681.35 36042.49 36691.05 35684.55 16382.37 28484.65 360
WR-MVS88.38 16187.67 16190.52 19093.30 21680.18 19893.26 21795.96 13088.57 7985.47 20792.81 21076.12 14996.91 23881.24 21682.29 28594.47 217
tpm cat181.96 28780.27 29387.01 29791.09 28671.02 33987.38 33491.53 30466.25 35980.17 30186.35 34068.22 26096.15 28069.16 32282.29 28593.86 244
v119287.25 20586.33 20390.00 21990.76 30279.04 23493.80 19395.48 16582.57 21885.48 20691.18 26573.38 19597.42 19482.30 19682.06 28793.53 262
v114487.61 18886.79 18490.06 21491.01 28879.34 22693.95 18695.42 17483.36 20185.66 19691.31 26174.98 16797.42 19483.37 17782.06 28793.42 268
v124086.78 22285.85 22389.56 23490.45 31277.79 26493.61 20195.37 17781.65 24085.43 21191.15 26771.50 21397.43 19381.47 21482.05 28993.47 266
Anonymous2023120681.03 30279.77 30084.82 32487.85 34670.26 34591.42 27192.08 28673.67 33477.75 32289.25 30462.43 30393.08 34161.50 35682.00 29091.12 328
V4287.68 18086.86 18090.15 20990.58 30880.14 20094.24 16595.28 18083.66 19185.67 19591.33 25874.73 17197.41 19984.43 16581.83 29192.89 288
v192192086.97 21786.06 21589.69 23290.53 31178.11 25493.80 19395.43 17281.90 23485.33 21991.05 27172.66 20297.41 19982.05 20181.80 29293.53 262
v2v48287.84 17587.06 17590.17 20790.99 28979.23 23394.00 18495.13 18684.87 16885.53 20192.07 23874.45 17497.45 19084.71 16181.75 29393.85 245
Anonymous2023121186.59 22985.13 24190.98 17896.52 8781.50 16096.14 5396.16 11473.78 33383.65 25792.15 23063.26 29997.37 20582.82 18781.74 29494.06 234
v14419287.19 21186.35 20289.74 22890.64 30678.24 25193.92 18995.43 17281.93 23285.51 20391.05 27174.21 17997.45 19082.86 18581.56 29593.53 262
cl____86.52 23285.78 22588.75 25492.03 25176.46 28490.74 28294.30 22781.83 23883.34 26590.78 27875.74 15996.57 25581.74 20981.54 29693.22 275
DIV-MVS_self_test86.53 23185.78 22588.75 25492.02 25276.45 28590.74 28294.30 22781.83 23883.34 26590.82 27675.75 15796.57 25581.73 21081.52 29793.24 274
Anonymous2024052180.44 30679.21 30684.11 33085.75 35767.89 35392.86 23393.23 25675.61 31575.59 33787.47 33150.03 35494.33 32271.14 31181.21 29890.12 339
OurMVSNet-221017-085.35 25384.64 25387.49 28490.77 30172.59 32494.01 18294.40 22484.72 17379.62 31293.17 19761.91 30696.72 24381.99 20281.16 29993.16 278
FMVSNet581.52 29679.60 30287.27 28891.17 28177.95 25691.49 27092.26 28076.87 30276.16 33287.91 32651.67 35192.34 34667.74 33281.16 29991.52 318
CP-MVSNet87.63 18587.26 17388.74 25693.12 22076.59 28395.29 9596.58 8988.43 8283.49 26292.98 20475.28 16395.83 29378.97 24981.15 30193.79 247
c3_l87.14 21386.50 19889.04 24892.20 24477.26 27391.22 27694.70 21582.01 23084.34 24190.43 28478.81 12296.61 25283.70 17581.09 30293.25 273
IterMVS-SCA-FT85.45 24984.53 25588.18 27091.71 26376.87 27890.19 29592.65 27185.40 15781.44 28690.54 28166.79 27295.00 31681.04 21881.05 30392.66 294
TinyColmap79.76 31277.69 31485.97 31291.71 26373.12 31489.55 30390.36 32775.03 32072.03 35390.19 28746.22 36396.19 27963.11 35181.03 30488.59 353
UniMVSNet_NR-MVSNet89.92 11489.29 11791.81 13993.39 21483.72 9894.43 15197.12 4089.80 4086.46 18093.32 19083.16 7497.23 21784.92 15681.02 30594.49 214
DU-MVS89.34 13588.50 13991.85 13693.04 22483.72 9894.47 14896.59 8889.50 4986.46 18093.29 19377.25 13997.23 21784.92 15681.02 30594.59 202
PS-CasMVS87.32 20286.88 17988.63 25992.99 22776.33 28895.33 9096.61 8788.22 9083.30 26793.07 20273.03 19995.79 29678.36 25381.00 30793.75 254
IterMVS84.88 26283.98 26287.60 28091.44 26976.03 29090.18 29692.41 27483.24 20481.06 29290.42 28566.60 27594.28 32479.46 24280.98 30892.48 298
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
UniMVSNet (Re)89.80 11789.07 12192.01 12093.60 20984.52 7894.78 12997.47 1189.26 5586.44 18392.32 22482.10 8997.39 20484.81 15980.84 30994.12 229
LF4IMVS80.37 30779.07 31084.27 32986.64 35069.87 34889.39 30891.05 31576.38 30674.97 34090.00 29347.85 36094.25 32574.55 29380.82 31088.69 352
v1087.25 20586.38 20089.85 22291.19 28079.50 22094.48 14595.45 16983.79 18983.62 25891.19 26375.13 16497.42 19481.94 20380.60 31192.63 295
tfpnnormal84.72 26583.23 27089.20 24392.79 23480.05 20594.48 14595.81 14182.38 22181.08 29191.21 26269.01 25196.95 23561.69 35580.59 31290.58 337
WR-MVS_H87.80 17787.37 16889.10 24693.23 21778.12 25395.61 8397.30 2887.90 10083.72 25492.01 24079.65 11696.01 28576.36 27480.54 31393.16 278
VPNet88.20 16787.47 16690.39 19993.56 21079.46 22194.04 17995.54 16288.67 7586.96 16794.58 14669.33 24497.15 22184.05 16980.53 31494.56 205
v7n86.81 22085.76 22889.95 22090.72 30479.25 23295.07 11195.92 13284.45 17882.29 27590.86 27472.60 20497.53 18479.42 24680.52 31593.08 282
v887.50 19586.71 18789.89 22191.37 27479.40 22394.50 14495.38 17584.81 17183.60 25991.33 25876.05 15097.42 19482.84 18680.51 31692.84 290
EU-MVSNet81.32 29980.95 28782.42 33888.50 33663.67 36493.32 21091.33 30864.02 36380.57 29892.83 20861.21 31492.27 34776.34 27580.38 31791.32 322
Patchmtry82.71 28280.93 28888.06 27290.05 31976.37 28784.74 35491.96 29372.28 34681.32 28987.87 32771.03 21895.50 30668.97 32380.15 31892.32 306
NR-MVSNet88.58 15987.47 16691.93 12893.04 22484.16 8994.77 13096.25 10789.05 6180.04 30693.29 19379.02 12097.05 23081.71 21180.05 31994.59 202
Baseline_NR-MVSNet87.07 21486.63 19288.40 26291.44 26977.87 26094.23 16692.57 27284.12 18185.74 19492.08 23677.25 13996.04 28282.29 19779.94 32091.30 323
dp81.47 29780.23 29485.17 32289.92 32265.49 36186.74 33890.10 33276.30 30881.10 29087.12 33562.81 30195.92 28868.13 33079.88 32194.09 232
TranMVSNet+NR-MVSNet88.84 14987.95 15591.49 15092.68 23683.01 12294.92 12096.31 10189.88 3885.53 20193.85 17776.63 14796.96 23481.91 20479.87 32294.50 212
miper_lstm_enhance85.27 25684.59 25487.31 28791.28 27874.63 30087.69 33094.09 23781.20 25381.36 28889.85 29774.97 16894.30 32381.03 22079.84 32393.01 284
v14887.04 21586.32 20489.21 24290.94 29377.26 27393.71 19894.43 22184.84 17084.36 24090.80 27776.04 15197.05 23082.12 19979.60 32493.31 270
IB-MVS80.51 1585.24 25783.26 26991.19 16292.13 24779.86 21391.75 26491.29 31083.28 20380.66 29688.49 31661.28 31198.46 10880.99 22179.46 32595.25 177
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
eth_miper_zixun_eth86.50 23385.77 22788.68 25791.94 25375.81 29390.47 28694.89 20182.05 22784.05 24790.46 28375.96 15296.77 24282.76 18979.36 32693.46 267
baseline188.10 16987.28 17190.57 18694.96 14680.07 20394.27 16291.29 31086.74 12687.41 15894.00 16776.77 14496.20 27780.77 22479.31 32795.44 170
our_test_381.93 28880.46 29186.33 31088.46 33773.48 31288.46 32291.11 31276.46 30476.69 32988.25 32066.89 27094.36 32168.75 32479.08 32891.14 327
PEN-MVS86.80 22186.27 20788.40 26292.32 24275.71 29495.18 10396.38 9887.97 9782.82 27193.15 19873.39 19495.92 28876.15 27879.03 32993.59 260
pm-mvs186.61 22785.54 23189.82 22491.44 26980.18 19895.28 9794.85 20583.84 18781.66 28392.62 21572.45 20796.48 26279.67 24078.06 33092.82 291
h-mvs3390.80 8990.15 9592.75 9096.01 10482.66 13695.43 8795.53 16389.80 4093.08 5395.64 10375.77 15499.00 6692.07 6078.05 33196.60 126
SixPastTwentyTwo83.91 27582.90 27586.92 30090.99 28970.67 34293.48 20591.99 29085.54 15477.62 32492.11 23460.59 31896.87 24076.05 27977.75 33293.20 276
ppachtmachnet_test81.84 28980.07 29787.15 29588.46 33774.43 30489.04 31592.16 28275.33 31777.75 32288.99 30766.20 28095.37 30965.12 34577.60 33391.65 316
MIMVSNet179.38 31477.28 31685.69 31786.35 35173.67 30991.61 26992.75 26778.11 29472.64 35188.12 32248.16 35991.97 35160.32 35877.49 33491.43 321
DTE-MVSNet86.11 23985.48 23387.98 27491.65 26774.92 29994.93 11995.75 14687.36 11382.26 27693.04 20372.85 20095.82 29474.04 29477.46 33593.20 276
N_pmnet68.89 33468.44 33670.23 35489.07 33028.79 38888.06 32519.50 38969.47 35571.86 35484.93 34761.24 31391.75 35254.70 36677.15 33690.15 338
AUN-MVS87.78 17886.54 19691.48 15194.82 15681.05 17593.91 19193.93 24083.00 20986.93 16893.53 18569.50 24197.67 16986.14 14177.12 33795.73 163
hse-mvs289.88 11689.34 11591.51 14994.83 15581.12 17493.94 18793.91 24389.80 4093.08 5393.60 18475.77 15497.66 17192.07 6077.07 33895.74 161
dmvs_testset74.57 32875.81 32770.86 35387.72 34740.47 38487.05 33777.90 37782.75 21571.15 35785.47 34667.98 26184.12 37345.26 37176.98 33988.00 356
test20.0379.95 31079.08 30982.55 33685.79 35667.74 35591.09 27891.08 31381.23 25274.48 34489.96 29561.63 30790.15 35960.08 35976.38 34089.76 340
FPMVS64.63 33762.55 33970.88 35270.80 37756.71 37384.42 35584.42 36051.78 37149.57 37181.61 35923.49 37681.48 37640.61 37776.25 34174.46 369
test_fmvs377.67 32277.16 31979.22 34279.52 37061.14 36892.34 24891.64 30073.98 33178.86 31586.59 33627.38 37487.03 36788.12 11775.97 34289.50 342
EGC-MVSNET61.97 33856.37 34278.77 34489.63 32773.50 31189.12 31382.79 3640.21 3861.24 38784.80 34839.48 36790.04 36044.13 37275.94 34372.79 370
pmmvs683.42 27881.60 28288.87 25188.01 34377.87 26094.96 11794.24 23074.67 32578.80 31691.09 27060.17 32196.49 26177.06 27075.40 34492.23 308
new_pmnet72.15 33070.13 33478.20 34582.95 36665.68 35983.91 35782.40 36662.94 36564.47 36479.82 36242.85 36586.26 36957.41 36474.44 34582.65 365
MDA-MVSNet_test_wron79.21 31677.19 31885.29 32088.22 34172.77 31885.87 34390.06 33374.34 32762.62 36687.56 33066.14 28191.99 35066.90 33973.01 34691.10 330
YYNet179.22 31577.20 31785.28 32188.20 34272.66 32185.87 34390.05 33574.33 32862.70 36587.61 32966.09 28292.03 34866.94 33672.97 34791.15 326
Patchmatch-RL test81.67 29279.96 29886.81 30485.42 35971.23 33682.17 36387.50 35378.47 28577.19 32682.50 35870.81 22293.48 33582.66 19072.89 34895.71 164
pmmvs-eth3d80.97 30378.72 31287.74 27784.99 36179.97 21190.11 29791.65 29975.36 31673.51 34786.03 34159.45 32593.96 32975.17 28572.21 34989.29 346
PM-MVS78.11 32076.12 32484.09 33183.54 36470.08 34688.97 31685.27 35879.93 26474.73 34286.43 33834.70 37093.48 33579.43 24572.06 35088.72 351
test_f71.95 33170.87 33375.21 34974.21 37559.37 37185.07 35185.82 35565.25 36170.42 35883.13 35523.62 37582.93 37578.32 25471.94 35183.33 362
Gipumacopyleft57.99 34354.91 34567.24 35888.51 33465.59 36052.21 37790.33 32843.58 37442.84 37751.18 37820.29 38085.07 37034.77 37870.45 35251.05 377
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
APD_test169.04 33366.26 33777.36 34880.51 36862.79 36785.46 34883.51 36354.11 37059.14 36884.79 34923.40 37789.61 36155.22 36570.24 35379.68 368
K. test v381.59 29480.15 29685.91 31589.89 32369.42 34992.57 24087.71 35185.56 15373.44 34889.71 29955.58 33795.52 30377.17 26769.76 35492.78 292
KD-MVS_self_test80.20 30879.24 30583.07 33485.64 35865.29 36291.01 27993.93 24078.71 28376.32 33186.40 33959.20 32792.93 34372.59 30269.35 35591.00 332
CL-MVSNet_self_test81.74 29180.53 28985.36 31985.96 35472.45 32690.25 29093.07 25981.24 25179.85 30987.29 33370.93 22092.52 34566.95 33569.23 35691.11 329
TDRefinement79.81 31177.34 31587.22 29379.24 37175.48 29693.12 22192.03 28876.45 30575.01 33991.58 25449.19 35796.44 26670.22 31669.18 35789.75 341
MDA-MVSNet-bldmvs78.85 31776.31 32286.46 30789.76 32473.88 30888.79 31790.42 32579.16 27459.18 36788.33 31960.20 32094.04 32662.00 35468.96 35891.48 320
ambc83.06 33579.99 36963.51 36577.47 37092.86 26374.34 34584.45 35028.74 37195.06 31573.06 30168.89 35990.61 334
TransMVSNet (Re)84.43 26883.06 27388.54 26091.72 26178.44 24495.18 10392.82 26582.73 21679.67 31092.12 23273.49 19195.96 28771.10 31268.73 36091.21 325
mvsany_test374.95 32773.26 33180.02 34174.61 37363.16 36685.53 34778.42 37474.16 32974.89 34186.46 33736.02 36989.09 36482.39 19466.91 36187.82 358
PMVScopyleft47.18 2252.22 34448.46 34863.48 35945.72 38846.20 38373.41 37378.31 37541.03 37730.06 38065.68 3736.05 38783.43 37430.04 37965.86 36260.80 374
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
test_vis3_rt65.12 33662.60 33872.69 35171.44 37660.71 36987.17 33565.55 38263.80 36453.22 37065.65 37414.54 38489.44 36376.65 27165.38 36367.91 373
lessismore_v086.04 31188.46 33768.78 35180.59 37073.01 35090.11 29055.39 33996.43 26775.06 28765.06 36492.90 287
new-patchmatchnet76.41 32575.17 32880.13 34082.65 36759.61 37087.66 33191.08 31378.23 29269.85 35983.22 35454.76 34291.63 35464.14 34964.89 36589.16 348
pmmvs371.81 33268.71 33581.11 33975.86 37270.42 34486.74 33883.66 36258.95 36768.64 36280.89 36136.93 36889.52 36263.10 35263.59 36683.39 361
UnsupCasMVSNet_eth80.07 30978.27 31385.46 31885.24 36072.63 32388.45 32394.87 20482.99 21071.64 35588.07 32356.34 33591.75 35273.48 29963.36 36792.01 311
LCM-MVSNet66.00 33562.16 34077.51 34764.51 38358.29 37283.87 35890.90 31948.17 37254.69 36973.31 36916.83 38386.75 36865.47 34261.67 36887.48 359
UnsupCasMVSNet_bld76.23 32673.27 33085.09 32383.79 36372.92 31585.65 34693.47 25371.52 34868.84 36179.08 36349.77 35593.21 33966.81 34060.52 36989.13 350
testf159.54 34056.11 34369.85 35569.28 37856.61 37580.37 36776.55 37942.58 37545.68 37475.61 36411.26 38584.18 37143.20 37460.44 37068.75 371
APD_test259.54 34056.11 34369.85 35569.28 37856.61 37580.37 36776.55 37942.58 37545.68 37475.61 36411.26 38584.18 37143.20 37460.44 37068.75 371
KD-MVS_2432*160078.50 31876.02 32585.93 31386.22 35274.47 30284.80 35292.33 27679.29 27176.98 32785.92 34253.81 34893.97 32767.39 33357.42 37289.36 343
miper_refine_blended78.50 31876.02 32585.93 31386.22 35274.47 30284.80 35292.33 27679.29 27176.98 32785.92 34253.81 34893.97 32767.39 33357.42 37289.36 343
DeepMVS_CXcopyleft56.31 36274.23 37451.81 38056.67 38744.85 37348.54 37375.16 36627.87 37358.74 38340.92 37652.22 37458.39 376
PVSNet_073.20 2077.22 32374.83 32984.37 32790.70 30571.10 33883.09 36189.67 34272.81 34373.93 34683.13 35560.79 31793.70 33368.54 32550.84 37588.30 355
test_method50.52 34548.47 34756.66 36152.26 38718.98 39041.51 37981.40 36810.10 38144.59 37675.01 36728.51 37268.16 37953.54 36749.31 37682.83 364
PMMVS259.60 33956.40 34169.21 35768.83 38046.58 38273.02 37477.48 37855.07 36949.21 37272.95 37017.43 38280.04 37749.32 37044.33 37780.99 367
MVEpermissive39.65 2343.39 34638.59 35257.77 36056.52 38548.77 38155.38 37658.64 38629.33 38028.96 38152.65 3774.68 38864.62 38228.11 38033.07 37859.93 375
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
E-PMN43.23 34742.29 34946.03 36365.58 38237.41 38573.51 37264.62 38333.99 37828.47 38247.87 37919.90 38167.91 38022.23 38124.45 37932.77 378
ANet_high58.88 34254.22 34672.86 35056.50 38656.67 37480.75 36686.00 35473.09 34037.39 37864.63 37522.17 37879.49 37843.51 37323.96 38082.43 366
EMVS42.07 34841.12 35044.92 36463.45 38435.56 38773.65 37163.48 38433.05 37926.88 38345.45 38021.27 37967.14 38119.80 38223.02 38132.06 379
tmp_tt35.64 34939.24 35124.84 36514.87 38923.90 38962.71 37551.51 3886.58 38336.66 37962.08 37644.37 36430.34 38552.40 36822.00 38220.27 380
wuyk23d21.27 35120.48 35423.63 36668.59 38136.41 38649.57 3786.85 3909.37 3827.89 3844.46 3864.03 38931.37 38417.47 38316.07 3833.12 381
testmvs8.92 35211.52 3551.12 3681.06 3900.46 39286.02 3420.65 3910.62 3842.74 3859.52 3840.31 3910.45 3872.38 3840.39 3842.46 383
test1238.76 35311.22 3561.39 3670.85 3910.97 39185.76 3450.35 3920.54 3852.45 3868.14 3850.60 3900.48 3862.16 3850.17 3852.71 382
test_blank0.00 3560.00 3590.00 3690.00 3920.00 3930.00 3800.00 3930.00 3870.00 3880.00 3870.00 3920.00 3880.00 3860.00 3860.00 384
uanet_test0.00 3560.00 3590.00 3690.00 3920.00 3930.00 3800.00 3930.00 3870.00 3880.00 3870.00 3920.00 3880.00 3860.00 3860.00 384
DCPMVS0.00 3560.00 3590.00 3690.00 3920.00 3930.00 3800.00 3930.00 3870.00 3880.00 3870.00 3920.00 3880.00 3860.00 3860.00 384
cdsmvs_eth3d_5k22.14 35029.52 3530.00 3690.00 3920.00 3930.00 38095.76 1450.00 3870.00 38894.29 15475.66 1600.00 3880.00 3860.00 3860.00 384
pcd_1.5k_mvsjas6.64 3558.86 3580.00 3690.00 3920.00 3930.00 3800.00 3930.00 3870.00 3880.00 38779.70 1120.00 3880.00 3860.00 3860.00 384
sosnet-low-res0.00 3560.00 3590.00 3690.00 3920.00 3930.00 3800.00 3930.00 3870.00 3880.00 3870.00 3920.00 3880.00 3860.00 3860.00 384
sosnet0.00 3560.00 3590.00 3690.00 3920.00 3930.00 3800.00 3930.00 3870.00 3880.00 3870.00 3920.00 3880.00 3860.00 3860.00 384
uncertanet0.00 3560.00 3590.00 3690.00 3920.00 3930.00 3800.00 3930.00 3870.00 3880.00 3870.00 3920.00 3880.00 3860.00 3860.00 384
Regformer0.00 3560.00 3590.00 3690.00 3920.00 3930.00 3800.00 3930.00 3870.00 3880.00 3870.00 3920.00 3880.00 3860.00 3860.00 384
ab-mvs-re7.82 35410.43 3570.00 3690.00 3920.00 3930.00 3800.00 3930.00 3870.00 38893.88 1750.00 3920.00 3880.00 3860.00 3860.00 384
uanet0.00 3560.00 3590.00 3690.00 3920.00 3930.00 3800.00 3930.00 3870.00 3880.00 3870.00 3920.00 3880.00 3860.00 3860.00 384
FOURS198.86 185.54 6498.29 197.49 689.79 4396.29 16
test_one_060198.58 1185.83 5897.44 1591.05 1396.78 1498.06 691.45 11
eth-test20.00 392
eth-test0.00 392
test_241102_ONE98.77 585.99 5097.44 1590.26 3297.71 197.96 1092.31 499.38 30
save fliter97.85 4685.63 6395.21 10196.82 6789.44 50
test072698.78 385.93 5397.19 1197.47 1190.27 3097.64 498.13 191.47 8
GSMVS96.12 143
test_part298.55 1287.22 1796.40 15
sam_mvs171.70 21196.12 143
sam_mvs70.60 224
MTGPAbinary96.97 49
test_post188.00 3269.81 38369.31 24695.53 30276.65 271
test_post10.29 38270.57 22895.91 290
patchmatchnet-post83.76 35271.53 21296.48 262
MTMP96.16 5060.64 385
gm-plane-assit89.60 32868.00 35277.28 30088.99 30797.57 17979.44 244
TEST997.53 5886.49 3594.07 17696.78 7081.61 24392.77 6496.20 7787.71 2899.12 50
test_897.49 6086.30 4394.02 18196.76 7381.86 23692.70 6896.20 7787.63 2999.02 60
agg_prior97.38 6385.92 5596.72 7992.16 7998.97 71
test_prior485.96 5294.11 171
test_prior93.82 5797.29 6784.49 7996.88 6098.87 7898.11 64
旧先验293.36 20971.25 35094.37 2997.13 22486.74 136
新几何293.11 223
无先验93.28 21696.26 10573.95 33299.05 5480.56 22996.59 127
原ACMM292.94 230
testdata298.75 8878.30 255
segment_acmp87.16 34
testdata192.15 25587.94 98
plane_prior794.70 16182.74 131
plane_prior694.52 17082.75 12974.23 177
plane_prior494.86 130
plane_prior382.75 12990.26 3286.91 170
plane_prior295.85 6790.81 16
plane_prior194.59 165
n20.00 393
nn0.00 393
door-mid85.49 356
test1196.57 90
door85.33 357
HQP5-MVS81.56 158
HQP-NCC94.17 18494.39 15588.81 6885.43 211
ACMP_Plane94.17 18494.39 15588.81 6885.43 211
BP-MVS87.11 133
HQP4-MVS85.43 21197.96 15594.51 209
HQP2-MVS73.83 187
NP-MVS94.37 17882.42 14193.98 168
MDTV_nov1_ep13_2view55.91 37987.62 33273.32 33784.59 23070.33 23174.65 29195.50 169
Test By Simon80.02 107