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 bysorted bysort bysort bysort bysort bysort bysort bysort by
MM89.16 689.23 888.97 490.79 9973.65 1092.66 2591.17 13886.57 187.39 5494.97 2271.70 5997.68 192.19 195.63 2995.57 1
UA-Net85.08 8184.96 8185.45 8692.07 7668.07 14289.78 8790.86 14982.48 284.60 8893.20 8369.35 9095.22 8571.39 22290.88 11093.07 127
MGCNet87.69 2287.55 2788.12 1389.45 13571.76 5391.47 5489.54 19482.14 386.65 6294.28 4368.28 10997.46 690.81 695.31 3595.15 8
CANet86.45 4686.10 5887.51 3990.09 11270.94 7389.70 9092.59 7681.78 481.32 14691.43 13470.34 7697.23 1484.26 7193.36 7194.37 51
NCCC88.06 1688.01 2088.24 1194.41 2373.62 1191.22 5992.83 6281.50 585.79 6893.47 7673.02 4397.00 1984.90 6094.94 4194.10 65
EPNet83.72 10082.92 11486.14 6984.22 32069.48 9891.05 6185.27 30981.30 676.83 23791.65 12266.09 13895.56 6576.00 16993.85 6593.38 108
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CNVR-MVS88.93 1189.13 1188.33 894.77 1273.82 890.51 6793.00 4880.90 788.06 4094.06 5576.43 1796.84 2288.48 3595.99 1894.34 53
3Dnovator+77.84 485.48 7084.47 8988.51 791.08 9073.49 1693.18 1393.78 2080.79 876.66 24293.37 7960.40 22596.75 2777.20 15093.73 6795.29 6
TranMVSNet+NR-MVSNet80.84 16580.31 16282.42 22787.85 20962.33 29487.74 17791.33 13380.55 977.99 21189.86 17865.23 14792.62 21467.05 26975.24 36392.30 164
MSP-MVS89.51 489.91 588.30 1094.28 3173.46 1792.90 1894.11 880.27 1091.35 1494.16 5078.35 1396.77 2589.59 1794.22 6394.67 31
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
HPM-MVS++copyleft89.02 989.15 1088.63 595.01 976.03 192.38 2992.85 6180.26 1187.78 4594.27 4475.89 2096.81 2487.45 4496.44 993.05 130
fmvsm_s_conf0.5_n_987.39 3187.95 2185.70 7889.48 13467.88 15088.59 14289.05 22280.19 1290.70 1795.40 1574.56 2693.92 14891.54 292.07 8895.31 5
UniMVSNet_NR-MVSNet81.88 14181.54 14082.92 20688.46 18163.46 26987.13 19592.37 8380.19 1278.38 20089.14 20371.66 6193.05 20070.05 23776.46 33692.25 166
SteuartSystems-ACMMP88.72 1288.86 1288.32 992.14 7572.96 2593.73 593.67 2280.19 1288.10 3994.80 2473.76 3597.11 1587.51 4395.82 2294.90 15
Skip Steuart: Steuart Systems R&D Blog.
EI-MVSNet-Vis-set84.19 8983.81 9585.31 9088.18 19167.85 15187.66 17889.73 18880.05 1582.95 11989.59 19270.74 7394.82 10580.66 11484.72 21993.28 114
ETV-MVS84.90 8584.67 8585.59 8389.39 13968.66 12488.74 13692.64 7479.97 1684.10 9985.71 30369.32 9195.38 7980.82 10991.37 10192.72 143
fmvsm_s_conf0.5_n_886.56 4587.17 3684.73 11787.76 21765.62 20889.20 11092.21 9279.94 1789.74 2494.86 2368.63 10394.20 13390.83 591.39 10094.38 50
EI-MVSNet-UG-set83.81 9583.38 10585.09 10087.87 20867.53 16387.44 18789.66 18979.74 1882.23 13089.41 20170.24 7994.74 11179.95 11983.92 23492.99 135
fmvsm_s_conf0.5_n_386.36 5187.46 3083.09 19587.08 24865.21 21789.09 11990.21 17179.67 1989.98 2195.02 2173.17 4091.71 25791.30 391.60 9592.34 161
CS-MVS86.69 4286.95 4085.90 7590.76 10067.57 16192.83 1993.30 3479.67 1984.57 8992.27 10371.47 6295.02 9784.24 7393.46 7095.13 9
casdiffmvs_mvgpermissive85.99 5686.09 5985.70 7887.65 22267.22 17688.69 13893.04 4379.64 2185.33 7292.54 10073.30 3794.50 12183.49 7991.14 10495.37 2
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
MTAPA87.23 3487.00 3787.90 2294.18 3674.25 586.58 22092.02 10079.45 2285.88 6694.80 2468.07 11196.21 4786.69 4995.34 3393.23 115
EC-MVSNet86.01 5586.38 4984.91 10989.31 14466.27 19192.32 3293.63 2379.37 2384.17 9891.88 11469.04 9895.43 7483.93 7793.77 6693.01 133
NormalMVS86.29 5285.88 6287.52 3893.26 5372.47 3891.65 4492.19 9479.31 2484.39 9292.18 10564.64 15395.53 6880.70 11294.65 4994.56 42
SymmetryMVS85.38 7584.81 8387.07 4791.47 8472.47 3891.65 4488.06 25379.31 2484.39 9292.18 10564.64 15395.53 6880.70 11290.91 10993.21 118
XVS87.18 3586.91 4288.00 1794.42 2173.33 1992.78 2092.99 5179.14 2683.67 10994.17 4967.45 11896.60 3483.06 8394.50 5494.07 67
X-MVStestdata80.37 18877.83 22888.00 1794.42 2173.33 1992.78 2092.99 5179.14 2683.67 10912.47 47067.45 11896.60 3483.06 8394.50 5494.07 67
HQP_MVS83.64 10383.14 10885.14 9590.08 11368.71 12091.25 5792.44 7979.12 2878.92 18791.00 15160.42 22395.38 7978.71 13286.32 19091.33 199
plane_prior291.25 5779.12 28
IS-MVSNet83.15 11882.81 11584.18 14289.94 12063.30 27391.59 4888.46 24679.04 3079.49 17692.16 10765.10 14894.28 12767.71 26091.86 9394.95 12
DU-MVS81.12 16180.52 15782.90 20787.80 21263.46 26987.02 20091.87 11079.01 3178.38 20089.07 20565.02 14993.05 20070.05 23776.46 33692.20 169
NR-MVSNet80.23 19279.38 18982.78 21787.80 21263.34 27286.31 22991.09 14279.01 3172.17 33189.07 20567.20 12192.81 21266.08 27675.65 34992.20 169
SPE-MVS-test86.29 5286.48 4885.71 7791.02 9267.21 17792.36 3193.78 2078.97 3383.51 11291.20 14170.65 7595.15 8881.96 9894.89 4394.77 25
DELS-MVS85.41 7385.30 7785.77 7688.49 17967.93 14985.52 25693.44 2978.70 3483.63 11189.03 20774.57 2595.71 6380.26 11794.04 6493.66 91
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
WR-MVS79.49 20579.22 19680.27 28088.79 16958.35 34085.06 26688.61 24478.56 3577.65 21888.34 23063.81 16190.66 29964.98 28577.22 32491.80 183
plane_prior368.60 12578.44 3678.92 187
UniMVSNet (Re)81.60 14981.11 14583.09 19588.38 18564.41 24387.60 17993.02 4778.42 3778.56 19588.16 23669.78 8493.26 18269.58 24476.49 33591.60 189
DVP-MVS++90.23 191.01 187.89 2494.34 2871.25 6295.06 194.23 478.38 3892.78 495.74 682.45 397.49 489.42 1996.68 294.95 12
test_0728_THIRD78.38 3892.12 995.78 481.46 797.40 989.42 1996.57 794.67 31
testing3-275.12 30575.19 28774.91 36690.40 10645.09 44980.29 35778.42 40178.37 4076.54 24787.75 24644.36 38287.28 35357.04 35983.49 24692.37 160
test_one_060195.07 771.46 5994.14 778.27 4192.05 1195.74 680.83 11
SD-MVS88.06 1688.50 1686.71 5792.60 7272.71 2991.81 4393.19 3777.87 4290.32 2094.00 5974.83 2493.78 15587.63 4294.27 6293.65 95
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
casdiffmvspermissive85.11 8085.14 7985.01 10287.20 23965.77 20587.75 17692.83 6277.84 4384.36 9592.38 10272.15 5293.93 14781.27 10590.48 11595.33 4
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
KinetiMVS83.31 11682.61 12085.39 8887.08 24867.56 16288.06 16491.65 12177.80 4482.21 13191.79 11757.27 25094.07 13977.77 14389.89 12894.56 42
BP-MVS184.32 8883.71 9886.17 6587.84 21067.85 15189.38 10589.64 19177.73 4583.98 10292.12 11056.89 25595.43 7484.03 7691.75 9495.24 7
CP-MVSNet78.22 24078.34 21477.84 33187.83 21154.54 39787.94 16991.17 13877.65 4673.48 31388.49 22662.24 18688.43 33862.19 30874.07 37290.55 230
plane_prior68.71 12090.38 7577.62 4786.16 195
baseline84.93 8384.98 8084.80 11487.30 23765.39 21487.30 19292.88 5977.62 4784.04 10192.26 10471.81 5693.96 14181.31 10390.30 11895.03 11
VDD-MVS83.01 12382.36 12584.96 10491.02 9266.40 18888.91 12488.11 24977.57 4984.39 9293.29 8152.19 29693.91 14977.05 15388.70 15094.57 40
MP-MVScopyleft87.71 2187.64 2487.93 2194.36 2773.88 692.71 2492.65 7277.57 4983.84 10594.40 3872.24 5196.28 4485.65 5595.30 3693.62 98
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
PEN-MVS77.73 25577.69 23677.84 33187.07 25053.91 40287.91 17191.18 13777.56 5173.14 31788.82 21661.23 20789.17 32459.95 32872.37 38790.43 235
OPM-MVS83.50 10882.95 11385.14 9588.79 16970.95 7289.13 11791.52 12777.55 5280.96 15491.75 11860.71 21594.50 12179.67 12386.51 18889.97 262
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
DeepPCF-MVS80.84 188.10 1488.56 1586.73 5692.24 7469.03 10789.57 9593.39 3277.53 5389.79 2294.12 5278.98 1296.58 3685.66 5495.72 2594.58 38
PS-CasMVS78.01 24978.09 22077.77 33387.71 21954.39 39988.02 16591.22 13577.50 5473.26 31588.64 22160.73 21488.41 33961.88 31273.88 37690.53 231
MSLP-MVS++85.43 7285.76 6684.45 12591.93 7870.24 8290.71 6492.86 6077.46 5584.22 9692.81 9567.16 12292.94 20480.36 11594.35 6090.16 246
RRT-MVS82.60 13182.10 13184.10 14487.98 20462.94 28487.45 18691.27 13477.42 5679.85 17190.28 17056.62 25894.70 11479.87 12188.15 15994.67 31
DVP-MVScopyleft89.60 390.35 387.33 4295.27 571.25 6293.49 1092.73 6677.33 5792.12 995.78 480.98 997.40 989.08 2296.41 1293.33 112
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
test072695.27 571.25 6293.60 794.11 877.33 5792.81 395.79 380.98 9
balanced_conf0386.78 4086.99 3886.15 6791.24 8767.61 15990.51 6792.90 5877.26 5987.44 5391.63 12471.27 6696.06 5185.62 5695.01 3894.78 24
SED-MVS90.08 290.85 287.77 2695.30 270.98 6993.57 894.06 1277.24 6093.10 195.72 882.99 197.44 789.07 2496.63 494.88 16
test_241102_TWO94.06 1277.24 6092.78 495.72 881.26 897.44 789.07 2496.58 694.26 58
3Dnovator76.31 583.38 11282.31 12686.59 5887.94 20572.94 2890.64 6592.14 9977.21 6275.47 26892.83 9358.56 23794.72 11273.24 20192.71 7892.13 176
test_241102_ONE95.30 270.98 6994.06 1277.17 6393.10 195.39 1682.99 197.27 12
WR-MVS_H78.51 23578.49 20978.56 31588.02 20156.38 37488.43 14792.67 6977.14 6473.89 30787.55 25466.25 13489.24 32258.92 33973.55 37990.06 256
lecture88.09 1588.59 1486.58 5993.26 5369.77 9393.70 694.16 677.13 6589.76 2395.52 1472.26 5096.27 4586.87 4794.65 4993.70 90
DeepC-MVS79.81 287.08 3886.88 4387.69 3491.16 8872.32 4590.31 7693.94 1677.12 6682.82 12394.23 4772.13 5397.09 1684.83 6395.37 3293.65 95
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
FC-MVSNet-test81.52 15382.02 13480.03 28588.42 18455.97 38087.95 16893.42 3177.10 6777.38 22390.98 15369.96 8291.79 25268.46 25684.50 22292.33 162
DTE-MVSNet76.99 27176.80 25677.54 33986.24 26953.06 41187.52 18190.66 15377.08 6872.50 32588.67 22060.48 22289.52 31657.33 35670.74 39990.05 257
LFMVS81.82 14381.23 14383.57 17691.89 7963.43 27189.84 8381.85 36277.04 6983.21 11493.10 8452.26 29593.43 17571.98 21789.95 12693.85 79
UGNet80.83 16679.59 18584.54 12188.04 20068.09 14189.42 10288.16 24876.95 7076.22 25489.46 19749.30 33993.94 14468.48 25590.31 11791.60 189
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
FIs82.07 13782.42 12281.04 26288.80 16858.34 34188.26 15793.49 2876.93 7178.47 19991.04 14769.92 8392.34 23269.87 24184.97 21592.44 159
GST-MVS87.42 2987.26 3287.89 2494.12 3772.97 2492.39 2893.43 3076.89 7284.68 8293.99 6170.67 7496.82 2384.18 7595.01 3893.90 77
mPP-MVS86.67 4486.32 5087.72 3194.41 2373.55 1392.74 2292.22 9076.87 7382.81 12494.25 4666.44 13196.24 4682.88 8894.28 6193.38 108
ZNCC-MVS87.94 2087.85 2288.20 1294.39 2573.33 1993.03 1693.81 1976.81 7485.24 7394.32 4171.76 5796.93 2085.53 5795.79 2394.32 55
VPNet78.69 23078.66 20678.76 31088.31 18755.72 38484.45 28486.63 29076.79 7578.26 20390.55 16459.30 23189.70 31466.63 27177.05 32690.88 215
HFP-MVS87.58 2487.47 2987.94 1994.58 1673.54 1593.04 1493.24 3576.78 7684.91 7894.44 3670.78 7296.61 3384.53 6894.89 4393.66 91
ACMMPR87.44 2787.23 3488.08 1594.64 1373.59 1293.04 1493.20 3676.78 7684.66 8594.52 2968.81 10096.65 3184.53 6894.90 4294.00 71
ACMMPcopyleft85.89 6285.39 7387.38 4193.59 4672.63 3392.74 2293.18 4176.78 7680.73 16093.82 6864.33 15596.29 4382.67 9590.69 11293.23 115
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
region2R87.42 2987.20 3588.09 1494.63 1473.55 1393.03 1693.12 4276.73 7984.45 9094.52 2969.09 9496.70 2884.37 7094.83 4694.03 69
sasdasda85.91 6085.87 6486.04 7189.84 12269.44 10290.45 7393.00 4876.70 8088.01 4291.23 13873.28 3893.91 14981.50 10188.80 14694.77 25
canonicalmvs85.91 6085.87 6486.04 7189.84 12269.44 10290.45 7393.00 4876.70 8088.01 4291.23 13873.28 3893.91 14981.50 10188.80 14694.77 25
CP-MVS87.11 3686.92 4187.68 3594.20 3573.86 793.98 392.82 6576.62 8283.68 10894.46 3367.93 11395.95 5984.20 7494.39 5893.23 115
DeepC-MVS_fast79.65 386.91 3986.62 4787.76 2793.52 4772.37 4391.26 5693.04 4376.62 8284.22 9693.36 8071.44 6396.76 2680.82 10995.33 3494.16 61
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
MGCFI-Net85.06 8285.51 7183.70 17189.42 13663.01 27989.43 10092.62 7576.43 8487.53 5091.34 13672.82 4793.42 17681.28 10488.74 14994.66 34
TSAR-MVS + GP.85.71 6685.33 7586.84 5391.34 8572.50 3689.07 12087.28 27376.41 8585.80 6790.22 17474.15 3395.37 8281.82 9991.88 9092.65 148
HQP-NCC89.33 14189.17 11276.41 8577.23 228
ACMP_Plane89.33 14189.17 11276.41 8577.23 228
HQP-MVS82.61 12982.02 13484.37 12789.33 14166.98 18089.17 11292.19 9476.41 8577.23 22890.23 17360.17 22695.11 9177.47 14785.99 19991.03 209
CANet_DTU80.61 17779.87 17582.83 21085.60 28663.17 27887.36 18988.65 24276.37 8975.88 26188.44 22853.51 28493.07 19873.30 19989.74 13092.25 166
VNet82.21 13482.41 12381.62 24390.82 9760.93 31284.47 28189.78 18376.36 9084.07 10091.88 11464.71 15290.26 30270.68 22988.89 14493.66 91
Vis-MVSNetpermissive83.46 10982.80 11685.43 8790.25 10968.74 11890.30 7790.13 17476.33 9180.87 15792.89 9161.00 21294.20 13372.45 21490.97 10793.35 111
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
MED-MVS88.98 1089.39 787.75 2894.54 1771.43 6091.61 4694.25 376.30 9290.62 1895.03 2078.06 1497.07 1788.15 3895.96 1994.75 29
ACMMP_NAP88.05 1888.08 1987.94 1993.70 4273.05 2290.86 6293.59 2576.27 9388.14 3895.09 1971.06 6996.67 3087.67 4196.37 1494.09 66
fmvsm_s_conf0.5_n_1086.38 5086.76 4485.24 9287.33 23467.30 17189.50 9790.98 14376.25 9490.56 1994.75 2668.38 10694.24 13290.80 792.32 8594.19 60
alignmvs85.48 7085.32 7685.96 7489.51 13169.47 9989.74 8892.47 7876.17 9587.73 4991.46 13370.32 7793.78 15581.51 10088.95 14394.63 35
MVS_111021_HR85.14 7984.75 8486.32 6291.65 8272.70 3085.98 23890.33 16676.11 9682.08 13391.61 12771.36 6594.17 13681.02 10692.58 7992.08 177
HPM-MVScopyleft87.11 3686.98 3987.50 4093.88 4072.16 4792.19 3593.33 3376.07 9783.81 10693.95 6469.77 8596.01 5585.15 5894.66 4894.32 55
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
h-mvs3383.15 11882.19 12986.02 7390.56 10270.85 7688.15 16289.16 21776.02 9884.67 8391.39 13561.54 19895.50 7082.71 9275.48 35391.72 188
hse-mvs281.72 14480.94 14984.07 15088.72 17267.68 15785.87 24287.26 27576.02 9884.67 8388.22 23561.54 19893.48 17182.71 9273.44 38191.06 207
DPE-MVScopyleft89.48 589.98 488.01 1694.80 1172.69 3191.59 4894.10 1075.90 10092.29 795.66 1081.67 697.38 1187.44 4596.34 1593.95 74
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
CLD-MVS82.31 13381.65 13984.29 13488.47 18067.73 15585.81 24692.35 8475.78 10178.33 20286.58 28564.01 15894.35 12576.05 16887.48 17090.79 218
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
viewmacassd2359aftdt83.76 9883.66 10084.07 15086.59 26364.56 23586.88 20791.82 11375.72 10283.34 11392.15 10968.24 11092.88 20779.05 12589.15 14194.77 25
SF-MVS88.46 1388.74 1387.64 3692.78 6771.95 5192.40 2694.74 275.71 10389.16 2695.10 1875.65 2296.19 4887.07 4696.01 1794.79 23
testdata184.14 29475.71 103
APDe-MVScopyleft89.15 789.63 687.73 2994.49 1971.69 5493.83 493.96 1575.70 10591.06 1696.03 176.84 1597.03 1889.09 2195.65 2894.47 46
Zhaojie Zeng, Yuesong Wang, Tao Guan: Matching Ambiguity-Resilient Multi-View Stereo via Adaptive Patch Deformation. Pattern Recognition
VPA-MVSNet80.60 17980.55 15680.76 26988.07 19960.80 31586.86 20891.58 12675.67 10680.24 16789.45 19963.34 16290.25 30370.51 23179.22 30291.23 202
fmvsm_l_conf0.5_n_985.84 6386.63 4683.46 17887.12 24766.01 19588.56 14489.43 19875.59 10789.32 2594.32 4172.89 4491.21 28290.11 1192.33 8493.16 122
PGM-MVS86.68 4386.27 5287.90 2294.22 3473.38 1890.22 7893.04 4375.53 10883.86 10494.42 3767.87 11596.64 3282.70 9494.57 5393.66 91
Effi-MVS+83.62 10583.08 10985.24 9288.38 18567.45 16488.89 12589.15 21875.50 10982.27 12988.28 23269.61 8794.45 12477.81 14287.84 16393.84 81
viewcassd2359sk1183.89 9383.74 9784.34 13087.76 21764.91 23086.30 23092.22 9075.47 11083.04 11891.52 12970.15 8093.53 16879.26 12487.96 16194.57 40
fmvsm_s_conf0.5_n_485.39 7485.75 6784.30 13386.70 25965.83 20188.77 13289.78 18375.46 11188.35 3393.73 7069.19 9393.06 19991.30 388.44 15594.02 70
fmvsm_s_conf0.5_n_685.55 6986.20 5383.60 17387.32 23665.13 22088.86 12691.63 12275.41 11288.23 3793.45 7768.56 10492.47 22489.52 1892.78 7693.20 120
test_prior288.85 12875.41 11284.91 7893.54 7274.28 3183.31 8195.86 21
LPG-MVS_test82.08 13681.27 14284.50 12289.23 14968.76 11690.22 7891.94 10675.37 11476.64 24391.51 13054.29 27594.91 9978.44 13483.78 23589.83 267
LGP-MVS_train84.50 12289.23 14968.76 11691.94 10675.37 11476.64 24391.51 13054.29 27594.91 9978.44 13483.78 23589.83 267
fmvsm_l_conf0.5_n_386.02 5486.32 5085.14 9587.20 23968.54 12789.57 9590.44 16075.31 11687.49 5194.39 3972.86 4592.72 21389.04 2690.56 11494.16 61
viewdifsd2359ckpt0782.83 12682.78 11882.99 20286.51 26562.58 28785.09 26590.83 15075.22 11782.28 12891.63 12469.43 8992.03 24177.71 14486.32 19094.34 53
MG-MVS83.41 11083.45 10383.28 18592.74 6862.28 29688.17 16089.50 19675.22 11781.49 14492.74 9966.75 12595.11 9172.85 20491.58 9792.45 158
SSC-MVS3.273.35 32773.39 31173.23 38385.30 29549.01 43474.58 41881.57 36475.21 11973.68 31085.58 30952.53 28982.05 40054.33 37777.69 32088.63 310
LCM-MVSNet-Re77.05 27076.94 25377.36 34087.20 23951.60 42080.06 36080.46 37975.20 12067.69 37786.72 27562.48 18088.98 32863.44 29589.25 13791.51 193
SDMVSNet80.38 18680.18 16580.99 26389.03 15864.94 22780.45 35489.40 19975.19 12176.61 24589.98 17660.61 22087.69 34876.83 15883.55 24490.33 240
sd_testset77.70 25877.40 24378.60 31389.03 15860.02 32679.00 37585.83 30475.19 12176.61 24589.98 17654.81 26785.46 37362.63 30483.55 24490.33 240
MP-MVS-pluss87.67 2387.72 2387.54 3793.64 4572.04 5089.80 8693.50 2775.17 12386.34 6495.29 1770.86 7196.00 5688.78 3096.04 1694.58 38
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
test111179.43 20879.18 19780.15 28389.99 11853.31 40887.33 19177.05 41375.04 12480.23 16892.77 9848.97 34492.33 23368.87 25192.40 8394.81 22
Effi-MVS+-dtu80.03 19678.57 20884.42 12685.13 30168.74 11888.77 13288.10 25074.99 12574.97 29283.49 35957.27 25093.36 17773.53 19580.88 27991.18 203
reproduce-ours87.47 2587.61 2587.07 4793.27 5171.60 5591.56 5193.19 3774.98 12688.96 2795.54 1271.20 6796.54 3786.28 5193.49 6893.06 128
our_new_method87.47 2587.61 2587.07 4793.27 5171.60 5591.56 5193.19 3774.98 12688.96 2795.54 1271.20 6796.54 3786.28 5193.49 6893.06 128
fmvsm_s_conf0.5_n_783.34 11384.03 9381.28 25485.73 28265.13 22085.40 25789.90 18174.96 12882.13 13293.89 6566.65 12687.92 34486.56 5091.05 10590.80 217
OMC-MVS82.69 12781.97 13684.85 11188.75 17167.42 16587.98 16690.87 14874.92 12979.72 17391.65 12262.19 18793.96 14175.26 18086.42 18993.16 122
viewmanbaseed2359cas83.66 10183.55 10184.00 16186.81 25564.53 23686.65 21791.75 11874.89 13083.15 11791.68 12068.74 10292.83 21179.02 12689.24 13894.63 35
test250677.30 26776.49 26479.74 29190.08 11352.02 41387.86 17463.10 45674.88 13180.16 16992.79 9638.29 42092.35 23168.74 25392.50 8194.86 19
ECVR-MVScopyleft79.61 20179.26 19480.67 27190.08 11354.69 39587.89 17277.44 40974.88 13180.27 16692.79 9648.96 34592.45 22568.55 25492.50 8194.86 19
MonoMVSNet76.49 28375.80 27278.58 31481.55 38158.45 33986.36 22886.22 29774.87 13374.73 29683.73 35251.79 30888.73 33370.78 22672.15 39088.55 313
nrg03083.88 9483.53 10284.96 10486.77 25769.28 10690.46 7292.67 6974.79 13482.95 11991.33 13772.70 4893.09 19780.79 11179.28 30192.50 154
SMA-MVScopyleft89.08 889.23 888.61 694.25 3273.73 992.40 2693.63 2374.77 13592.29 795.97 274.28 3197.24 1388.58 3296.91 194.87 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
reproduce_model87.28 3387.39 3186.95 5193.10 5971.24 6691.60 4793.19 3774.69 13688.80 3095.61 1170.29 7896.44 4086.20 5393.08 7293.16 122
MVS_111021_LR82.61 12982.11 13084.11 14388.82 16371.58 5785.15 26286.16 29974.69 13680.47 16591.04 14762.29 18490.55 30080.33 11690.08 12390.20 245
EIA-MVS83.31 11682.80 11684.82 11289.59 12765.59 20988.21 15892.68 6874.66 13878.96 18586.42 29069.06 9695.26 8475.54 17690.09 12293.62 98
TSAR-MVS + MP.88.02 1988.11 1887.72 3193.68 4472.13 4891.41 5592.35 8474.62 13988.90 2993.85 6775.75 2196.00 5687.80 4094.63 5195.04 10
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
SR-MVS86.73 4186.67 4586.91 5294.11 3872.11 4992.37 3092.56 7774.50 14086.84 6194.65 2867.31 12095.77 6184.80 6492.85 7592.84 142
FOURS195.00 1072.39 4195.06 193.84 1774.49 14191.30 15
ACMP74.13 681.51 15580.57 15584.36 12889.42 13668.69 12389.97 8291.50 13174.46 14275.04 29090.41 16653.82 28194.54 11877.56 14682.91 25589.86 266
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
EPP-MVSNet83.40 11183.02 11184.57 12090.13 11164.47 24192.32 3290.73 15274.45 14379.35 18191.10 14469.05 9795.12 8972.78 20587.22 17494.13 63
fmvsm_s_conf0.5_n_284.04 9184.11 9283.81 16986.17 27265.00 22586.96 20287.28 27374.35 14488.25 3694.23 4761.82 19392.60 21689.85 1288.09 16093.84 81
fmvsm_s_conf0.1_n_283.80 9683.79 9683.83 16785.62 28564.94 22787.03 19986.62 29174.32 14587.97 4494.33 4060.67 21792.60 21689.72 1487.79 16493.96 72
save fliter93.80 4172.35 4490.47 7191.17 13874.31 146
MVS_Test83.15 11883.06 11083.41 18286.86 25263.21 27586.11 23692.00 10274.31 14682.87 12189.44 20070.03 8193.21 18677.39 14988.50 15493.81 83
myMVS_eth3d2873.62 32073.53 31073.90 37988.20 19047.41 43978.06 39079.37 39374.29 14873.98 30684.29 33844.67 37883.54 38951.47 39187.39 17190.74 222
UniMVSNet_ETH3D79.10 21978.24 21781.70 24286.85 25360.24 32487.28 19388.79 23374.25 14976.84 23690.53 16549.48 33591.56 26367.98 25882.15 26493.29 113
IterMVS-LS80.06 19579.38 18982.11 23485.89 27863.20 27686.79 21189.34 20174.19 15075.45 27186.72 27566.62 12792.39 22872.58 20776.86 32990.75 221
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
EI-MVSNet80.52 18379.98 17182.12 23284.28 31863.19 27786.41 22588.95 22974.18 15178.69 19087.54 25566.62 12792.43 22672.57 20880.57 28590.74 222
Vis-MVSNet (Re-imp)78.36 23878.45 21078.07 32788.64 17551.78 41986.70 21579.63 39174.14 15275.11 28790.83 15561.29 20689.75 31258.10 34991.60 9592.69 146
v879.97 19879.02 20082.80 21384.09 32364.50 24087.96 16790.29 16974.13 15375.24 28386.81 27262.88 17693.89 15274.39 18875.40 35890.00 258
guyue81.13 16080.64 15482.60 22486.52 26463.92 25386.69 21687.73 26473.97 15480.83 15989.69 18656.70 25691.33 27878.26 14185.40 21292.54 151
CSCG86.41 4986.19 5587.07 4792.91 6472.48 3790.81 6393.56 2673.95 15583.16 11691.07 14675.94 1995.19 8679.94 12094.38 5993.55 103
thres100view90076.50 28075.55 27979.33 30089.52 13056.99 36385.83 24583.23 34073.94 15676.32 25287.12 26751.89 30591.95 24648.33 41183.75 23889.07 285
9.1488.26 1792.84 6691.52 5394.75 173.93 15788.57 3294.67 2775.57 2395.79 6086.77 4895.76 24
HPM-MVS_fast85.35 7684.95 8286.57 6093.69 4370.58 8192.15 3791.62 12373.89 15882.67 12694.09 5362.60 17795.54 6780.93 10792.93 7493.57 101
PAPM_NR83.02 12282.41 12384.82 11292.47 7366.37 18987.93 17091.80 11473.82 15977.32 22590.66 15967.90 11494.90 10170.37 23289.48 13593.19 121
thres600view776.50 28075.44 28079.68 29389.40 13857.16 36085.53 25483.23 34073.79 16076.26 25387.09 26851.89 30591.89 24948.05 41683.72 24190.00 258
testing9176.54 27875.66 27779.18 30488.43 18355.89 38181.08 34183.00 34773.76 16175.34 27684.29 33846.20 36690.07 30664.33 28984.50 22291.58 191
AstraMVS80.81 16780.14 16882.80 21386.05 27763.96 25086.46 22485.90 30373.71 16280.85 15890.56 16354.06 27991.57 26279.72 12283.97 23392.86 140
v7n78.97 22377.58 23983.14 19383.45 34065.51 21088.32 15591.21 13673.69 16372.41 32786.32 29357.93 24193.81 15469.18 24775.65 34990.11 250
dcpmvs_285.63 6786.15 5784.06 15391.71 8164.94 22786.47 22391.87 11073.63 16486.60 6393.02 8976.57 1691.87 25183.36 8092.15 8695.35 3
v2v48280.23 19279.29 19383.05 19983.62 33664.14 24787.04 19889.97 17873.61 16578.18 20687.22 26361.10 21093.82 15376.11 16676.78 33291.18 203
Baseline_NR-MVSNet78.15 24478.33 21577.61 33685.79 28056.21 37886.78 21285.76 30573.60 16677.93 21287.57 25265.02 14988.99 32767.14 26875.33 36087.63 330
BH-RMVSNet79.61 20178.44 21183.14 19389.38 14065.93 19884.95 26987.15 27873.56 16778.19 20589.79 18456.67 25793.36 17759.53 33386.74 18490.13 248
APD-MVS_3200maxsize85.97 5885.88 6286.22 6492.69 6969.53 9691.93 3992.99 5173.54 16885.94 6594.51 3265.80 14395.61 6483.04 8592.51 8093.53 105
SR-MVS-dyc-post85.77 6485.61 6986.23 6393.06 6170.63 7991.88 4092.27 8673.53 16985.69 6994.45 3465.00 15195.56 6582.75 9091.87 9192.50 154
RE-MVS-def85.48 7293.06 6170.63 7991.88 4092.27 8673.53 16985.69 6994.45 3463.87 15982.75 9091.87 9192.50 154
reproduce_monomvs75.40 30174.38 29978.46 32083.92 32857.80 35283.78 29986.94 28273.47 17172.25 33084.47 33238.74 41689.27 32175.32 17970.53 40088.31 317
test_fmvsmconf_n85.92 5986.04 6085.57 8485.03 30469.51 9789.62 9490.58 15573.42 17287.75 4794.02 5772.85 4693.24 18390.37 890.75 11193.96 72
tfpn200view976.42 28475.37 28479.55 29889.13 15357.65 35485.17 26083.60 33273.41 17376.45 24886.39 29152.12 29791.95 24648.33 41183.75 23889.07 285
thres40076.50 28075.37 28479.86 28889.13 15357.65 35485.17 26083.60 33273.41 17376.45 24886.39 29152.12 29791.95 24648.33 41183.75 23890.00 258
diffmvs_AUTHOR82.38 13282.27 12882.73 22183.26 34463.80 25583.89 29789.76 18573.35 17582.37 12790.84 15466.25 13490.79 29482.77 8987.93 16293.59 100
test_fmvsmconf0.1_n85.61 6885.65 6885.50 8582.99 35669.39 10489.65 9190.29 16973.31 17687.77 4694.15 5171.72 5893.23 18490.31 990.67 11393.89 78
testing9976.09 29075.12 28979.00 30588.16 19255.50 38780.79 34581.40 36773.30 17775.17 28484.27 34144.48 38190.02 30764.28 29084.22 23191.48 196
v14878.72 22977.80 23081.47 24782.73 36261.96 30086.30 23088.08 25173.26 17876.18 25685.47 31262.46 18192.36 23071.92 21873.82 37790.09 252
FA-MVS(test-final)80.96 16379.91 17384.10 14488.30 18865.01 22484.55 28090.01 17773.25 17979.61 17487.57 25258.35 23994.72 11271.29 22386.25 19392.56 150
test_fmvsmconf0.01_n84.73 8684.52 8885.34 8980.25 39869.03 10789.47 9889.65 19073.24 18086.98 5994.27 4466.62 12793.23 18490.26 1089.95 12693.78 87
viewdifsd2359ckpt1180.37 18879.73 17982.30 23083.70 33462.39 29184.20 29186.67 28773.22 18180.90 15590.62 16063.00 17491.56 26376.81 15978.44 30892.95 137
viewmsd2359difaftdt80.37 18879.73 17982.30 23083.70 33462.39 29184.20 29186.67 28773.22 18180.90 15590.62 16063.00 17491.56 26376.81 15978.44 30892.95 137
v1079.74 20078.67 20582.97 20584.06 32464.95 22687.88 17390.62 15473.11 18375.11 28786.56 28661.46 20194.05 14073.68 19375.55 35189.90 264
MCST-MVS87.37 3287.25 3387.73 2994.53 1872.46 4089.82 8493.82 1873.07 18484.86 8192.89 9176.22 1896.33 4284.89 6295.13 3794.40 49
baseline176.98 27276.75 26077.66 33488.13 19555.66 38585.12 26381.89 36073.04 18576.79 23888.90 21362.43 18287.78 34763.30 29771.18 39789.55 276
APD-MVScopyleft87.44 2787.52 2887.19 4494.24 3372.39 4191.86 4292.83 6273.01 18688.58 3194.52 2973.36 3696.49 3984.26 7195.01 3892.70 144
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
diffmvspermissive82.10 13581.88 13782.76 21983.00 35463.78 25783.68 30289.76 18572.94 18782.02 13489.85 17965.96 14290.79 29482.38 9687.30 17393.71 89
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
K. test v371.19 34768.51 35979.21 30383.04 35357.78 35384.35 28876.91 41472.90 18862.99 42082.86 37139.27 41291.09 28861.65 31552.66 44788.75 305
MVSMamba_PlusPlus85.99 5685.96 6186.05 7091.09 8967.64 15889.63 9392.65 7272.89 18984.64 8691.71 11971.85 5596.03 5284.77 6594.45 5794.49 45
GDP-MVS83.52 10782.64 11986.16 6688.14 19468.45 12989.13 11792.69 6772.82 19083.71 10791.86 11655.69 26295.35 8380.03 11889.74 13094.69 30
fmvsm_s_conf0.5_n_585.22 7885.55 7084.25 14086.26 26867.40 16789.18 11189.31 20772.50 19188.31 3493.86 6669.66 8691.96 24589.81 1391.05 10593.38 108
Fast-Effi-MVS+-dtu78.02 24876.49 26482.62 22383.16 35066.96 18286.94 20487.45 27172.45 19271.49 33984.17 34354.79 27191.58 26067.61 26180.31 28889.30 283
PHI-MVS86.43 4786.17 5687.24 4390.88 9670.96 7192.27 3494.07 1172.45 19285.22 7491.90 11369.47 8896.42 4183.28 8295.94 2094.35 52
thres20075.55 29674.47 29778.82 30987.78 21557.85 35083.07 32083.51 33572.44 19475.84 26284.42 33352.08 30091.75 25447.41 41883.64 24386.86 353
test_yl81.17 15880.47 15983.24 18889.13 15363.62 25886.21 23389.95 17972.43 19581.78 13989.61 19057.50 24793.58 16370.75 22786.90 18092.52 152
DCV-MVSNet81.17 15880.47 15983.24 18889.13 15363.62 25886.21 23389.95 17972.43 19581.78 13989.61 19057.50 24793.58 16370.75 22786.90 18092.52 152
viewdifsd2359ckpt1382.91 12482.29 12784.77 11586.96 25166.90 18487.47 18391.62 12372.19 19781.68 14190.71 15766.92 12493.28 17975.90 17087.15 17694.12 64
BH-untuned79.47 20678.60 20782.05 23589.19 15165.91 19986.07 23788.52 24572.18 19875.42 27287.69 24961.15 20993.54 16760.38 32586.83 18386.70 357
TransMVSNet (Re)75.39 30274.56 29577.86 33085.50 29057.10 36286.78 21286.09 30172.17 19971.53 33887.34 25863.01 17389.31 32056.84 36261.83 42987.17 343
GA-MVS76.87 27475.17 28881.97 23882.75 36162.58 28781.44 33886.35 29672.16 20074.74 29582.89 37046.20 36692.02 24368.85 25281.09 27691.30 201
VortexMVS78.57 23477.89 22680.59 27285.89 27862.76 28685.61 24789.62 19272.06 20174.99 29185.38 31455.94 26190.77 29774.99 18176.58 33388.23 318
mmtdpeth74.16 31373.01 31777.60 33883.72 33361.13 30885.10 26485.10 31272.06 20177.21 23280.33 39943.84 38685.75 36777.14 15252.61 44885.91 372
v114480.03 19679.03 19983.01 20183.78 33164.51 23887.11 19790.57 15771.96 20378.08 20986.20 29561.41 20293.94 14474.93 18277.23 32390.60 228
viewdifsd2359ckpt0983.34 11382.55 12185.70 7887.64 22367.72 15688.43 14791.68 12071.91 20481.65 14290.68 15867.10 12394.75 11076.17 16587.70 16694.62 37
PS-MVSNAJss82.07 13781.31 14184.34 13086.51 26567.27 17389.27 10891.51 12871.75 20579.37 18090.22 17463.15 16994.27 12877.69 14582.36 26391.49 195
EPNet_dtu75.46 29874.86 29077.23 34382.57 36654.60 39686.89 20683.09 34471.64 20666.25 39985.86 30155.99 26088.04 34354.92 37386.55 18789.05 290
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
GBi-Net78.40 23677.40 24381.40 25087.60 22463.01 27988.39 15089.28 20871.63 20775.34 27687.28 25954.80 26891.11 28362.72 30079.57 29590.09 252
test178.40 23677.40 24381.40 25087.60 22463.01 27988.39 15089.28 20871.63 20775.34 27687.28 25954.80 26891.11 28362.72 30079.57 29590.09 252
FMVSNet278.20 24277.21 24781.20 25787.60 22462.89 28587.47 18389.02 22471.63 20775.29 28287.28 25954.80 26891.10 28662.38 30579.38 29989.61 274
patch_mono-283.65 10284.54 8680.99 26390.06 11765.83 20184.21 29088.74 23871.60 21085.01 7592.44 10174.51 2783.50 39082.15 9792.15 8693.64 97
V4279.38 21278.24 21782.83 21081.10 39065.50 21185.55 25289.82 18271.57 21178.21 20486.12 29760.66 21893.18 19275.64 17375.46 35589.81 269
API-MVS81.99 13981.23 14384.26 13990.94 9470.18 8891.10 6089.32 20671.51 21278.66 19288.28 23265.26 14695.10 9464.74 28791.23 10387.51 334
tttt051779.40 21077.91 22483.90 16688.10 19763.84 25488.37 15384.05 32771.45 21376.78 23989.12 20449.93 33294.89 10270.18 23683.18 25392.96 136
pm-mvs177.25 26876.68 26278.93 30784.22 32058.62 33886.41 22588.36 24771.37 21473.31 31488.01 24261.22 20889.15 32564.24 29173.01 38489.03 291
Elysia81.53 15180.16 16685.62 8185.51 28868.25 13688.84 12992.19 9471.31 21580.50 16389.83 18046.89 35694.82 10576.85 15589.57 13293.80 85
StellarMVS81.53 15180.16 16685.62 8185.51 28868.25 13688.84 12992.19 9471.31 21580.50 16389.83 18046.89 35694.82 10576.85 15589.57 13293.80 85
testing22274.04 31572.66 32178.19 32387.89 20755.36 38881.06 34279.20 39671.30 21774.65 29883.57 35839.11 41588.67 33551.43 39385.75 20690.53 231
GeoE81.71 14581.01 14883.80 17089.51 13164.45 24288.97 12288.73 23971.27 21878.63 19389.76 18566.32 13393.20 18969.89 24086.02 19893.74 88
tt080578.73 22877.83 22881.43 24885.17 29760.30 32389.41 10390.90 14671.21 21977.17 23388.73 21746.38 36193.21 18672.57 20878.96 30390.79 218
FMVSNet377.88 25276.85 25580.97 26586.84 25462.36 29386.52 22288.77 23471.13 22075.34 27686.66 28154.07 27891.10 28662.72 30079.57 29589.45 278
VDDNet81.52 15380.67 15384.05 15690.44 10564.13 24889.73 8985.91 30271.11 22183.18 11593.48 7450.54 32293.49 17073.40 19888.25 15794.54 44
fmvsm_s_conf0.5_n83.80 9683.71 9884.07 15086.69 26067.31 17089.46 9983.07 34571.09 22286.96 6093.70 7169.02 9991.47 27288.79 2984.62 22193.44 107
XVG-OURS80.41 18479.23 19583.97 16385.64 28469.02 10983.03 32290.39 16171.09 22277.63 21991.49 13254.62 27491.35 27675.71 17283.47 24791.54 192
SSM_040781.58 15080.48 15884.87 11088.81 16467.96 14687.37 18889.25 21271.06 22479.48 17790.39 16759.57 22894.48 12372.45 21485.93 20192.18 171
SSM_040481.91 14080.84 15185.13 9889.24 14868.26 13487.84 17589.25 21271.06 22480.62 16190.39 16759.57 22894.65 11672.45 21487.19 17592.47 157
SixPastTwentyTwo73.37 32471.26 33879.70 29285.08 30257.89 34985.57 24883.56 33471.03 22665.66 40285.88 30042.10 39892.57 21859.11 33763.34 42488.65 309
ZD-MVS94.38 2672.22 4692.67 6970.98 22787.75 4794.07 5474.01 3496.70 2884.66 6694.84 45
mamba_040879.37 21377.52 24084.93 10788.81 16467.96 14665.03 45488.66 24070.96 22879.48 17789.80 18258.69 23494.65 11670.35 23385.93 20192.18 171
SSM_0407277.67 26077.52 24078.12 32588.81 16467.96 14665.03 45488.66 24070.96 22879.48 17789.80 18258.69 23474.23 44670.35 23385.93 20192.18 171
v119279.59 20378.43 21283.07 19883.55 33864.52 23786.93 20590.58 15570.83 23077.78 21685.90 29959.15 23293.94 14473.96 19277.19 32590.76 220
Fast-Effi-MVS+80.81 16779.92 17283.47 17788.85 16064.51 23885.53 25489.39 20070.79 23178.49 19785.06 32367.54 11793.58 16367.03 27086.58 18692.32 163
PS-MVSNAJ81.69 14681.02 14783.70 17189.51 13168.21 13984.28 28990.09 17570.79 23181.26 15085.62 30863.15 16994.29 12675.62 17488.87 14588.59 311
LTVRE_ROB69.57 1376.25 28774.54 29681.41 24988.60 17664.38 24479.24 37089.12 22170.76 23369.79 36087.86 24549.09 34293.20 18956.21 36880.16 28986.65 358
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
testing1175.14 30474.01 30278.53 31788.16 19256.38 37480.74 34880.42 38170.67 23472.69 32483.72 35343.61 38889.86 30962.29 30783.76 23789.36 281
fmvsm_s_conf0.1_n83.56 10683.38 10584.10 14484.86 30667.28 17289.40 10483.01 34670.67 23487.08 5793.96 6368.38 10691.45 27388.56 3384.50 22293.56 102
xiu_mvs_v2_base81.69 14681.05 14683.60 17389.15 15268.03 14484.46 28390.02 17670.67 23481.30 14986.53 28863.17 16894.19 13575.60 17588.54 15288.57 312
XVG-OURS-SEG-HR80.81 16779.76 17883.96 16485.60 28668.78 11583.54 30990.50 15870.66 23776.71 24191.66 12160.69 21691.26 27976.94 15481.58 27191.83 181
Anonymous20240521178.25 23977.01 25081.99 23791.03 9160.67 31784.77 27283.90 32970.65 23880.00 17091.20 14141.08 40591.43 27465.21 28285.26 21393.85 79
DP-MVS Recon83.11 12182.09 13286.15 6794.44 2070.92 7488.79 13192.20 9370.53 23979.17 18391.03 14964.12 15796.03 5268.39 25790.14 12191.50 194
icg_test_0407_278.92 22578.93 20278.90 30887.13 24263.59 26276.58 40189.33 20270.51 24077.82 21389.03 20761.84 19181.38 40572.56 21085.56 20891.74 184
IMVS_040780.61 17779.90 17482.75 22087.13 24263.59 26285.33 25889.33 20270.51 24077.82 21389.03 20761.84 19192.91 20572.56 21085.56 20891.74 184
IMVS_040477.16 26976.42 26779.37 29987.13 24263.59 26277.12 39989.33 20270.51 24066.22 40089.03 20750.36 32482.78 39572.56 21085.56 20891.74 184
IMVS_040380.80 17080.12 16982.87 20987.13 24263.59 26285.19 25989.33 20270.51 24078.49 19789.03 20763.26 16593.27 18172.56 21085.56 20891.74 184
FMVSNet177.44 26376.12 27181.40 25086.81 25563.01 27988.39 15089.28 20870.49 24474.39 30287.28 25949.06 34391.11 28360.91 32178.52 30690.09 252
LuminaMVS80.68 17579.62 18483.83 16785.07 30368.01 14586.99 20188.83 23170.36 24581.38 14587.99 24350.11 32792.51 22379.02 12686.89 18290.97 212
testing368.56 37667.67 37571.22 40487.33 23442.87 45483.06 32171.54 43470.36 24569.08 36684.38 33530.33 44285.69 36937.50 44775.45 35685.09 387
ab-mvs79.51 20478.97 20181.14 25988.46 18160.91 31383.84 29889.24 21470.36 24579.03 18488.87 21563.23 16790.21 30465.12 28382.57 26192.28 165
tfpnnormal74.39 30973.16 31578.08 32686.10 27658.05 34484.65 27787.53 26870.32 24871.22 34285.63 30754.97 26689.86 30943.03 43575.02 36586.32 361
ACMM73.20 880.78 17479.84 17683.58 17589.31 14468.37 13189.99 8191.60 12570.28 24977.25 22689.66 18853.37 28693.53 16874.24 19082.85 25688.85 300
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
fmvsm_s_conf0.5_n_a83.63 10483.41 10484.28 13586.14 27368.12 14089.43 10082.87 35070.27 25087.27 5693.80 6969.09 9491.58 26088.21 3783.65 24293.14 125
ACMH+68.96 1476.01 29174.01 30282.03 23688.60 17665.31 21688.86 12687.55 26770.25 25167.75 37687.47 25741.27 40393.19 19158.37 34675.94 34687.60 331
IB-MVS68.01 1575.85 29373.36 31383.31 18484.76 30966.03 19383.38 31185.06 31370.21 25269.40 36281.05 38945.76 37194.66 11565.10 28475.49 35289.25 284
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
thisisatest053079.40 21077.76 23384.31 13287.69 22165.10 22387.36 18984.26 32570.04 25377.42 22288.26 23449.94 33094.79 10970.20 23584.70 22093.03 131
mvsmamba80.60 17979.38 18984.27 13789.74 12567.24 17587.47 18386.95 28170.02 25475.38 27488.93 21251.24 31392.56 21975.47 17889.22 13993.00 134
test_fmvsmvis_n_192084.02 9283.87 9484.49 12484.12 32269.37 10588.15 16287.96 25670.01 25583.95 10393.23 8268.80 10191.51 27088.61 3189.96 12592.57 149
v14419279.47 20678.37 21382.78 21783.35 34163.96 25086.96 20290.36 16569.99 25677.50 22085.67 30660.66 21893.77 15774.27 18976.58 33390.62 226
test_fmvsm_n_192085.29 7785.34 7485.13 9886.12 27469.93 8988.65 14090.78 15169.97 25788.27 3593.98 6271.39 6491.54 26788.49 3490.45 11693.91 75
c3_l78.75 22777.91 22481.26 25582.89 35961.56 30584.09 29589.13 22069.97 25775.56 26684.29 33866.36 13292.09 24073.47 19775.48 35390.12 249
v192192079.22 21578.03 22182.80 21383.30 34363.94 25286.80 21090.33 16669.91 25977.48 22185.53 31058.44 23893.75 15973.60 19476.85 33090.71 224
ACMH67.68 1675.89 29273.93 30481.77 24188.71 17366.61 18688.62 14189.01 22569.81 26066.78 39086.70 27941.95 40091.51 27055.64 36978.14 31487.17 343
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
fmvsm_s_conf0.1_n_a83.32 11582.99 11284.28 13583.79 33068.07 14289.34 10782.85 35169.80 26187.36 5594.06 5568.34 10891.56 26387.95 3983.46 24893.21 118
DPM-MVS84.93 8384.29 9086.84 5390.20 11073.04 2387.12 19693.04 4369.80 26182.85 12291.22 14073.06 4296.02 5476.72 16294.63 5191.46 198
MAR-MVS81.84 14280.70 15285.27 9191.32 8671.53 5889.82 8490.92 14569.77 26378.50 19686.21 29462.36 18394.52 12065.36 28192.05 8989.77 270
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
XVG-ACMP-BASELINE76.11 28974.27 30181.62 24383.20 34764.67 23483.60 30689.75 18769.75 26471.85 33487.09 26832.78 43592.11 23969.99 23980.43 28788.09 322
BH-w/o78.21 24177.33 24680.84 26788.81 16465.13 22084.87 27087.85 26169.75 26474.52 30084.74 33061.34 20493.11 19658.24 34885.84 20484.27 395
v124078.99 22277.78 23182.64 22283.21 34663.54 26686.62 21990.30 16869.74 26677.33 22485.68 30557.04 25393.76 15873.13 20276.92 32790.62 226
ET-MVSNet_ETH3D78.63 23176.63 26384.64 11986.73 25869.47 9985.01 26784.61 31869.54 26766.51 39786.59 28350.16 32691.75 25476.26 16484.24 23092.69 146
eth_miper_zixun_eth77.92 25176.69 26181.61 24583.00 35461.98 29983.15 31689.20 21669.52 26874.86 29484.35 33761.76 19492.56 21971.50 22172.89 38590.28 243
PVSNet_Blended_VisFu82.62 12881.83 13884.96 10490.80 9869.76 9488.74 13691.70 11969.39 26978.96 18588.46 22765.47 14594.87 10474.42 18788.57 15190.24 244
mvs_tets79.13 21877.77 23283.22 19084.70 31066.37 18989.17 11290.19 17269.38 27075.40 27389.46 19744.17 38493.15 19376.78 16180.70 28390.14 247
PVSNet_BlendedMVS80.60 17980.02 17082.36 22988.85 16065.40 21286.16 23592.00 10269.34 27178.11 20786.09 29866.02 14094.27 12871.52 21982.06 26687.39 336
SD_040374.65 30874.77 29274.29 37486.20 27147.42 43883.71 30185.12 31169.30 27268.50 37287.95 24459.40 23086.05 36449.38 40583.35 24989.40 279
AdaColmapbinary80.58 18279.42 18884.06 15393.09 6068.91 11289.36 10688.97 22869.27 27375.70 26489.69 18657.20 25295.77 6163.06 29888.41 15687.50 335
ETVMVS72.25 34071.05 33975.84 35287.77 21651.91 41679.39 36874.98 42269.26 27473.71 30982.95 36840.82 40786.14 36346.17 42484.43 22789.47 277
ITE_SJBPF78.22 32281.77 37760.57 31883.30 33869.25 27567.54 37887.20 26436.33 42887.28 35354.34 37674.62 36986.80 354
cl____77.72 25676.76 25880.58 27382.49 36860.48 32083.09 31887.87 25969.22 27674.38 30385.22 31962.10 18891.53 26871.09 22475.41 35789.73 272
DIV-MVS_self_test77.72 25676.76 25880.58 27382.48 36960.48 32083.09 31887.86 26069.22 27674.38 30385.24 31762.10 18891.53 26871.09 22475.40 35889.74 271
jajsoiax79.29 21477.96 22283.27 18684.68 31166.57 18789.25 10990.16 17369.20 27875.46 27089.49 19445.75 37293.13 19576.84 15780.80 28190.11 250
IterMVS-SCA-FT75.43 29973.87 30680.11 28482.69 36364.85 23181.57 33583.47 33669.16 27970.49 34684.15 34451.95 30388.15 34169.23 24672.14 39187.34 338
CL-MVSNet_self_test72.37 33871.46 33375.09 36479.49 41153.53 40480.76 34785.01 31569.12 28070.51 34582.05 38357.92 24284.13 38452.27 38766.00 41887.60 331
AUN-MVS79.21 21677.60 23884.05 15688.71 17367.61 15985.84 24487.26 27569.08 28177.23 22888.14 24053.20 28893.47 17275.50 17773.45 38091.06 207
xiu_mvs_v1_base_debu80.80 17079.72 18184.03 15887.35 22970.19 8585.56 24988.77 23469.06 28281.83 13588.16 23650.91 31692.85 20878.29 13887.56 16789.06 287
xiu_mvs_v1_base80.80 17079.72 18184.03 15887.35 22970.19 8585.56 24988.77 23469.06 28281.83 13588.16 23650.91 31692.85 20878.29 13887.56 16789.06 287
xiu_mvs_v1_base_debi80.80 17079.72 18184.03 15887.35 22970.19 8585.56 24988.77 23469.06 28281.83 13588.16 23650.91 31692.85 20878.29 13887.56 16789.06 287
MVSTER79.01 22177.88 22782.38 22883.07 35164.80 23284.08 29688.95 22969.01 28578.69 19087.17 26654.70 27292.43 22674.69 18380.57 28589.89 265
cl2278.07 24677.01 25081.23 25682.37 37161.83 30283.55 30787.98 25568.96 28675.06 28983.87 34661.40 20391.88 25073.53 19576.39 33889.98 261
miper_ehance_all_eth78.59 23377.76 23381.08 26182.66 36461.56 30583.65 30389.15 21868.87 28775.55 26783.79 35066.49 13092.03 24173.25 20076.39 33889.64 273
PAPR81.66 14880.89 15083.99 16290.27 10864.00 24986.76 21491.77 11768.84 28877.13 23589.50 19367.63 11694.88 10367.55 26288.52 15393.09 126
CPTT-MVS83.73 9983.33 10784.92 10893.28 5070.86 7592.09 3890.38 16268.75 28979.57 17592.83 9360.60 22193.04 20280.92 10891.56 9890.86 216
train_agg86.43 4786.20 5387.13 4693.26 5372.96 2588.75 13491.89 10868.69 29085.00 7693.10 8474.43 2895.41 7784.97 5995.71 2693.02 132
test_893.13 5772.57 3588.68 13991.84 11268.69 29084.87 8093.10 8474.43 2895.16 87
dmvs_re71.14 34870.58 34372.80 39081.96 37459.68 32975.60 40979.34 39468.55 29269.27 36580.72 39549.42 33676.54 42752.56 38677.79 31782.19 420
MVSFormer82.85 12582.05 13385.24 9287.35 22970.21 8390.50 6990.38 16268.55 29281.32 14689.47 19561.68 19593.46 17378.98 12990.26 11992.05 178
test_djsdf80.30 19179.32 19283.27 18683.98 32665.37 21590.50 6990.38 16268.55 29276.19 25588.70 21856.44 25993.46 17378.98 12980.14 29190.97 212
TEST993.26 5372.96 2588.75 13491.89 10868.44 29585.00 7693.10 8474.36 3095.41 77
FE-MVS77.78 25475.68 27584.08 14988.09 19866.00 19683.13 31787.79 26268.42 29678.01 21085.23 31845.50 37595.12 8959.11 33785.83 20591.11 205
CDPH-MVS85.76 6585.29 7887.17 4593.49 4871.08 6788.58 14392.42 8268.32 29784.61 8793.48 7472.32 4996.15 5079.00 12895.43 3194.28 57
PC_three_145268.21 29892.02 1294.00 5982.09 595.98 5884.58 6796.68 294.95 12
fmvsm_l_conf0.5_n84.47 8784.54 8684.27 13785.42 29168.81 11388.49 14687.26 27568.08 29988.03 4193.49 7372.04 5491.77 25388.90 2889.14 14292.24 168
IterMVS74.29 31072.94 31878.35 32181.53 38263.49 26881.58 33482.49 35468.06 30069.99 35583.69 35451.66 31085.54 37165.85 27871.64 39486.01 369
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
dmvs_testset62.63 40564.11 39658.19 43578.55 41724.76 47375.28 41065.94 45067.91 30160.34 42976.01 43253.56 28373.94 44831.79 45367.65 41175.88 442
TAMVS78.89 22677.51 24283.03 20087.80 21267.79 15484.72 27385.05 31467.63 30276.75 24087.70 24862.25 18590.82 29358.53 34487.13 17790.49 233
PVSNet_Blended80.98 16280.34 16182.90 20788.85 16065.40 21284.43 28592.00 10267.62 30378.11 20785.05 32466.02 14094.27 12871.52 21989.50 13489.01 292
TR-MVS77.44 26376.18 27081.20 25788.24 18963.24 27484.61 27886.40 29467.55 30477.81 21586.48 28954.10 27793.15 19357.75 35282.72 25987.20 342
CDS-MVSNet79.07 22077.70 23583.17 19287.60 22468.23 13884.40 28786.20 29867.49 30576.36 25186.54 28761.54 19890.79 29461.86 31387.33 17290.49 233
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
fmvsm_l_conf0.5_n_a84.13 9084.16 9184.06 15385.38 29268.40 13088.34 15486.85 28567.48 30687.48 5293.40 7870.89 7091.61 25888.38 3689.22 13992.16 175
mvs_anonymous79.42 20979.11 19880.34 27884.45 31757.97 34782.59 32487.62 26667.40 30776.17 25888.56 22568.47 10589.59 31570.65 23086.05 19793.47 106
viewmambaseed2359dif80.41 18479.84 17682.12 23282.95 35862.50 29083.39 31088.06 25367.11 30880.98 15390.31 16966.20 13691.01 29074.62 18484.90 21692.86 140
mvs5depth69.45 36867.45 37975.46 36073.93 43655.83 38279.19 37283.23 34066.89 30971.63 33783.32 36133.69 43485.09 37659.81 33055.34 44485.46 378
IU-MVS95.30 271.25 6292.95 5766.81 31092.39 688.94 2796.63 494.85 21
baseline275.70 29473.83 30781.30 25383.26 34461.79 30382.57 32580.65 37466.81 31066.88 38883.42 36057.86 24392.19 23763.47 29479.57 29589.91 263
miper_lstm_enhance74.11 31473.11 31677.13 34480.11 40059.62 33072.23 42586.92 28466.76 31270.40 34782.92 36956.93 25482.92 39469.06 24972.63 38688.87 299
OpenMVScopyleft72.83 1079.77 19978.33 21584.09 14885.17 29769.91 9090.57 6690.97 14466.70 31372.17 33191.91 11254.70 27293.96 14161.81 31490.95 10888.41 316
test-LLR72.94 33472.43 32374.48 37181.35 38658.04 34578.38 38477.46 40766.66 31469.95 35679.00 41448.06 34879.24 41366.13 27384.83 21786.15 365
test20.0367.45 38366.95 38468.94 41375.48 43144.84 45077.50 39577.67 40566.66 31463.01 41983.80 34947.02 35478.40 41742.53 43868.86 40983.58 405
test0.0.03 168.00 38167.69 37468.90 41477.55 42047.43 43775.70 40872.95 43366.66 31466.56 39382.29 38048.06 34875.87 43644.97 43174.51 37083.41 406
Syy-MVS68.05 38067.85 36968.67 41784.68 31140.97 46078.62 38173.08 43166.65 31766.74 39179.46 40952.11 29982.30 39832.89 45276.38 34182.75 415
myMVS_eth3d67.02 38766.29 38769.21 41284.68 31142.58 45578.62 38173.08 43166.65 31766.74 39179.46 40931.53 43982.30 39839.43 44476.38 34182.75 415
QAPM80.88 16479.50 18785.03 10188.01 20368.97 11191.59 4892.00 10266.63 31975.15 28692.16 10757.70 24495.45 7263.52 29388.76 14890.66 225
XXY-MVS75.41 30075.56 27874.96 36583.59 33757.82 35180.59 35183.87 33066.54 32074.93 29388.31 23163.24 16680.09 41162.16 30976.85 33086.97 351
OurMVSNet-221017-074.26 31172.42 32479.80 29083.76 33259.59 33185.92 24186.64 28966.39 32166.96 38787.58 25139.46 41191.60 25965.76 27969.27 40588.22 319
SCA74.22 31272.33 32579.91 28784.05 32562.17 29779.96 36379.29 39566.30 32272.38 32880.13 40251.95 30388.60 33659.25 33577.67 32188.96 296
testgi66.67 39066.53 38667.08 42475.62 43041.69 45975.93 40476.50 41666.11 32365.20 40886.59 28335.72 43074.71 44343.71 43273.38 38284.84 390
HY-MVS69.67 1277.95 25077.15 24880.36 27787.57 22860.21 32583.37 31287.78 26366.11 32375.37 27587.06 27063.27 16490.48 30161.38 31882.43 26290.40 237
EG-PatchMatch MVS74.04 31571.82 32980.71 27084.92 30567.42 16585.86 24388.08 25166.04 32564.22 41283.85 34735.10 43192.56 21957.44 35480.83 28082.16 421
CNLPA78.08 24576.79 25781.97 23890.40 10671.07 6887.59 18084.55 31966.03 32672.38 32889.64 18957.56 24686.04 36559.61 33283.35 24988.79 303
Anonymous2024052980.19 19478.89 20384.10 14490.60 10164.75 23388.95 12390.90 14665.97 32780.59 16291.17 14349.97 32993.73 16169.16 24882.70 26093.81 83
TAPA-MVS73.13 979.15 21777.94 22382.79 21689.59 12762.99 28388.16 16191.51 12865.77 32877.14 23491.09 14560.91 21393.21 18650.26 40187.05 17892.17 174
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
MSDG73.36 32670.99 34080.49 27584.51 31665.80 20380.71 34986.13 30065.70 32965.46 40383.74 35144.60 37990.91 29251.13 39476.89 32884.74 391
anonymousdsp78.60 23277.15 24882.98 20480.51 39667.08 17887.24 19489.53 19565.66 33075.16 28587.19 26552.52 29092.25 23577.17 15179.34 30089.61 274
test_040272.79 33570.44 34679.84 28988.13 19565.99 19785.93 24084.29 32365.57 33167.40 38385.49 31146.92 35592.61 21535.88 44974.38 37180.94 428
UBG73.08 33172.27 32675.51 35888.02 20151.29 42478.35 38777.38 41065.52 33273.87 30882.36 37745.55 37386.48 36055.02 37284.39 22888.75 305
miper_enhance_ethall77.87 25376.86 25480.92 26681.65 37861.38 30782.68 32388.98 22665.52 33275.47 26882.30 37965.76 14492.00 24472.95 20376.39 33889.39 280
WBMVS73.43 32372.81 31975.28 36287.91 20650.99 42678.59 38381.31 36965.51 33474.47 30184.83 32746.39 36086.68 35758.41 34577.86 31688.17 321
UnsupCasMVSNet_eth67.33 38465.99 38871.37 40073.48 44151.47 42275.16 41285.19 31065.20 33560.78 42780.93 39442.35 39477.20 42357.12 35753.69 44685.44 379
WTY-MVS75.65 29575.68 27575.57 35686.40 26756.82 36577.92 39382.40 35565.10 33676.18 25687.72 24763.13 17280.90 40860.31 32681.96 26789.00 294
thisisatest051577.33 26675.38 28383.18 19185.27 29663.80 25582.11 32983.27 33965.06 33775.91 26083.84 34849.54 33494.27 12867.24 26686.19 19491.48 196
MVP-Stereo76.12 28874.46 29881.13 26085.37 29369.79 9284.42 28687.95 25765.03 33867.46 38085.33 31553.28 28791.73 25658.01 35083.27 25181.85 423
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
Anonymous2023121178.97 22377.69 23682.81 21290.54 10364.29 24590.11 8091.51 12865.01 33976.16 25988.13 24150.56 32193.03 20369.68 24377.56 32291.11 205
pmmvs674.69 30773.39 31178.61 31281.38 38557.48 35786.64 21887.95 25764.99 34070.18 35086.61 28250.43 32389.52 31662.12 31070.18 40288.83 301
PAPM77.68 25976.40 26881.51 24687.29 23861.85 30183.78 29989.59 19364.74 34171.23 34188.70 21862.59 17893.66 16252.66 38587.03 17989.01 292
MIMVSNet70.69 35469.30 35374.88 36784.52 31556.35 37675.87 40779.42 39264.59 34267.76 37582.41 37641.10 40481.54 40346.64 42281.34 27286.75 356
tpm72.37 33871.71 33074.35 37382.19 37252.00 41479.22 37177.29 41164.56 34372.95 32083.68 35551.35 31183.26 39358.33 34775.80 34787.81 327
MDA-MVSNet-bldmvs66.68 38963.66 39975.75 35379.28 41360.56 31973.92 42178.35 40264.43 34450.13 45279.87 40644.02 38583.67 38746.10 42556.86 43883.03 412
MIMVSNet168.58 37566.78 38573.98 37880.07 40151.82 41880.77 34684.37 32064.40 34559.75 43382.16 38236.47 42783.63 38842.73 43670.33 40186.48 360
D2MVS74.82 30673.21 31479.64 29579.81 40562.56 28980.34 35687.35 27264.37 34668.86 36782.66 37446.37 36290.10 30567.91 25981.24 27486.25 362
PLCcopyleft70.83 1178.05 24776.37 26983.08 19791.88 8067.80 15388.19 15989.46 19764.33 34769.87 35888.38 22953.66 28293.58 16358.86 34082.73 25887.86 326
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
PatchmatchNetpermissive73.12 33071.33 33678.49 31983.18 34860.85 31479.63 36578.57 40064.13 34871.73 33579.81 40751.20 31485.97 36657.40 35576.36 34388.66 308
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
mamv476.81 27578.23 21972.54 39386.12 27465.75 20678.76 37982.07 35964.12 34972.97 31991.02 15067.97 11268.08 45883.04 8578.02 31583.80 403
KD-MVS_2432*160066.22 39463.89 39773.21 38475.47 43253.42 40670.76 43284.35 32164.10 35066.52 39578.52 41834.55 43284.98 37750.40 39750.33 45181.23 426
miper_refine_blended66.22 39463.89 39773.21 38475.47 43253.42 40670.76 43284.35 32164.10 35066.52 39578.52 41834.55 43284.98 37750.40 39750.33 45181.23 426
tpmvs71.09 34969.29 35476.49 34882.04 37356.04 37978.92 37781.37 36864.05 35267.18 38578.28 42049.74 33389.77 31149.67 40472.37 38783.67 404
F-COLMAP76.38 28674.33 30082.50 22689.28 14666.95 18388.41 14989.03 22364.05 35266.83 38988.61 22246.78 35892.89 20657.48 35378.55 30587.67 329
DP-MVS76.78 27674.57 29483.42 18093.29 4969.46 10188.55 14583.70 33163.98 35470.20 34988.89 21454.01 28094.80 10846.66 42081.88 26986.01 369
原ACMM184.35 12993.01 6368.79 11492.44 7963.96 35581.09 15191.57 12866.06 13995.45 7267.19 26794.82 4788.81 302
PM-MVS66.41 39264.14 39573.20 38673.92 43756.45 37178.97 37664.96 45363.88 35664.72 40980.24 40119.84 45883.44 39166.24 27264.52 42279.71 434
FE-MVSNET67.25 38665.33 39073.02 38875.86 42752.54 41280.26 35980.56 37663.80 35760.39 42879.70 40841.41 40284.66 38243.34 43462.62 42781.86 422
UWE-MVS72.13 34271.49 33274.03 37786.66 26147.70 43681.40 33976.89 41563.60 35875.59 26584.22 34239.94 41085.62 37048.98 40886.13 19688.77 304
jason81.39 15680.29 16384.70 11886.63 26269.90 9185.95 23986.77 28663.24 35981.07 15289.47 19561.08 21192.15 23878.33 13790.07 12492.05 178
jason: jason.
KD-MVS_self_test68.81 37267.59 37772.46 39474.29 43545.45 44477.93 39287.00 28063.12 36063.99 41578.99 41642.32 39584.77 38056.55 36664.09 42387.16 345
gg-mvs-nofinetune69.95 36467.96 36775.94 35183.07 35154.51 39877.23 39870.29 43763.11 36170.32 34862.33 45143.62 38788.69 33453.88 37987.76 16584.62 393
tpmrst72.39 33672.13 32773.18 38780.54 39549.91 43179.91 36479.08 39763.11 36171.69 33679.95 40455.32 26482.77 39665.66 28073.89 37586.87 352
PCF-MVS73.52 780.38 18678.84 20485.01 10287.71 21968.99 11083.65 30391.46 13263.00 36377.77 21790.28 17066.10 13795.09 9561.40 31788.22 15890.94 214
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
COLMAP_ROBcopyleft66.92 1773.01 33270.41 34780.81 26887.13 24265.63 20788.30 15684.19 32662.96 36463.80 41787.69 24938.04 42192.56 21946.66 42074.91 36684.24 396
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
Patchmatch-RL test70.24 36067.78 37377.61 33677.43 42159.57 33271.16 42970.33 43662.94 36568.65 36972.77 44250.62 32085.49 37269.58 24466.58 41587.77 328
lupinMVS81.39 15680.27 16484.76 11687.35 22970.21 8385.55 25286.41 29362.85 36681.32 14688.61 22261.68 19592.24 23678.41 13690.26 11991.83 181
test_vis1_n_192075.52 29775.78 27374.75 37079.84 40457.44 35883.26 31485.52 30762.83 36779.34 18286.17 29645.10 37779.71 41278.75 13181.21 27587.10 349
EPMVS69.02 37168.16 36371.59 39879.61 40949.80 43377.40 39666.93 44762.82 36870.01 35379.05 41245.79 37077.86 42156.58 36575.26 36287.13 346
PatchMatch-RL72.38 33770.90 34176.80 34788.60 17667.38 16879.53 36676.17 41962.75 36969.36 36382.00 38545.51 37484.89 37953.62 38080.58 28478.12 437
gm-plane-assit81.40 38453.83 40362.72 37080.94 39292.39 22863.40 296
FMVSNet569.50 36767.96 36774.15 37682.97 35755.35 38980.01 36282.12 35862.56 37163.02 41881.53 38636.92 42481.92 40148.42 41074.06 37385.17 385
sss73.60 32173.64 30973.51 38282.80 36055.01 39376.12 40381.69 36362.47 37274.68 29785.85 30257.32 24978.11 41960.86 32280.93 27787.39 336
WB-MVSnew71.96 34471.65 33172.89 38984.67 31451.88 41782.29 32777.57 40662.31 37373.67 31183.00 36753.49 28581.10 40745.75 42782.13 26585.70 375
AllTest70.96 35068.09 36579.58 29685.15 29963.62 25884.58 27979.83 38862.31 37360.32 43086.73 27332.02 43688.96 33050.28 39971.57 39586.15 365
TestCases79.58 29685.15 29963.62 25879.83 38862.31 37360.32 43086.73 27332.02 43688.96 33050.28 39971.57 39586.15 365
1112_ss77.40 26576.43 26680.32 27989.11 15760.41 32283.65 30387.72 26562.13 37673.05 31886.72 27562.58 17989.97 30862.11 31180.80 28190.59 229
PVSNet64.34 1872.08 34370.87 34275.69 35486.21 27056.44 37274.37 41980.73 37362.06 37770.17 35182.23 38142.86 39283.31 39254.77 37484.45 22687.32 339
UWE-MVS-2865.32 39764.93 39166.49 42578.70 41638.55 46277.86 39464.39 45462.00 37864.13 41383.60 35641.44 40176.00 43431.39 45480.89 27884.92 388
LS3D76.95 27374.82 29183.37 18390.45 10467.36 16989.15 11686.94 28261.87 37969.52 36190.61 16251.71 30994.53 11946.38 42386.71 18588.21 320
CostFormer75.24 30373.90 30579.27 30182.65 36558.27 34280.80 34482.73 35361.57 38075.33 28083.13 36555.52 26391.07 28964.98 28578.34 31388.45 314
new-patchmatchnet61.73 40761.73 40861.70 43172.74 44724.50 47469.16 43978.03 40361.40 38156.72 44275.53 43638.42 41876.48 42945.95 42657.67 43784.13 398
ANet_high50.57 42546.10 42963.99 42848.67 47339.13 46170.99 43180.85 37161.39 38231.18 46257.70 45817.02 46173.65 44931.22 45515.89 47079.18 435
MS-PatchMatch73.83 31872.67 32077.30 34283.87 32966.02 19481.82 33084.66 31761.37 38368.61 37082.82 37247.29 35188.21 34059.27 33484.32 22977.68 438
USDC70.33 35968.37 36076.21 35080.60 39456.23 37779.19 37286.49 29260.89 38461.29 42585.47 31231.78 43889.47 31853.37 38276.21 34482.94 414
cascas76.72 27774.64 29382.99 20285.78 28165.88 20082.33 32689.21 21560.85 38572.74 32181.02 39047.28 35293.75 15967.48 26385.02 21489.34 282
sc_t172.19 34169.51 35280.23 28184.81 30761.09 31084.68 27480.22 38560.70 38671.27 34083.58 35736.59 42689.24 32260.41 32463.31 42590.37 238
MDTV_nov1_ep1369.97 35183.18 34853.48 40577.10 40080.18 38760.45 38769.33 36480.44 39648.89 34686.90 35551.60 39078.51 307
TinyColmap67.30 38564.81 39274.76 36981.92 37656.68 36980.29 35781.49 36660.33 38856.27 44483.22 36224.77 45087.66 34945.52 42869.47 40479.95 433
test-mter71.41 34670.39 34874.48 37181.35 38658.04 34578.38 38477.46 40760.32 38969.95 35679.00 41436.08 42979.24 41366.13 27384.83 21786.15 365
131476.53 27975.30 28680.21 28283.93 32762.32 29584.66 27588.81 23260.23 39070.16 35284.07 34555.30 26590.73 29867.37 26483.21 25287.59 333
PatchT68.46 37867.85 36970.29 40880.70 39343.93 45272.47 42474.88 42360.15 39170.55 34476.57 42949.94 33081.59 40250.58 39574.83 36785.34 380
无先验87.48 18288.98 22660.00 39294.12 13767.28 26588.97 295
CR-MVSNet73.37 32471.27 33779.67 29481.32 38865.19 21875.92 40580.30 38359.92 39372.73 32281.19 38752.50 29186.69 35659.84 32977.71 31887.11 347
TDRefinement67.49 38264.34 39476.92 34573.47 44261.07 31184.86 27182.98 34859.77 39458.30 43785.13 32126.06 44687.89 34547.92 41760.59 43481.81 424
dp66.80 38865.43 38970.90 40779.74 40848.82 43575.12 41474.77 42459.61 39564.08 41477.23 42642.89 39180.72 40948.86 40966.58 41583.16 409
our_test_369.14 37067.00 38375.57 35679.80 40658.80 33677.96 39177.81 40459.55 39662.90 42178.25 42147.43 35083.97 38551.71 38967.58 41283.93 401
Test_1112_low_res76.40 28575.44 28079.27 30189.28 14658.09 34381.69 33387.07 27959.53 39772.48 32686.67 28061.30 20589.33 31960.81 32380.15 29090.41 236
pmmvs474.03 31771.91 32880.39 27681.96 37468.32 13281.45 33782.14 35759.32 39869.87 35885.13 32152.40 29388.13 34260.21 32774.74 36884.73 392
testdata79.97 28690.90 9564.21 24684.71 31659.27 39985.40 7192.91 9062.02 19089.08 32668.95 25091.37 10186.63 359
WB-MVS54.94 41554.72 41655.60 44173.50 44020.90 47574.27 42061.19 45859.16 40050.61 45074.15 43847.19 35375.78 43717.31 46635.07 46070.12 448
ppachtmachnet_test70.04 36367.34 38178.14 32479.80 40661.13 30879.19 37280.59 37559.16 40065.27 40579.29 41146.75 35987.29 35249.33 40666.72 41386.00 371
RPSCF73.23 32971.46 33378.54 31682.50 36759.85 32782.18 32882.84 35258.96 40271.15 34389.41 20145.48 37684.77 38058.82 34171.83 39391.02 211
pmmvs-eth3d70.50 35767.83 37178.52 31877.37 42266.18 19281.82 33081.51 36558.90 40363.90 41680.42 39742.69 39386.28 36258.56 34365.30 42083.11 410
tt0320-xc70.11 36267.45 37978.07 32785.33 29459.51 33383.28 31378.96 39858.77 40467.10 38680.28 40036.73 42587.42 35156.83 36359.77 43687.29 340
OpenMVS_ROBcopyleft64.09 1970.56 35668.19 36277.65 33580.26 39759.41 33485.01 26782.96 34958.76 40565.43 40482.33 37837.63 42391.23 28145.34 43076.03 34582.32 418
114514_t80.68 17579.51 18684.20 14194.09 3967.27 17389.64 9291.11 14158.75 40674.08 30590.72 15658.10 24095.04 9669.70 24289.42 13690.30 242
Patchmtry70.74 35369.16 35675.49 35980.72 39254.07 40174.94 41680.30 38358.34 40770.01 35381.19 38752.50 29186.54 35853.37 38271.09 39885.87 374
test_cas_vis1_n_192073.76 31973.74 30873.81 38075.90 42659.77 32880.51 35282.40 35558.30 40881.62 14385.69 30444.35 38376.41 43076.29 16378.61 30485.23 382
Anonymous2024052168.80 37367.22 38273.55 38174.33 43454.11 40083.18 31585.61 30658.15 40961.68 42480.94 39230.71 44181.27 40657.00 36073.34 38385.28 381
tt032070.49 35868.03 36677.89 32984.78 30859.12 33583.55 30780.44 38058.13 41067.43 38280.41 39839.26 41387.54 35055.12 37163.18 42686.99 350
旧先验286.56 22158.10 41187.04 5888.98 32874.07 191
JIA-IIPM66.32 39362.82 40576.82 34677.09 42361.72 30465.34 45275.38 42058.04 41264.51 41062.32 45242.05 39986.51 35951.45 39269.22 40682.21 419
pmmvs571.55 34570.20 35075.61 35577.83 41956.39 37381.74 33280.89 37057.76 41367.46 38084.49 33149.26 34085.32 37557.08 35875.29 36185.11 386
TESTMET0.1,169.89 36569.00 35772.55 39279.27 41456.85 36478.38 38474.71 42657.64 41468.09 37477.19 42737.75 42276.70 42663.92 29284.09 23284.10 399
RPMNet73.51 32270.49 34582.58 22581.32 38865.19 21875.92 40592.27 8657.60 41572.73 32276.45 43052.30 29495.43 7448.14 41577.71 31887.11 347
SSC-MVS53.88 41853.59 41854.75 44372.87 44619.59 47673.84 42260.53 46057.58 41649.18 45473.45 44146.34 36475.47 44016.20 46932.28 46269.20 449
新几何183.42 18093.13 5770.71 7785.48 30857.43 41781.80 13891.98 11163.28 16392.27 23464.60 28892.99 7387.27 341
YYNet165.03 39862.91 40371.38 39975.85 42856.60 37069.12 44074.66 42757.28 41854.12 44677.87 42345.85 36974.48 44449.95 40261.52 43183.05 411
MDA-MVSNet_test_wron65.03 39862.92 40271.37 40075.93 42556.73 36669.09 44174.73 42557.28 41854.03 44777.89 42245.88 36874.39 44549.89 40361.55 43082.99 413
Anonymous2023120668.60 37467.80 37271.02 40580.23 39950.75 42878.30 38880.47 37856.79 42066.11 40182.63 37546.35 36378.95 41543.62 43375.70 34883.36 407
tpm273.26 32871.46 33378.63 31183.34 34256.71 36880.65 35080.40 38256.63 42173.55 31282.02 38451.80 30791.24 28056.35 36778.42 31187.95 323
CHOSEN 1792x268877.63 26175.69 27483.44 17989.98 11968.58 12678.70 38087.50 26956.38 42275.80 26386.84 27158.67 23691.40 27561.58 31685.75 20690.34 239
HyFIR lowres test77.53 26275.40 28283.94 16589.59 12766.62 18580.36 35588.64 24356.29 42376.45 24885.17 32057.64 24593.28 17961.34 31983.10 25491.91 180
PVSNet_057.27 2061.67 40859.27 41168.85 41579.61 40957.44 35868.01 44273.44 43055.93 42458.54 43670.41 44744.58 38077.55 42247.01 41935.91 45971.55 447
UnsupCasMVSNet_bld63.70 40361.53 40970.21 40973.69 43951.39 42372.82 42381.89 36055.63 42557.81 43971.80 44438.67 41778.61 41649.26 40752.21 44980.63 430
MDTV_nov1_ep13_2view37.79 46375.16 41255.10 42666.53 39449.34 33853.98 37887.94 324
MVS78.19 24376.99 25281.78 24085.66 28366.99 17984.66 27590.47 15955.08 42772.02 33385.27 31663.83 16094.11 13866.10 27589.80 12984.24 396
test22291.50 8368.26 13484.16 29383.20 34354.63 42879.74 17291.63 12458.97 23391.42 9986.77 355
dongtai45.42 42945.38 43045.55 44773.36 44326.85 47167.72 44334.19 47354.15 42949.65 45356.41 46025.43 44762.94 46319.45 46428.09 46446.86 463
CHOSEN 280x42066.51 39164.71 39371.90 39681.45 38363.52 26757.98 46168.95 44353.57 43062.59 42276.70 42846.22 36575.29 44255.25 37079.68 29476.88 440
ADS-MVSNet266.20 39663.33 40074.82 36879.92 40258.75 33767.55 44475.19 42153.37 43165.25 40675.86 43342.32 39580.53 41041.57 43968.91 40785.18 383
ADS-MVSNet64.36 40162.88 40468.78 41679.92 40247.17 44067.55 44471.18 43553.37 43165.25 40675.86 43342.32 39573.99 44741.57 43968.91 40785.18 383
LF4IMVS64.02 40262.19 40669.50 41170.90 45053.29 40976.13 40277.18 41252.65 43358.59 43580.98 39123.55 45376.52 42853.06 38466.66 41478.68 436
tpm cat170.57 35568.31 36177.35 34182.41 37057.95 34878.08 38980.22 38552.04 43468.54 37177.66 42552.00 30287.84 34651.77 38872.07 39286.25 362
test_vis1_n69.85 36669.21 35571.77 39772.66 44855.27 39181.48 33676.21 41852.03 43575.30 28183.20 36428.97 44376.22 43274.60 18578.41 31283.81 402
Patchmatch-test64.82 40063.24 40169.57 41079.42 41249.82 43263.49 45869.05 44251.98 43659.95 43280.13 40250.91 31670.98 45140.66 44173.57 37887.90 325
N_pmnet52.79 42153.26 41951.40 44578.99 4157.68 47969.52 4363.89 47851.63 43757.01 44174.98 43740.83 40665.96 46037.78 44664.67 42180.56 432
test_fmvs1_n70.86 35270.24 34972.73 39172.51 44955.28 39081.27 34079.71 39051.49 43878.73 18984.87 32627.54 44577.02 42476.06 16779.97 29385.88 373
test_fmvs170.93 35170.52 34472.16 39573.71 43855.05 39280.82 34378.77 39951.21 43978.58 19484.41 33431.20 44076.94 42575.88 17180.12 29284.47 394
PMMVS69.34 36968.67 35871.35 40275.67 42962.03 29875.17 41173.46 42950.00 44068.68 36879.05 41252.07 30178.13 41861.16 32082.77 25773.90 444
test_fmvs268.35 37967.48 37870.98 40669.50 45251.95 41580.05 36176.38 41749.33 44174.65 29884.38 33523.30 45475.40 44174.51 18675.17 36485.60 376
ttmdpeth59.91 41057.10 41468.34 41967.13 45646.65 44374.64 41767.41 44648.30 44262.52 42385.04 32520.40 45675.93 43542.55 43745.90 45782.44 417
CMPMVSbinary51.72 2170.19 36168.16 36376.28 34973.15 44557.55 35679.47 36783.92 32848.02 44356.48 44384.81 32843.13 39086.42 36162.67 30381.81 27084.89 389
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
mvsany_test162.30 40661.26 41065.41 42769.52 45154.86 39466.86 44649.78 46746.65 44468.50 37283.21 36349.15 34166.28 45956.93 36160.77 43275.11 443
kuosan39.70 43340.40 43437.58 45064.52 45926.98 46965.62 45133.02 47446.12 44542.79 45748.99 46324.10 45246.56 47112.16 47226.30 46539.20 464
test_fmvs363.36 40461.82 40767.98 42162.51 46146.96 44277.37 39774.03 42845.24 44667.50 37978.79 41712.16 46672.98 45072.77 20666.02 41783.99 400
CVMVSNet72.99 33372.58 32274.25 37584.28 31850.85 42786.41 22583.45 33744.56 44773.23 31687.54 25549.38 33785.70 36865.90 27778.44 30886.19 364
test_vis1_rt60.28 40958.42 41265.84 42667.25 45555.60 38670.44 43460.94 45944.33 44859.00 43466.64 44924.91 44968.67 45662.80 29969.48 40373.25 445
mvsany_test353.99 41751.45 42261.61 43255.51 46644.74 45163.52 45745.41 47143.69 44958.11 43876.45 43017.99 45963.76 46254.77 37447.59 45376.34 441
EU-MVSNet68.53 37767.61 37671.31 40378.51 41847.01 44184.47 28184.27 32442.27 45066.44 39884.79 32940.44 40883.76 38658.76 34268.54 41083.17 408
FPMVS53.68 41951.64 42159.81 43465.08 45851.03 42569.48 43769.58 44041.46 45140.67 45872.32 44316.46 46270.00 45524.24 46265.42 41958.40 458
pmmvs357.79 41254.26 41768.37 41864.02 46056.72 36775.12 41465.17 45140.20 45252.93 44869.86 44820.36 45775.48 43945.45 42955.25 44572.90 446
new_pmnet50.91 42450.29 42452.78 44468.58 45334.94 46663.71 45656.63 46439.73 45344.95 45565.47 45021.93 45558.48 46434.98 45056.62 43964.92 452
MVS-HIRNet59.14 41157.67 41363.57 42981.65 37843.50 45371.73 42665.06 45239.59 45451.43 44957.73 45738.34 41982.58 39739.53 44273.95 37464.62 453
MVStest156.63 41452.76 42068.25 42061.67 46253.25 41071.67 42768.90 44438.59 45550.59 45183.05 36625.08 44870.66 45236.76 44838.56 45880.83 429
PMMVS240.82 43238.86 43646.69 44653.84 46816.45 47748.61 46449.92 46637.49 45631.67 46160.97 4548.14 47256.42 46628.42 45730.72 46367.19 451
test_vis3_rt49.26 42647.02 42856.00 43854.30 46745.27 44866.76 44848.08 46836.83 45744.38 45653.20 4617.17 47364.07 46156.77 36455.66 44158.65 457
test_f52.09 42250.82 42355.90 43953.82 46942.31 45859.42 46058.31 46336.45 45856.12 44570.96 44612.18 46557.79 46553.51 38156.57 44067.60 450
LCM-MVSNet54.25 41649.68 42667.97 42253.73 47045.28 44766.85 44780.78 37235.96 45939.45 46062.23 4538.70 47078.06 42048.24 41451.20 45080.57 431
APD_test153.31 42049.93 42563.42 43065.68 45750.13 43071.59 42866.90 44834.43 46040.58 45971.56 4458.65 47176.27 43134.64 45155.36 44363.86 454
PMVScopyleft37.38 2244.16 43140.28 43555.82 44040.82 47542.54 45765.12 45363.99 45534.43 46024.48 46657.12 4593.92 47676.17 43317.10 46755.52 44248.75 461
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
Gipumacopyleft45.18 43041.86 43355.16 44277.03 42451.52 42132.50 46780.52 37732.46 46227.12 46535.02 4669.52 46975.50 43822.31 46360.21 43538.45 465
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
DSMNet-mixed57.77 41356.90 41560.38 43367.70 45435.61 46469.18 43853.97 46532.30 46357.49 44079.88 40540.39 40968.57 45738.78 44572.37 38776.97 439
testf145.72 42741.96 43157.00 43656.90 46445.32 44566.14 44959.26 46126.19 46430.89 46360.96 4554.14 47470.64 45326.39 46046.73 45555.04 459
APD_test245.72 42741.96 43157.00 43656.90 46445.32 44566.14 44959.26 46126.19 46430.89 46360.96 4554.14 47470.64 45326.39 46046.73 45555.04 459
E-PMN31.77 43430.64 43735.15 45152.87 47127.67 46857.09 46247.86 46924.64 46616.40 47133.05 46711.23 46754.90 46714.46 47018.15 46822.87 467
EMVS30.81 43629.65 43834.27 45250.96 47225.95 47256.58 46346.80 47024.01 46715.53 47230.68 46812.47 46454.43 46812.81 47117.05 46922.43 468
MVEpermissive26.22 2330.37 43725.89 44143.81 44844.55 47435.46 46528.87 46839.07 47218.20 46818.58 47040.18 4652.68 47747.37 47017.07 46823.78 46748.60 462
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
DeepMVS_CXcopyleft27.40 45340.17 47626.90 47024.59 47717.44 46923.95 46748.61 4649.77 46826.48 47218.06 46524.47 46628.83 466
wuyk23d16.82 44015.94 44319.46 45458.74 46331.45 46739.22 4653.74 4796.84 4706.04 4732.70 4731.27 47824.29 47310.54 47314.40 4722.63 470
test_method31.52 43529.28 43938.23 44927.03 4776.50 48020.94 46962.21 4574.05 47122.35 46952.50 46213.33 46347.58 46927.04 45934.04 46160.62 455
tmp_tt18.61 43921.40 44210.23 4554.82 47810.11 47834.70 46630.74 4761.48 47223.91 46826.07 46928.42 44413.41 47427.12 45815.35 4717.17 469
EGC-MVSNET52.07 42347.05 42767.14 42383.51 33960.71 31680.50 35367.75 4450.07 4730.43 47475.85 43524.26 45181.54 40328.82 45662.25 42859.16 456
testmvs6.04 4438.02 4460.10 4570.08 4790.03 48269.74 4350.04 4800.05 4740.31 4751.68 4740.02 4800.04 4750.24 4740.02 4730.25 472
test1236.12 4428.11 4450.14 4560.06 4800.09 48171.05 4300.03 4810.04 4750.25 4761.30 4750.05 4790.03 4760.21 4750.01 4740.29 471
mmdepth0.00 4450.00 4480.00 4580.00 4810.00 4830.00 4700.00 4820.00 4760.00 4770.00 4760.00 4810.00 4770.00 4760.00 4750.00 473
monomultidepth0.00 4450.00 4480.00 4580.00 4810.00 4830.00 4700.00 4820.00 4760.00 4770.00 4760.00 4810.00 4770.00 4760.00 4750.00 473
test_blank0.00 4450.00 4480.00 4580.00 4810.00 4830.00 4700.00 4820.00 4760.00 4770.00 4760.00 4810.00 4770.00 4760.00 4750.00 473
uanet_test0.00 4450.00 4480.00 4580.00 4810.00 4830.00 4700.00 4820.00 4760.00 4770.00 4760.00 4810.00 4770.00 4760.00 4750.00 473
DCPMVS0.00 4450.00 4480.00 4580.00 4810.00 4830.00 4700.00 4820.00 4760.00 4770.00 4760.00 4810.00 4770.00 4760.00 4750.00 473
cdsmvs_eth3d_5k19.96 43826.61 4400.00 4580.00 4810.00 4830.00 47089.26 2110.00 4760.00 47788.61 22261.62 1970.00 4770.00 4760.00 4750.00 473
pcd_1.5k_mvsjas5.26 4447.02 4470.00 4580.00 4810.00 4830.00 4700.00 4820.00 4760.00 4770.00 47663.15 1690.00 4770.00 4760.00 4750.00 473
sosnet-low-res0.00 4450.00 4480.00 4580.00 4810.00 4830.00 4700.00 4820.00 4760.00 4770.00 4760.00 4810.00 4770.00 4760.00 4750.00 473
sosnet0.00 4450.00 4480.00 4580.00 4810.00 4830.00 4700.00 4820.00 4760.00 4770.00 4760.00 4810.00 4770.00 4760.00 4750.00 473
uncertanet0.00 4450.00 4480.00 4580.00 4810.00 4830.00 4700.00 4820.00 4760.00 4770.00 4760.00 4810.00 4770.00 4760.00 4750.00 473
Regformer0.00 4450.00 4480.00 4580.00 4810.00 4830.00 4700.00 4820.00 4760.00 4770.00 4760.00 4810.00 4770.00 4760.00 4750.00 473
ab-mvs-re7.23 4419.64 4440.00 4580.00 4810.00 4830.00 4700.00 4820.00 4760.00 47786.72 2750.00 4810.00 4770.00 4760.00 4750.00 473
uanet0.00 4450.00 4480.00 4580.00 4810.00 4830.00 4700.00 4820.00 4760.00 4770.00 4760.00 4810.00 4770.00 4760.00 4750.00 473
TestfortrainingZip93.28 12
WAC-MVS42.58 45539.46 443
MSC_two_6792asdad89.16 194.34 2875.53 292.99 5197.53 289.67 1596.44 994.41 47
No_MVS89.16 194.34 2875.53 292.99 5197.53 289.67 1596.44 994.41 47
eth-test20.00 481
eth-test0.00 481
OPU-MVS89.06 394.62 1575.42 493.57 894.02 5782.45 396.87 2183.77 7896.48 894.88 16
test_0728_SECOND87.71 3395.34 171.43 6093.49 1094.23 497.49 489.08 2296.41 1294.21 59
GSMVS88.96 296
test_part295.06 872.65 3291.80 13
sam_mvs151.32 31288.96 296
sam_mvs50.01 328
ambc75.24 36373.16 44450.51 42963.05 45987.47 27064.28 41177.81 42417.80 46089.73 31357.88 35160.64 43385.49 377
MTGPAbinary92.02 100
test_post178.90 3785.43 47248.81 34785.44 37459.25 335
test_post5.46 47150.36 32484.24 383
patchmatchnet-post74.00 43951.12 31588.60 336
GG-mvs-BLEND75.38 36181.59 38055.80 38379.32 36969.63 43967.19 38473.67 44043.24 38988.90 33250.41 39684.50 22281.45 425
MTMP92.18 3632.83 475
test9_res84.90 6095.70 2792.87 139
agg_prior282.91 8795.45 3092.70 144
agg_prior92.85 6571.94 5291.78 11684.41 9194.93 98
test_prior472.60 3489.01 121
test_prior86.33 6192.61 7169.59 9592.97 5695.48 7193.91 75
新几何286.29 232
旧先验191.96 7765.79 20486.37 29593.08 8869.31 9292.74 7788.74 307
原ACMM286.86 208
testdata291.01 29062.37 306
segment_acmp73.08 41
test1286.80 5592.63 7070.70 7891.79 11582.71 12571.67 6096.16 4994.50 5493.54 104
plane_prior790.08 11368.51 128
plane_prior689.84 12268.70 12260.42 223
plane_prior592.44 7995.38 7978.71 13286.32 19091.33 199
plane_prior491.00 151
plane_prior189.90 121
n20.00 482
nn0.00 482
door-mid69.98 438
lessismore_v078.97 30681.01 39157.15 36165.99 44961.16 42682.82 37239.12 41491.34 27759.67 33146.92 45488.43 315
test1192.23 89
door69.44 441
HQP5-MVS66.98 180
BP-MVS77.47 147
HQP4-MVS77.24 22795.11 9191.03 209
HQP3-MVS92.19 9485.99 199
HQP2-MVS60.17 226
NP-MVS89.62 12668.32 13290.24 172
ACMMP++_ref81.95 268
ACMMP++81.25 273
Test By Simon64.33 155