High-res multi-view results

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

Accuracy [%]: The fraction of the reconstruction which is closer to the ground truth than the evaluation threshold distance (*). Larger is better.
Completeness [%]: The fraction of the ground truth which is closer to the reconstruction than the evaluation threshold distance (*). Larger is better.
F₁ score [%]: The harmonic mean of accuracy and completeness, used to rank methods based on both metrics. Larger is better.
Time [s]: The runtime of the method. Smaller is better.

(*) For exact definitions, detailing how potentially incomplete ground truth is taken into account, see our paper.

The datasets are grouped into different categories, and result averages are computed for a category and method if results of the method are available for all datasets within the category. Note that the category "all" includes both the high-res multi-view and the low-res many-view scenarios.

Methods with suffix _ROB may participate in the Robust Vision Challenge.

Click a dataset result cell to show a visualization of the reconstruction. For training datasets, ground truth and accuracy / completeness visualizations are also available. The visualizations may not work with mobile browsers.

Method	all	high-res multi-view	indoor	outdoor	courty.	delive.	electro	facade	kicker	meadow	office	pipes	playgr.	relief	relief.	terrace	terrai.

ESAPD		88.63 1	91.29 1	85.53 1	90.87 7	92.20 1	91.98 2	76.00 4	90.55 4	82.09 4	93.85 1	90.75 1	81.25 1	88.62 6	87.59 11	90.96 7	95.48 1

APDe-MVS		88.00 2	90.50 2	85.08 3	90.95 6	91.58 5	92.03 1	75.53 9	91.15 1	80.10 11	92.27 4	88.34 8	80.80 3	88.00 12	86.99 16	91.09 4	95.16 4

SMA-MVS		87.56 3	90.17 4	84.52 5	91.71 3	90.57 6	90.77 5	75.19 10	90.67 3	80.50 9	86.59 14	88.86 5	78.09 13	89.92 1	89.41 1	90.84 8	95.19 3

HSP-MVS		87.45 4	90.22 3	84.22 9	90.00 20	91.80 4	90.59 6	75.80 5	89.93 6	78.35 17	92.54 3	89.18 4	80.89 2	87.99 13	86.29 28	89.70 38	93.85 10

HPM-MVS++		87.09 5	88.92 9	84.95 4	92.61 1	87.91 37	90.23 12	76.06 3	88.85 9	81.20 5	87.33 10	87.93 9	79.47 7	88.59 7	88.23 5	90.15 30	93.60 17

SD-MVS		86.96 6	89.45 5	84.05 12	90.13 17	89.23 19	89.77 15	74.59 11	89.17 7	80.70 6	89.93 8	89.67 3	78.47 9	87.57 17	86.79 20	90.67 14	93.76 13

TSAR-MVS + MP.		86.88 7	89.23 6	84.14 10	89.78 23	88.67 28	90.59 6	73.46 24	88.99 8	80.52 8	91.26 5	88.65 6	79.91 6	86.96 27	86.22 29	90.59 15	93.83 11

APD-MVS		86.84 8	88.91 10	84.41 6	90.66 10	90.10 9	90.78 4	75.64 6	87.38 14	78.72 15	90.68 7	86.82 13	80.15 5	87.13 22	86.45 26	90.51 17	93.83 11
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
ACMMP_NAP		86.52 9	89.01 7	83.62 14	90.28 16	90.09 10	90.32 10	74.05 17	88.32 11	79.74 12	87.04 12	85.59 20	76.97 26	89.35 2	88.44 4	90.35 26	94.27 8

CNVR-MVS		86.36 10	88.19 13	84.23 8	91.33 5	89.84 11	90.34 8	75.56 7	87.36 15	78.97 14	81.19 25	86.76 14	78.74 8	89.30 3	88.58 2	90.45 23	94.33 7

HFP-MVS		86.15 11	87.95 14	84.06 11	90.80 8	89.20 20	89.62 17	74.26 13	87.52 12	80.63 7	86.82 13	84.19 26	78.22 11	87.58 16	87.19 14	90.81 9	93.13 21

SteuartSystems-ACMMP		85.99 12	88.31 12	83.27 18	90.73 9	89.84 11	90.27 11	74.31 12	84.56 27	75.88 27	87.32 11	85.04 21	77.31 21	89.01 4	88.46 3	91.14 3	93.96 9
Skip Steuart: Steuart Systems R&D Blog.
zzz-MVS		85.71 13	86.88 19	84.34 7	90.54 14	87.11 41	89.77 15	74.17 15	88.54 10	83.08 2	78.60 29	86.10 16	78.11 12	87.80 15	87.46 12	90.35 26	92.56 23

ACMMPR		85.52 14	87.53 16	83.17 19	90.13 17	89.27 17	89.30 18	73.97 18	86.89 17	77.14 22	86.09 15	83.18 29	77.74 17	87.42 18	87.20 13	90.77 10	92.63 22

MP-MVS		85.50 15	87.40 17	83.28 17	90.65 11	89.51 16	89.16 21	74.11 16	83.70 31	78.06 19	85.54 17	84.89 24	77.31 21	87.40 19	87.14 15	90.41 24	93.65 16
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
NCCC		85.34 16	86.59 21	83.88 13	91.48 4	88.88 22	89.79 14	75.54 8	86.67 18	77.94 20	76.55 32	84.99 22	78.07 14	88.04 10	87.68 8	90.46 22	93.31 18

DeepPCF-MVS	79.04 1	85.30 17	88.93 8	81.06 29	88.77 33	90.48 7	85.46 44	73.08 26	90.97 2	73.77 34	84.81 19	85.95 17	77.43 20	88.22 9	87.73 7	87.85 71	94.34 6

CSCG		85.28 18	87.68 15	82.49 22	89.95 21	91.99 3	88.82 22	71.20 35	86.41 19	79.63 13	79.26 26	88.36 7	73.94 36	86.64 29	86.67 23	91.40 2	94.41 5

MCST-MVS		85.13 19	86.62 20	83.39 15	90.55 13	89.82 13	89.29 19	73.89 20	84.38 28	76.03 26	79.01 28	85.90 18	78.47 9	87.81 14	86.11 31	92.11 1	93.29 19

TSAR-MVS + ACMM		85.10 20	88.81 11	80.77 32	89.55 26	88.53 30	88.59 25	72.55 28	87.39 13	71.90 41	90.95 6	87.55 10	74.57 31	87.08 24	86.54 24	87.47 78	93.67 14

train_agg		84.86 21	87.21 18	82.11 24	90.59 12	85.47 54	89.81 13	73.55 23	83.95 29	73.30 35	89.84 9	87.23 12	75.61 29	86.47 31	85.46 36	89.78 34	92.06 29

DeepC-MVS	78.47 2	84.81 22	86.03 25	83.37 16	89.29 29	90.38 8	88.61 24	76.50 2	86.25 20	77.22 21	75.12 36	80.28 42	77.59 19	88.39 8	88.17 6	91.02 5	93.66 15
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
CP-MVS		84.74 23	86.43 23	82.77 21	89.48 27	88.13 36	88.64 23	73.93 19	84.92 22	76.77 23	81.94 23	83.50 27	77.29 23	86.92 28	86.49 25	90.49 18	93.14 20

PGM-MVS		84.42 24	86.29 24	82.23 23	90.04 19	88.82 24	89.23 20	71.74 33	82.82 34	74.61 30	84.41 20	82.09 32	77.03 25	87.13 22	86.73 22	90.73 12	92.06 29

DeepC-MVS_fast	78.24 3	84.27 25	85.50 27	82.85 20	90.46 15	89.24 18	87.83 30	74.24 14	84.88 23	76.23 25	75.26 35	81.05 40	77.62 18	88.02 11	87.62 10	90.69 13	92.41 25
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
TSAR-MVS + GP.		83.69 26	86.58 22	80.32 33	85.14 52	86.96 43	84.91 48	70.25 39	84.71 26	73.91 33	85.16 18	85.63 19	77.92 15	85.44 38	85.71 34	89.77 35	92.45 24

ACMMP		83.42 27	85.27 28	81.26 28	88.47 34	88.49 31	88.31 28	72.09 30	83.42 32	72.77 38	82.65 21	78.22 46	75.18 30	86.24 35	85.76 33	90.74 11	92.13 28
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
DPM-MVS		83.30 28	84.33 31	82.11 24	89.56 25	88.49 31	90.33 9	73.24 25	83.85 30	76.46 24	72.43 46	82.65 30	73.02 43	86.37 33	86.91 17	90.03 32	89.62 48

X-MVS		83.23 29	85.20 29	80.92 31	89.71 24	88.68 25	88.21 29	73.60 21	82.57 35	71.81 44	77.07 30	81.92 34	71.72 54	86.98 26	86.86 18	90.47 19	92.36 26

CDPH-MVS		82.64 30	85.03 30	79.86 36	89.41 28	88.31 33	88.32 27	71.84 32	80.11 42	67.47 60	82.09 22	81.44 38	71.85 52	85.89 37	86.15 30	90.24 28	91.25 35

3Dnovator+	75.73 4	82.40 31	82.76 36	81.97 26	88.02 35	89.67 14	86.60 34	71.48 34	81.28 40	78.18 18	64.78 76	77.96 48	77.13 24	87.32 20	86.83 19	90.41 24	91.48 33

PHI-MVS		82.36 32	85.89 26	78.24 46	86.40 45	89.52 15	85.52 42	69.52 46	82.38 37	65.67 65	81.35 24	82.36 31	73.07 42	87.31 21	86.76 21	89.24 45	91.56 32

MSLP-MVS++		82.09 33	82.66 37	81.42 27	87.03 41	87.22 40	85.82 39	70.04 40	80.30 41	78.66 16	68.67 62	81.04 41	77.81 16	85.19 41	84.88 41	89.19 47	91.31 34

CPTT-MVS		81.77 34	83.10 35	80.21 34	85.93 48	86.45 48	87.72 31	70.98 36	82.54 36	71.53 47	74.23 41	81.49 37	76.31 28	82.85 59	81.87 55	88.79 54	92.26 27

MVS_0304		81.73 35	83.86 32	79.26 39	86.22 47	89.18 21	86.41 35	67.15 60	75.28 54	70.75 51	74.59 38	83.49 28	74.42 33	87.05 25	86.34 27	90.58 16	91.08 37

CANet		81.62 36	83.41 33	79.53 38	87.06 40	88.59 29	85.47 43	67.96 56	76.59 51	74.05 31	74.69 37	81.98 33	72.98 44	86.14 36	85.47 35	89.68 39	90.42 43

HQP-MVS		81.19 37	83.27 34	78.76 43	87.40 38	85.45 55	86.95 32	70.47 38	81.31 39	66.91 63	79.24 27	76.63 51	71.67 55	84.43 45	83.78 46	89.19 47	92.05 31

v1.0		81.11 38	77.43 65	85.41 2	91.73 2	92.08 2	91.91 3	76.73 1	90.14 5	80.33 10	92.75 2	90.44 2	80.73 4	88.97 5	87.63 9	91.01 6	0.00 250

OMC-MVS		80.26 39	82.59 38	77.54 50	83.04 61	85.54 53	83.25 56	65.05 74	87.32 16	72.42 39	72.04 48	78.97 44	73.30 39	83.86 48	81.60 58	88.15 62	88.83 53

MVS_111021_HR		80.13 40	81.46 41	78.58 44	85.77 49	85.17 58	83.45 55	69.28 47	74.08 60	70.31 52	74.31 40	75.26 56	73.13 41	86.46 32	85.15 39	89.53 41	89.81 46

LGP-MVS_train		79.83 41	81.22 43	78.22 47	86.28 46	85.36 57	86.76 33	69.59 44	77.34 48	65.14 67	75.68 34	70.79 72	71.37 57	84.60 43	84.01 44	90.18 29	90.74 39

ACMP	73.23 7	79.79 42	80.53 47	78.94 41	85.61 50	85.68 52	85.61 41	69.59 44	77.33 49	71.00 50	74.45 39	69.16 83	71.88 50	83.15 56	83.37 49	89.92 33	90.57 42
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
3Dnovator	73.76 5	79.75 43	80.52 48	78.84 42	84.94 57	87.35 38	84.43 51	65.54 70	78.29 47	73.97 32	63.00 84	75.62 55	74.07 35	85.00 42	85.34 37	90.11 31	89.04 51

AdaColmap		79.74 44	78.62 57	81.05 30	89.23 30	86.06 51	84.95 47	71.96 31	79.39 45	75.51 28	63.16 82	68.84 88	76.51 27	83.55 52	82.85 51	88.13 63	86.46 70

OPM-MVS		79.68 45	79.28 54	80.15 35	87.99 36	86.77 45	88.52 26	72.72 27	64.55 88	67.65 59	67.87 66	74.33 60	74.31 34	86.37 33	85.25 38	89.73 37	89.81 46

casdiffmvs1		79.56 46	81.02 45	77.86 49	84.19 59	87.00 42	85.73 40	63.24 86	79.22 46	72.05 40	73.55 43	76.93 50	73.25 40	80.92 80	80.20 81	88.69 56	89.31 50

PCF-MVS	73.28 6	79.42 47	80.41 49	78.26 45	84.88 58	88.17 34	86.08 36	69.85 41	75.23 56	68.43 55	68.03 65	78.38 45	71.76 53	81.26 74	80.65 75	88.56 59	91.18 36
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
CLD-MVS		79.35 48	81.23 42	77.16 52	85.01 55	86.92 44	85.87 38	60.89 129	80.07 44	75.35 29	72.96 44	73.21 63	68.43 70	85.41 40	84.63 42	87.41 79	85.44 82
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
MAR-MVS		79.21 49	80.32 50	77.92 48	87.46 37	88.15 35	83.95 52	67.48 59	74.28 58	68.25 56	64.70 77	77.04 49	72.17 48	85.42 39	85.00 40	88.22 60	87.62 62
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
canonicalmvs		79.16 50	82.37 39	75.41 59	82.33 67	86.38 50	80.80 61	63.18 87	82.90 33	67.34 61	72.79 45	76.07 53	69.62 63	83.46 55	84.41 43	89.20 46	90.60 41

DELS-MVS		79.15 51	81.07 44	76.91 54	83.54 60	87.31 39	84.45 49	64.92 75	69.98 65	69.34 54	71.62 50	76.26 52	69.84 62	86.57 30	85.90 32	89.39 43	89.88 45
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
EPNet		79.08 52	80.62 46	77.28 51	88.90 32	83.17 71	83.65 53	72.41 29	74.41 57	67.15 62	76.78 31	74.37 59	64.43 106	83.70 51	83.69 47	87.15 84	88.19 55
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
ACMM	72.26 8	78.86 53	78.13 58	79.71 37	86.89 42	83.40 68	86.02 37	70.50 37	75.28 54	71.49 48	63.01 83	69.26 82	73.57 38	84.11 47	83.98 45	89.76 36	87.84 59
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
QAPM		78.47 54	80.22 51	76.43 56	85.03 54	86.75 46	80.62 63	66.00 67	73.77 61	65.35 66	65.54 73	78.02 47	72.69 45	83.71 50	83.36 50	88.87 53	90.41 44

TSAR-MVS + COLMAP		78.34 55	81.64 40	74.48 66	80.13 81	85.01 59	81.73 57	65.93 69	84.75 25	61.68 77	85.79 16	66.27 95	71.39 56	82.91 58	80.78 66	86.01 138	85.98 72

MVS_111021_LR		78.13 56	79.85 53	76.13 57	81.12 71	81.50 82	80.28 64	65.25 72	76.09 53	71.32 49	76.49 33	72.87 65	72.21 47	82.79 60	81.29 60	86.59 120	87.91 58

casdiffmvs		77.90 57	78.63 56	77.06 53	82.85 63	86.44 49	84.45 49	64.35 79	71.84 63	69.93 53	70.80 53	72.99 64	72.00 49	80.84 82	79.80 87	88.76 55	87.71 61

TAPA-MVS	71.42 9	77.69 58	80.05 52	74.94 62	80.68 75	84.52 61	81.36 58	63.14 88	84.77 24	64.82 69	68.72 60	75.91 54	71.86 51	81.62 64	79.55 93	87.80 73	85.24 85
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
CNLPA		77.20 59	77.54 62	76.80 55	82.63 64	84.31 62	79.77 67	64.64 76	85.17 21	73.18 36	56.37 118	69.81 79	74.53 32	81.12 77	78.69 101	86.04 137	87.29 66

PVSNet_Blended_VisFu		76.57 60	77.90 59	75.02 61	80.56 76	86.58 47	79.24 72	66.18 64	64.81 85	68.18 57	65.61 71	71.45 68	67.05 73	84.16 46	81.80 56	88.90 51	90.92 38

PVSNet_BlendedMVS		76.21 61	77.52 63	74.69 64	79.46 83	83.79 65	77.50 105	64.34 80	69.88 66	71.88 42	68.54 63	70.42 75	67.05 73	83.48 53	79.63 89	87.89 69	86.87 68

PVSNet_Blended		76.21 61	77.52 63	74.69 64	79.46 83	83.79 65	77.50 105	64.34 80	69.88 66	71.88 42	68.54 63	70.42 75	67.05 73	83.48 53	79.63 89	87.89 69	86.87 68

OpenMVS	70.44 10	76.15 63	76.82 71	75.37 60	85.01 55	84.79 60	78.99 77	62.07 115	71.27 64	67.88 58	57.91 110	72.36 66	70.15 61	82.23 62	81.41 59	88.12 64	87.78 60

diffmvs1		76.02 64	78.90 55	72.65 72	77.84 96	82.90 73	80.67 62	60.86 131	76.16 52	63.35 74	71.50 51	74.85 57	68.35 71	80.22 99	78.69 101	84.87 165	88.00 57

PLC	68.99 11	75.68 65	75.31 76	76.12 58	82.94 62	81.26 85	79.94 66	66.10 65	77.15 50	66.86 64	59.13 99	68.53 89	73.73 37	80.38 90	79.04 97	87.13 88	81.68 135
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
MVS_Test		75.37 66	77.13 69	73.31 70	79.07 86	81.32 84	79.98 65	60.12 150	69.72 68	64.11 71	70.53 54	73.22 62	68.90 66	80.14 101	79.48 95	87.67 75	85.50 80

Effi-MVS+		75.28 67	76.20 73	74.20 67	81.15 70	83.24 69	81.11 59	63.13 89	66.37 74	60.27 82	64.30 80	68.88 87	70.93 60	81.56 66	81.69 57	88.61 57	87.35 64

DI_MVS_plusplus_trai		75.13 68	76.12 74	73.96 68	78.18 91	81.55 80	80.97 60	62.54 109	68.59 70	65.13 68	61.43 85	74.81 58	69.32 65	81.01 79	79.59 91	87.64 76	85.89 73

UA-Net		74.47 69	77.80 60	70.59 91	85.33 51	85.40 56	73.54 149	65.98 68	60.65 117	56.00 116	72.11 47	79.15 43	54.63 178	83.13 57	82.25 53	88.04 65	81.92 133

diffmvs		74.38 70	76.65 72	71.74 75	77.05 113	81.86 78	79.30 71	60.54 135	69.54 69	62.16 75	69.70 57	70.74 73	66.73 81	79.18 115	78.14 114	84.63 169	87.42 63

LS3D		74.08 71	73.39 81	74.88 63	85.05 53	82.62 75	79.71 68	68.66 50	72.82 62	58.80 88	57.61 111	61.31 108	71.07 59	80.32 94	78.87 100	86.00 140	80.18 150

EPP-MVSNet		74.00 72	77.41 66	70.02 105	80.53 77	83.91 64	74.99 125	62.68 105	65.06 83	49.77 154	68.68 61	72.09 67	63.06 115	82.49 61	80.73 67	89.12 49	88.91 52

DCV-MVSNet		73.65 73	75.78 75	71.16 78	80.19 79	79.27 110	77.45 107	61.68 121	66.73 73	58.72 89	65.31 74	69.96 78	62.19 120	81.29 73	80.97 63	86.74 112	86.91 67

IS_MVSNet		73.33 74	77.34 67	68.65 120	81.29 69	83.47 67	74.45 129	63.58 84	65.75 80	48.49 158	67.11 70	70.61 74	54.63 178	84.51 44	83.58 48	89.48 42	86.34 71

CANet_DTU		73.29 75	76.96 70	69.00 116	77.04 114	82.06 77	79.49 70	56.30 185	67.85 71	53.29 132	71.12 52	70.37 77	61.81 128	81.59 65	80.96 64	86.09 132	84.73 94

Fast-Effi-MVS+		73.11 76	73.66 79	72.48 73	77.72 106	80.88 91	78.55 92	58.83 170	65.19 82	60.36 81	59.98 94	62.42 106	71.22 58	81.66 63	80.61 77	88.20 61	84.88 93

UGNet		72.78 77	77.67 61	67.07 144	71.65 182	83.24 69	75.20 119	63.62 83	64.93 84	56.72 110	71.82 49	73.30 61	49.02 194	81.02 78	80.70 73	86.22 125	88.67 54
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
Vis-MVSNet		72.77 78	77.20 68	67.59 131	74.19 158	84.01 63	76.61 115	61.69 120	60.62 118	50.61 148	70.25 56	71.31 70	55.57 173	83.85 49	82.28 52	86.90 98	88.08 56
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
FC-MVSNet-train		72.60 79	75.07 77	69.71 109	81.10 72	78.79 120	73.74 147	65.23 73	66.10 77	53.34 131	70.36 55	63.40 103	56.92 158	81.44 67	80.96 64	87.93 67	84.46 98

MVSTER		72.06 80	74.24 78	69.51 112	70.39 192	75.97 164	76.91 111	57.36 180	64.64 87	61.39 79	68.86 59	63.76 101	63.46 111	81.44 67	79.70 88	87.56 77	85.31 84

Anonymous20231211		71.90 81	72.48 89	71.21 77	80.14 80	81.53 81	76.92 110	62.89 92	64.46 89	58.94 86	43.80 209	70.98 71	62.22 119	80.70 83	80.19 83	86.18 126	85.73 74

Effi-MVS+-dtu		71.82 82	71.86 93	71.78 74	78.77 87	80.47 100	78.55 92	61.67 122	60.68 116	55.49 117	58.48 103	65.48 97	68.85 67	76.92 155	75.55 170	87.35 80	85.46 81

IterMVS-LS		71.69 83	72.82 87	70.37 100	77.54 108	76.34 160	75.13 123	60.46 138	61.53 112	57.57 99	64.89 75	67.33 92	66.04 99	77.09 154	77.37 130	85.48 154	85.18 86
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
MSDG		71.52 84	69.87 107	73.44 69	82.21 68	79.35 109	79.52 69	64.59 77	66.15 76	61.87 76	53.21 167	56.09 144	65.85 103	78.94 117	78.50 103	86.60 119	76.85 178

thisisatest0530		71.48 85	73.01 84	69.70 110	73.83 163	78.62 123	74.53 128	59.12 159	64.13 90	58.63 91	64.60 78	58.63 118	64.27 107	80.28 96	80.17 84	87.82 72	84.64 96

tttt0517		71.41 86	72.95 85	69.60 111	73.70 165	78.70 121	74.42 132	59.12 159	63.89 94	58.35 93	64.56 79	58.39 120	64.27 107	80.29 95	80.17 84	87.74 74	84.69 95

ACMH+	66.54 13	71.36 87	70.09 102	72.85 71	82.59 65	81.13 86	78.56 91	68.04 54	61.55 111	52.52 138	51.50 186	54.14 158	68.56 69	78.85 118	79.50 94	86.82 105	83.94 103

IB-MVS	66.94 12	71.21 88	71.66 94	70.68 88	79.18 85	82.83 74	72.61 156	61.77 119	59.66 124	63.44 73	53.26 165	59.65 115	59.16 142	76.78 158	82.11 54	87.90 68	87.33 65
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
GBi-Net		70.78 89	73.37 82	67.76 125	72.95 170	78.00 130	75.15 120	62.72 100	64.13 90	51.44 140	58.37 104	69.02 84	57.59 150	81.33 70	80.72 68	86.70 114	82.02 127

test1		70.78 89	73.37 82	67.76 125	72.95 170	78.00 130	75.15 120	62.72 100	64.13 90	51.44 140	58.37 104	69.02 84	57.59 150	81.33 70	80.72 68	86.70 114	82.02 127

ACMH	65.37 14	70.71 91	70.00 103	71.54 76	82.51 66	82.47 76	77.78 102	68.13 53	56.19 167	46.06 175	54.30 146	51.20 195	68.68 68	80.66 84	80.72 68	86.07 133	84.45 99
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
UniMVSNet_NR-MVSNet		70.59 92	72.19 90	68.72 118	77.72 106	80.72 92	73.81 145	69.65 43	61.99 106	43.23 186	60.54 90	57.50 123	58.57 143	79.56 109	81.07 62	89.34 44	83.97 101

FMVSNet3		70.49 93	72.90 86	67.67 129	72.88 173	77.98 133	74.96 126	62.72 100	64.13 90	51.44 140	58.37 104	69.02 84	57.43 153	79.43 111	79.57 92	86.59 120	81.81 134

FMVSNet2		70.39 94	72.67 88	67.72 128	72.95 170	78.00 130	75.15 120	62.69 104	63.29 98	51.25 144	55.64 122	68.49 90	57.59 150	80.91 81	80.35 80	86.70 114	82.02 127

v6		70.35 95	69.94 104	70.83 80	74.68 151	80.62 93	78.81 82	60.16 148	58.81 129	58.17 95	55.01 132	57.31 128	66.32 92	77.53 138	76.73 149	86.82 105	83.62 106

v1neww		70.34 96	69.93 105	70.82 81	74.68 151	80.61 94	78.80 83	60.17 145	58.74 131	58.10 96	55.00 133	57.28 129	66.33 90	77.53 138	76.74 145	86.82 105	83.61 107

v7new		70.34 96	69.93 105	70.82 81	74.68 151	80.61 94	78.80 83	60.17 145	58.74 131	58.10 96	55.00 133	57.28 129	66.33 90	77.53 138	76.74 145	86.82 105	83.61 107

v7		70.33 98	69.87 107	70.88 79	74.79 143	81.04 87	79.22 73	60.57 134	57.70 141	56.65 112	54.23 151	55.29 149	66.95 76	78.28 124	77.47 126	87.12 91	85.05 89

v8		70.23 99	69.86 109	70.67 89	74.69 150	79.82 105	78.79 85	59.18 158	58.80 130	58.20 94	55.00 133	57.33 126	66.31 93	77.51 141	76.71 153	86.82 105	83.88 104

v10		70.22 100	69.76 111	70.74 85	74.79 143	80.30 103	79.22 73	59.81 153	57.71 140	56.58 113	54.22 153	55.31 147	66.95 76	78.28 124	77.47 126	87.12 91	85.07 88

MS-PatchMatch		70.17 101	70.49 100	69.79 107	80.98 73	77.97 135	77.51 104	58.95 162	62.33 104	55.22 120	53.14 168	65.90 96	62.03 123	79.08 116	77.11 134	84.08 174	77.91 168

v18		70.10 102	69.52 114	70.77 84	74.66 154	77.06 145	78.84 80	58.84 169	60.01 122	59.23 84	55.06 131	57.47 124	66.34 89	77.50 142	76.75 143	86.71 113	82.77 121

v16		70.07 103	69.46 116	70.79 83	74.74 149	77.08 144	78.79 85	58.86 164	59.75 123	59.15 85	54.87 138	57.33 126	66.38 87	77.61 136	76.77 138	86.81 110	82.79 119

v2v482		70.05 104	69.46 116	70.74 85	74.62 155	80.32 102	79.00 76	60.62 133	57.41 143	56.89 105	55.43 126	55.14 150	66.39 86	77.25 150	77.14 133	86.90 98	83.57 112

v17		70.03 105	69.43 121	70.72 87	74.75 148	77.09 143	78.78 87	58.85 166	59.53 126	58.72 89	54.87 138	57.39 125	66.38 87	77.60 137	76.75 143	86.83 104	82.80 117

divwei89l23v2f112		69.97 106	69.44 119	70.58 93	74.78 145	80.50 98	78.85 78	60.30 140	56.97 148	56.75 108	54.67 143	56.27 140	65.92 101	77.37 145	76.72 150	86.88 101	83.58 111

v1		69.97 106	69.45 118	70.59 91	74.78 145	80.51 97	78.84 80	60.30 140	56.98 146	56.81 107	54.69 141	56.29 139	65.91 102	77.37 145	76.71 153	86.89 100	83.59 109

v1141		69.96 108	69.44 119	70.58 93	74.78 145	80.50 98	78.85 78	60.30 140	56.95 149	56.74 109	54.68 142	56.26 141	65.93 100	77.38 144	76.72 150	86.88 101	83.57 112

v1144		69.93 109	69.36 122	70.61 90	74.89 136	80.93 88	79.11 75	60.64 132	55.97 170	55.31 119	53.85 158	54.14 158	66.54 84	78.10 127	77.44 128	87.14 87	85.09 87

DU-MVS		69.63 110	70.91 97	68.13 124	75.99 124	79.54 106	73.81 145	69.20 48	61.20 114	43.23 186	58.52 101	53.50 165	58.57 143	79.22 113	80.45 78	87.97 66	83.97 101

v15		69.61 111	68.88 129	70.46 95	74.81 142	77.03 148	78.75 88	58.83 170	57.06 145	57.18 101	54.55 144	56.37 135	66.13 97	77.70 133	76.76 140	87.03 95	82.69 124

V14		69.59 112	68.86 130	70.45 97	74.83 141	77.04 146	78.70 89	58.83 170	56.95 149	57.08 103	54.41 145	56.34 136	66.15 94	77.77 132	76.76 140	87.08 93	82.74 122

V9		69.58 113	68.83 131	70.46 95	74.85 140	77.04 146	78.65 90	58.85 166	56.83 152	57.12 102	54.26 149	56.31 137	66.14 96	77.83 131	76.76 140	87.13 88	82.79 119

v12		69.54 114	68.79 133	70.41 98	74.88 137	77.03 148	78.54 95	58.85 166	56.71 153	56.87 106	54.13 154	56.23 142	66.15 94	77.89 129	76.74 145	87.17 83	82.80 117

UniMVSNet (Re)		69.53 115	71.90 92	66.76 150	76.42 117	80.93 88	72.59 157	68.03 55	61.75 110	41.68 194	58.34 107	57.23 131	53.27 185	79.53 110	80.62 76	88.57 58	84.90 92

v13		69.52 116	68.76 136	70.41 98	74.88 137	77.02 150	78.52 96	58.86 164	56.61 161	56.91 104	54.00 156	56.17 143	66.11 98	77.93 128	76.74 145	87.21 82	82.83 116

v1192		69.50 117	68.83 131	70.29 101	74.49 156	80.92 90	78.55 92	60.54 135	55.04 179	54.21 122	52.79 175	52.33 183	66.92 78	77.88 130	77.35 131	87.04 94	85.51 79

HyFIR lowres test		69.47 118	68.94 128	70.09 104	76.77 116	82.93 72	76.63 114	60.17 145	59.00 128	54.03 125	40.54 219	65.23 98	67.89 72	76.54 162	78.30 110	85.03 160	80.07 151

v11		69.37 119	68.65 140	70.20 102	74.87 139	76.97 151	78.29 99	58.55 174	56.38 164	56.04 115	54.02 155	54.98 151	66.47 85	78.30 123	76.91 136	86.97 96	83.02 115

v144192		69.34 120	68.68 139	70.12 103	74.06 159	80.54 96	78.08 101	60.54 135	54.99 181	54.13 124	52.92 172	52.80 179	66.73 81	77.13 152	76.72 150	87.15 84	85.63 75

TranMVSNet+NR-MVSNet		69.25 121	70.81 98	67.43 132	77.23 112	79.46 108	73.48 151	69.66 42	60.43 119	39.56 198	58.82 100	53.48 167	55.74 171	79.59 107	81.21 61	88.89 52	82.70 123

CHOSEN 1792x2688		69.20 122	69.26 123	69.13 114	76.86 115	78.93 114	77.27 108	60.12 150	61.86 108	54.42 121	42.54 213	61.61 107	66.91 79	78.55 121	78.14 114	79.23 195	83.23 114

v1921920		69.03 123	68.32 145	69.86 106	74.03 160	80.37 101	77.55 103	60.25 144	54.62 183	53.59 130	52.36 182	51.50 194	66.75 80	77.17 151	76.69 155	86.96 97	85.56 76

CostFormer		68.92 124	69.58 113	68.15 123	75.98 126	76.17 163	78.22 100	51.86 203	65.80 79	61.56 78	63.57 81	62.83 104	61.85 126	70.40 206	68.67 203	79.42 193	79.62 157

FMVSNet1		68.84 125	70.47 101	66.94 146	71.35 187	77.68 138	74.71 127	62.35 114	56.93 151	49.94 153	50.01 192	64.59 99	57.07 156	81.33 70	80.72 68	86.25 124	82.00 130

NR-MVSNet		68.79 126	70.56 99	66.71 152	77.48 109	79.54 106	73.52 150	69.20 48	61.20 114	39.76 197	58.52 101	50.11 201	51.37 189	80.26 98	80.71 72	88.97 50	83.59 109

V42		68.76 127	69.63 112	67.74 127	64.93 214	78.01 129	78.30 98	56.48 184	58.65 133	56.30 114	54.26 149	57.03 132	64.85 105	77.47 143	77.01 135	85.60 152	84.96 91

v1240		68.64 128	67.89 152	69.51 112	73.89 162	80.26 104	76.73 113	59.97 152	53.43 192	53.08 133	51.82 185	50.84 197	66.62 83	76.79 157	76.77 138	86.78 111	85.34 83

tfpn111		68.38 129	69.23 124	67.39 134	77.83 98	78.93 114	74.28 135	62.81 93	56.64 155	46.70 168	56.24 119	53.47 168	56.59 159	80.41 85	78.43 104	86.11 129	80.53 145

Fast-Effi-MVS+-dtu		68.34 130	69.47 115	67.01 145	75.15 132	77.97 135	77.12 109	55.40 188	57.87 135	46.68 172	56.17 121	60.39 109	62.36 118	76.32 163	76.25 159	85.35 156	81.34 137

tpmp4_e23		68.32 131	67.08 161	69.76 108	77.86 95	75.22 176	78.37 97	56.17 187	66.06 78	64.27 70	57.15 115	54.89 152	63.40 112	70.97 199	68.29 208	78.46 197	77.00 177

GA-MVS		68.14 132	69.17 126	66.93 147	73.77 164	78.50 126	74.45 129	58.28 175	55.11 178	48.44 159	60.08 92	53.99 161	61.50 129	78.43 122	77.57 124	85.13 158	80.54 144

conf200view11		68.11 133	68.72 137	67.39 134	77.83 98	78.93 114	74.28 135	62.81 93	56.64 155	46.70 168	52.65 177	53.47 168	56.59 159	80.41 85	78.43 104	86.11 129	80.53 145

tfpn200view9		68.11 133	68.72 137	67.40 133	77.83 98	78.93 114	74.28 135	62.81 93	56.64 155	46.82 166	52.65 177	53.47 168	56.59 159	80.41 85	78.43 104	86.11 129	80.52 147

EPNet_dtu		68.08 135	71.00 96	64.67 164	79.64 82	68.62 203	75.05 124	63.30 85	66.36 75	45.27 179	67.40 68	66.84 94	43.64 208	75.37 169	74.98 176	81.15 186	77.44 171
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
thres200		67.98 136	68.55 142	67.30 139	77.89 94	78.86 118	74.18 142	62.75 98	56.35 165	46.48 173	52.98 171	53.54 164	56.46 164	80.41 85	77.97 116	86.05 135	79.78 155

thres400		67.95 137	68.62 141	67.17 141	77.90 92	78.59 125	74.27 140	62.72 100	56.34 166	45.77 177	53.00 170	53.35 173	56.46 164	80.21 100	78.43 104	85.91 145	80.43 148

pmmvs4		67.89 138	67.39 158	68.48 121	71.60 184	73.57 185	74.45 129	60.98 128	64.65 86	57.97 98	54.95 136	51.73 192	61.88 125	73.78 178	75.11 174	83.99 176	77.91 168

v148		67.85 139	67.53 154	68.23 122	73.25 168	77.57 141	74.26 141	57.36 180	55.70 172	57.45 100	53.53 160	55.42 146	61.96 124	75.23 170	73.92 179	85.08 159	81.32 138

Vis-MVSNet (Re-imp)		67.83 140	73.52 80	61.19 187	78.37 90	76.72 154	66.80 192	62.96 90	65.50 81	34.17 213	67.19 69	69.68 80	39.20 217	79.39 112	79.44 96	85.68 151	76.73 179

PatchMatch-RL		67.78 141	66.65 166	69.10 115	73.01 169	72.69 188	68.49 178	61.85 118	62.93 101	60.20 83	56.83 117	50.42 199	69.52 64	75.62 168	74.46 178	81.51 184	73.62 197

conf0.01		67.72 142	67.99 149	67.39 134	77.82 103	78.94 112	74.28 135	62.81 93	56.64 155	46.70 168	53.33 163	48.59 208	56.59 159	80.34 92	78.43 104	86.16 128	79.67 156

thres600view7		67.68 143	68.43 143	66.80 148	77.90 92	78.86 118	73.84 144	62.75 98	56.07 168	44.70 183	52.85 174	52.81 178	55.58 172	80.41 85	77.77 119	86.05 135	80.28 149

COLMAP_ROB	62.73 15	67.66 144	66.76 165	68.70 119	80.49 78	77.98 133	75.29 118	62.95 91	63.62 96	49.96 152	47.32 204	50.72 198	58.57 143	76.87 156	75.50 171	84.94 163	75.33 188
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
CDS-MVSNet		67.65 145	69.83 110	65.09 159	75.39 131	76.55 155	74.42 132	63.75 82	53.55 191	49.37 156	59.41 97	62.45 105	44.44 206	79.71 105	79.82 86	83.17 180	77.36 172
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
RPSCF		67.64 146	71.25 95	63.43 176	61.86 220	70.73 195	67.26 187	50.86 208	74.20 59	58.91 87	67.49 67	69.33 81	64.10 109	71.41 192	68.45 207	77.61 199	77.17 173

view600		67.63 147	68.36 144	66.77 149	77.84 96	78.66 122	73.74 147	62.62 107	56.04 169	44.98 180	52.86 173	52.83 177	55.48 175	80.36 91	77.75 120	85.95 144	80.02 152

thres100view900		67.60 148	68.02 148	67.12 143	77.83 98	77.75 137	73.90 143	62.52 110	56.64 155	46.82 166	52.65 177	53.47 168	55.92 168	78.77 119	77.62 123	85.72 150	79.23 160

Baseline_NR-MVSNet		67.53 149	68.77 135	66.09 154	75.99 124	74.75 180	72.43 158	68.41 51	61.33 113	38.33 202	51.31 187	54.13 160	56.03 167	79.22 113	78.19 112	85.37 155	82.45 125

conf0.002		67.52 150	67.64 153	67.39 134	77.80 105	78.94 112	74.28 135	62.81 93	56.64 155	46.70 168	53.65 159	46.28 216	56.59 159	80.33 93	78.37 109	86.17 127	79.23 160

thisisatest0515		67.40 151	68.78 134	65.80 156	70.02 194	75.24 171	69.36 175	57.37 179	54.94 182	53.67 129	55.53 125	54.85 153	58.00 148	78.19 126	78.91 99	86.39 123	83.78 105

USDC		67.36 152	67.90 151	66.74 151	71.72 180	75.23 174	71.58 164	60.28 143	67.45 72	50.54 149	60.93 86	45.20 220	62.08 121	76.56 161	74.50 177	84.25 173	75.38 187

view800		67.35 153	68.22 147	66.35 153	77.83 98	78.62 123	72.97 155	62.58 108	55.71 171	44.13 184	52.69 176	52.24 187	54.58 180	80.27 97	78.19 112	86.01 138	79.79 154

DWT-MVSNet_training		67.24 154	65.96 174	68.74 117	76.15 122	74.36 183	74.37 134	56.66 183	61.82 109	60.51 80	58.23 109	49.76 203	65.07 104	70.04 207	70.39 194	79.70 192	77.11 175

EG-PatchMatch MVS		67.24 154	66.94 162	67.60 130	78.73 88	81.35 83	73.28 153	59.49 155	46.89 218	51.42 143	43.65 210	53.49 166	55.50 174	81.38 69	80.66 74	87.15 84	81.17 139

v7n		67.05 156	66.94 162	67.17 141	72.35 175	78.97 111	73.26 154	58.88 163	51.16 203	50.90 145	48.21 197	50.11 201	60.96 132	77.70 133	77.38 129	86.68 117	85.05 89

IterMVS-SCA-FT		66.89 157	69.22 125	64.17 166	71.30 188	75.64 166	71.33 165	53.17 195	57.63 142	49.08 157	60.72 88	60.05 113	63.09 114	74.99 172	73.92 179	77.07 203	81.57 136

tfpn		66.58 158	67.18 159	65.88 155	77.82 103	78.45 127	72.07 160	62.52 110	55.35 175	43.21 188	52.54 181	46.12 217	53.68 181	80.02 102	78.23 111	85.99 141	79.55 158

IterMVS		66.36 159	68.30 146	64.10 167	69.48 200	74.61 181	73.41 152	50.79 209	57.30 144	48.28 160	60.64 89	59.92 114	60.85 136	74.14 176	72.66 186	81.80 183	78.82 164
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
conf0.05thres1000		66.26 160	66.77 164	65.66 157	77.45 110	78.10 128	71.85 163	62.44 113	51.47 202	43.00 189	47.92 199	51.66 193	53.40 183	79.71 105	77.97 116	85.82 146	80.56 143

TDRefinement		66.09 161	65.03 187	67.31 138	69.73 197	76.75 153	75.33 116	64.55 78	60.28 120	49.72 155	45.63 207	42.83 223	60.46 137	75.75 165	75.95 165	84.08 174	78.04 167

pm-mvs1		65.62 162	67.42 156	63.53 174	73.66 166	76.39 159	69.66 170	60.87 130	49.73 210	43.97 185	51.24 188	57.00 133	48.16 195	79.89 103	77.84 118	84.85 167	79.82 153

tpm cat1		65.41 163	63.81 195	67.28 140	75.61 130	72.88 187	75.32 117	52.85 197	62.97 100	63.66 72	53.24 166	53.29 175	61.83 127	65.54 218	64.14 221	74.43 215	74.60 190

SCA		65.40 164	66.58 167	64.02 170	70.65 190	73.37 186	67.35 186	53.46 193	63.66 95	54.14 123	60.84 87	60.20 112	61.50 129	69.96 208	68.14 209	77.01 204	69.91 208

anonymousdsp		65.28 165	67.98 150	62.13 181	58.73 228	73.98 184	67.10 189	50.69 210	48.41 213	47.66 165	54.27 147	52.75 180	61.45 131	76.71 159	80.20 81	87.13 88	89.53 49

v52		65.23 166	66.24 169	64.06 168	61.94 218	76.42 157	72.06 161	54.30 190	49.94 207	50.04 151	47.41 202	52.42 181	60.23 139	75.71 166	76.22 160	85.78 147	85.56 76

V4		65.23 166	66.23 170	64.06 168	61.94 218	76.42 157	72.05 162	54.31 189	49.91 209	50.06 150	47.42 201	52.40 182	60.24 138	75.71 166	76.22 160	85.78 147	85.56 76

v748		65.12 168	65.24 182	64.98 161	69.77 196	76.45 156	69.47 173	57.06 182	49.93 208	50.70 146	47.87 200	49.50 205	57.14 155	73.64 180	75.18 173	85.75 149	84.14 100

tfpn_ndepth		65.09 169	67.12 160	62.73 178	75.75 129	76.23 161	68.00 180	60.36 139	58.16 134	40.27 196	54.89 137	54.22 157	46.80 201	76.69 160	75.66 167	85.19 157	73.98 196

PMMVS		65.06 170	69.17 126	60.26 193	55.25 237	63.43 219	66.71 193	43.01 234	62.41 103	50.64 147	69.44 58	67.04 93	63.29 113	74.36 175	73.54 182	82.68 181	73.99 195

CR-MVSNet		64.83 171	65.54 180	64.01 171	70.64 191	69.41 198	65.97 197	52.74 198	57.81 137	52.65 135	54.27 147	56.31 137	60.92 133	72.20 188	73.09 184	81.12 187	75.69 184

thresconf0.02		64.77 172	65.90 175	63.44 175	76.37 118	75.17 179	69.51 172	61.28 123	56.98 146	39.01 200	56.24 119	48.68 207	49.78 192	77.13 152	75.61 168	84.71 168	71.53 204

TransMVSNet (Re)		64.74 173	65.66 179	63.66 173	77.40 111	75.33 170	69.86 169	62.67 106	47.63 216	41.21 195	50.01 192	52.33 183	45.31 205	79.57 108	77.69 122	85.49 153	77.07 176

test-LLR		64.42 174	64.36 191	64.49 165	75.02 134	63.93 216	66.61 194	61.96 116	54.41 184	47.77 162	57.46 112	60.25 110	55.20 176	70.80 200	69.33 198	80.40 190	74.38 192

MDTV_nov1_ep13		64.37 175	65.24 182	63.37 177	68.94 202	70.81 194	72.40 159	50.29 212	60.10 121	53.91 127	60.07 93	59.15 117	57.21 154	69.43 211	67.30 211	77.47 200	69.78 210

tfpnview11		64.33 176	66.17 171	62.18 180	76.25 119	75.23 174	67.45 183	61.16 124	55.50 173	36.38 207	55.35 127	51.89 189	46.96 197	77.28 149	76.10 164	84.86 166	71.85 203

tfpnnormal		64.27 177	63.64 196	65.02 160	75.84 127	75.61 167	71.24 167	62.52 110	47.79 215	42.97 190	42.65 212	44.49 221	52.66 187	78.77 119	76.86 137	84.88 164	79.29 159

tfpn_n400		64.23 178	66.05 172	62.12 182	76.20 120	75.24 171	67.43 184	61.15 125	54.04 189	36.38 207	55.35 127	51.89 189	46.94 198	77.31 147	76.15 162	84.59 170	72.36 200

tfpnconf		64.23 178	66.05 172	62.12 182	76.20 120	75.24 171	67.43 184	61.15 125	54.04 189	36.38 207	55.35 127	51.89 189	46.94 198	77.31 147	76.15 162	84.59 170	72.36 200

PatchmatchNet		64.21 180	64.65 189	63.69 172	71.29 189	68.66 202	69.63 171	51.70 205	63.04 99	53.77 128	59.83 96	58.34 121	60.23 139	68.54 214	66.06 216	75.56 210	68.08 214
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
dps		64.00 181	62.99 198	65.18 158	73.29 167	72.07 190	68.98 177	53.07 196	57.74 139	58.41 92	55.55 124	47.74 212	60.89 135	69.53 210	67.14 213	76.44 207	71.19 206

tfpn1000		63.81 182	66.31 168	60.90 189	75.76 128	75.74 165	65.14 201	60.14 149	56.47 162	35.99 210	55.11 130	52.30 185	43.42 209	76.21 164	75.34 172	84.97 162	73.01 199

pmmvs-eth3d		63.52 183	62.44 205	64.77 163	66.82 208	70.12 197	69.41 174	59.48 156	54.34 187	52.71 134	46.24 206	44.35 222	56.93 157	72.37 183	73.77 181	83.30 178	75.91 181

WR-MVS		63.03 184	67.40 157	57.92 203	75.14 133	77.60 140	60.56 216	66.10 65	54.11 188	23.88 225	53.94 157	53.58 163	34.50 221	73.93 177	77.71 121	87.35 80	80.94 140

PEN-MVS		62.96 185	65.77 178	59.70 196	73.98 161	75.45 168	63.39 209	67.61 58	52.49 195	25.49 224	53.39 161	49.12 206	40.85 215	71.94 190	77.26 132	86.86 103	80.72 142

TinyColmap		62.84 186	61.03 211	64.96 162	69.61 198	71.69 191	68.48 179	59.76 154	55.41 174	47.69 164	47.33 203	34.20 233	62.76 117	74.52 173	72.59 187	81.44 185	71.47 205

CP-MVSNet		62.68 187	65.49 181	59.40 199	71.84 178	75.34 169	62.87 211	67.04 61	52.64 194	27.19 222	53.38 162	48.15 210	41.40 213	71.26 193	75.68 166	86.07 133	82.00 130

gg-mvs-nofinetune		62.55 188	65.05 186	59.62 197	78.72 89	77.61 139	70.83 168	53.63 191	39.71 230	22.04 234	36.36 223	64.32 100	47.53 196	81.16 75	79.03 98	85.00 161	77.17 173

CVMVSNet		62.55 188	65.89 176	58.64 201	66.95 206	69.15 200	66.49 196	56.29 186	52.46 196	32.70 214	59.27 98	58.21 122	50.09 191	71.77 191	71.39 191	79.31 194	78.99 163

CMPMVS	47.78 17	62.49 190	62.52 203	62.46 179	70.01 195	70.66 196	62.97 210	51.84 204	51.98 198	56.71 111	42.87 211	53.62 162	57.80 149	72.23 186	70.37 195	75.45 212	75.91 181
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
pmmvs6		62.41 191	62.88 199	61.87 184	71.38 186	75.18 178	67.76 182	59.45 157	41.64 226	42.52 193	37.33 221	52.91 176	46.87 200	77.67 135	76.26 158	83.23 179	79.18 162

tpm		62.41 191	63.15 197	61.55 186	72.24 176	63.79 218	71.31 166	46.12 225	57.82 136	55.33 118	59.90 95	54.74 154	53.63 182	67.24 217	64.29 219	70.65 226	74.25 194

PS-CasMVS		62.38 193	65.06 185	59.25 200	71.73 179	75.21 177	62.77 212	66.99 62	51.94 200	26.96 223	52.00 184	47.52 213	41.06 214	71.16 196	75.60 169	85.97 142	81.97 132

pmmvs5		62.37 194	64.04 193	60.42 191	65.03 212	71.67 192	67.17 188	52.70 200	50.30 204	44.80 181	54.23 151	51.19 196	49.37 193	72.88 182	73.48 183	83.45 177	74.55 191

tpmrst		62.00 195	62.35 206	61.58 185	71.62 183	64.14 215	69.07 176	48.22 221	62.21 105	53.93 126	58.26 108	55.30 148	55.81 170	63.22 223	62.62 224	70.85 225	70.70 207

PatchT		61.97 196	64.04 193	59.55 198	60.49 222	67.40 206	56.54 223	48.65 217	56.69 154	52.65 135	51.10 189	52.14 188	60.92 133	72.20 188	73.09 184	78.03 198	75.69 184

DTE-MVSNet		61.85 197	64.96 188	58.22 202	74.32 157	74.39 182	61.01 215	67.85 57	51.76 201	21.91 235	53.28 164	48.17 209	37.74 218	72.22 187	76.44 156	86.52 122	78.49 165

SixPastTwentyTwo		61.84 198	62.45 204	61.12 188	69.20 201	72.20 189	62.03 213	57.40 178	46.54 219	38.03 204	57.14 116	41.72 225	58.12 147	69.67 209	71.58 190	81.94 182	78.30 166

WR-MVS_H		61.83 199	65.87 177	57.12 206	71.72 180	76.87 152	61.45 214	66.19 63	51.97 199	22.92 232	53.13 169	52.30 185	33.80 222	71.03 197	75.00 175	86.65 118	80.78 141

LTVRE_ROB	59.44 16	61.82 200	62.64 202	60.87 190	72.83 174	77.19 142	64.37 205	58.97 161	33.56 239	28.00 221	52.59 180	42.21 224	63.93 110	74.52 173	76.28 157	77.15 202	82.13 126
Andreas Kuhn, Heiko HirschmÃ¼ller, Daniel Scharstein, Helmut Mayer: A TV Prior for High-Quality Scalable Multi-View Stereo Reconstruction. International Journal of Computer Vision 2016
RPMNet		61.71 201	62.88 199	60.34 192	69.51 199	69.41 198	63.48 208	49.23 213	57.81 137	45.64 178	50.51 190	50.12 200	53.13 186	68.17 216	68.49 206	81.07 188	75.62 186

TESTMET0.1,1		61.10 202	64.36 191	57.29 205	57.53 230	63.93 216	66.61 194	36.22 240	54.41 184	47.77 162	57.46 112	60.25 110	55.20 176	70.80 200	69.33 198	80.40 190	74.38 192

test-mter		60.84 203	64.62 190	56.42 208	55.99 235	64.18 214	65.39 199	34.23 242	54.39 186	46.21 174	57.40 114	59.49 116	55.86 169	71.02 198	69.65 197	80.87 189	76.20 180

PM-MVS		60.48 204	60.94 212	59.94 194	58.85 227	66.83 209	64.27 206	51.39 206	55.03 180	48.03 161	50.00 194	40.79 227	58.26 146	69.20 212	67.13 214	78.84 196	77.60 170

MDTV_nov1_ep13_2view		60.16 205	60.51 213	59.75 195	65.39 211	69.05 201	68.00 180	48.29 219	51.99 197	45.95 176	48.01 198	49.64 204	53.39 184	68.83 213	66.52 215	77.47 200	69.55 211

EPMVS		60.00 206	61.97 207	57.71 204	68.46 203	63.17 222	64.54 204	48.23 220	63.30 97	44.72 182	60.19 91	56.05 145	50.85 190	65.27 220	62.02 226	69.44 228	63.81 221

TAMVS		59.58 207	62.81 201	55.81 210	66.03 210	65.64 213	63.86 207	48.74 216	49.95 206	37.07 206	54.77 140	58.54 119	44.44 206	72.29 185	71.79 188	74.70 214	66.66 216

test0.0.03 1		58.80 208	61.58 209	55.56 211	75.02 134	68.45 204	59.58 220	61.96 116	52.74 193	29.57 217	49.75 195	54.56 155	31.46 224	71.19 194	69.77 196	75.75 208	64.57 219

CHOSEN 280x420		58.70 209	61.88 208	54.98 213	55.45 236	50.55 239	64.92 202	40.36 236	55.21 176	38.13 203	48.31 196	63.76 101	63.03 116	73.73 179	68.58 205	68.00 231	73.04 198

MIMVSNet		58.52 210	61.34 210	55.22 212	60.76 221	67.01 208	66.81 191	49.02 215	56.43 163	38.90 201	40.59 218	54.54 156	40.57 216	73.16 181	71.65 189	75.30 213	66.00 217

FMVSNet5		57.24 211	60.02 214	53.99 216	56.45 232	62.74 223	65.27 200	47.03 222	55.14 177	39.55 199	40.88 216	53.42 172	41.83 210	72.35 184	71.10 193	73.79 217	64.50 220

gm-plane-assit		57.00 212	57.62 219	56.28 209	76.10 123	62.43 226	47.62 235	46.57 223	33.84 238	23.24 228	37.52 220	40.19 228	59.61 141	79.81 104	77.55 125	84.55 172	72.03 202

FC-MVSNet-test		56.90 213	65.20 184	47.21 224	66.98 205	63.20 221	49.11 233	58.60 173	59.38 127	11.50 244	65.60 72	56.68 134	24.66 236	71.17 195	71.36 192	72.38 221	69.02 212

Anonymous20231206		56.36 214	57.80 218	54.67 214	70.08 193	66.39 210	60.46 217	57.54 177	49.50 212	29.30 218	33.86 229	46.64 214	35.18 220	70.44 204	68.88 202	75.47 211	68.88 213

ADS-MVSNet		55.94 215	58.01 216	53.54 219	62.48 217	58.48 228	59.12 221	46.20 224	59.65 125	42.88 191	52.34 183	53.31 174	46.31 203	62.00 227	60.02 231	64.23 237	60.24 229

EU-MVSNet		54.63 216	58.69 215	49.90 222	56.99 231	62.70 224	56.41 224	50.64 211	45.95 221	23.14 229	50.42 191	46.51 215	36.63 219	65.51 219	64.85 218	75.57 209	74.91 189

MVS-HIRNet		54.41 217	52.10 225	57.11 207	58.99 226	56.10 231	49.68 232	49.10 214	46.18 220	52.15 139	33.18 230	46.11 218	56.10 166	63.19 224	59.70 232	76.64 206	60.25 228

testgi		54.39 218	57.86 217	50.35 221	71.59 185	67.24 207	54.95 225	53.25 194	43.36 223	23.78 226	44.64 208	47.87 211	24.96 233	70.45 203	68.66 204	73.60 218	62.78 224

test20.03		53.93 219	56.28 220	51.19 220	72.19 177	65.83 211	53.20 227	61.08 127	42.74 224	22.08 233	37.07 222	45.76 219	24.29 237	70.44 204	69.04 200	74.31 216	63.05 223

LP		53.62 220	53.43 221	53.83 217	58.51 229	62.59 225	57.31 222	46.04 226	47.86 214	42.69 192	36.08 225	36.86 231	46.53 202	64.38 221	64.25 220	71.92 222	62.00 226

MDA-MVSNet-bldmvs		53.37 221	53.01 224	53.79 218	43.67 245	67.95 205	59.69 219	57.92 176	43.69 222	32.41 215	41.47 214	27.89 242	52.38 188	56.97 237	65.99 217	76.68 205	67.13 215

FPMVS		51.87 222	50.00 227	54.07 215	66.83 207	57.25 229	60.25 218	50.91 207	50.25 205	34.36 212	36.04 226	32.02 235	41.49 212	58.98 235	56.07 235	70.56 227	59.36 230

MIMVSNet1		49.27 223	53.25 223	44.62 228	44.61 242	61.52 227	53.61 226	52.18 201	41.62 227	18.68 237	28.14 237	41.58 226	25.50 231	68.46 215	69.04 200	73.15 219	62.37 225

pmmvs3		47.65 224	49.08 229	45.99 226	44.61 242	54.79 234	50.04 230	31.95 245	33.91 237	29.90 216	30.37 231	33.53 234	46.31 203	63.50 222	63.67 222	73.14 220	63.77 222

testpf		47.41 225	48.47 232	46.18 225	66.30 209	50.67 238	48.15 234	42.60 235	37.10 234	28.75 219	40.97 215	39.01 230	30.82 225	52.95 240	53.74 239	60.46 238	64.87 218

N_pmnet		47.35 226	50.13 226	44.11 229	59.98 223	51.64 237	51.86 228	44.80 230	49.58 211	20.76 236	40.65 217	40.05 229	29.64 226	59.84 233	55.15 236	57.63 239	54.00 237

test2356		47.20 227	48.62 231	45.54 227	56.38 233	54.89 233	50.62 229	45.08 229	38.65 231	23.40 227	36.23 224	31.10 237	29.31 227	62.76 225	62.49 225	68.48 230	54.23 236

new-patchmatchnet		46.97 228	49.47 228	44.05 230	62.82 216	56.55 230	45.35 236	52.01 202	42.47 225	17.04 240	35.73 227	35.21 232	21.84 242	61.27 228	54.83 237	65.26 236	60.26 227

GG-mvs-BLEND		46.86 229	67.51 155	22.75 242	0.05 252	76.21 162	64.69 203	0.04 249	61.90 107	0.09 252	55.57 123	71.32 69	0.08 248	70.54 202	67.19 212	71.58 223	69.86 209

PMVS	39.38 18	46.06 230	43.30 236	49.28 223	62.93 215	38.75 245	41.88 238	53.50 192	33.33 240	35.46 211	28.90 234	31.01 238	33.04 223	58.61 236	54.63 238	68.86 229	57.88 233
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
testus		45.61 231	49.06 230	41.59 232	56.13 234	55.28 232	43.51 237	39.64 238	37.74 232	18.23 238	35.52 228	31.28 236	24.69 235	62.46 226	62.90 223	67.33 232	58.26 232

1111		43.08 232	44.02 235	41.98 231	59.22 224	49.27 241	41.48 239	45.63 227	35.01 235	23.06 230	28.60 235	30.15 239	27.22 228	60.42 231	57.97 233	55.27 242	46.74 239

testmv		42.58 233	44.36 233	40.49 233	54.63 238	52.76 235	41.21 241	44.37 231	28.83 241	12.87 241	27.16 238	25.03 243	23.01 238	60.83 229	61.13 227	66.88 233	54.81 234

test1235678		42.57 234	44.36 233	40.49 233	54.63 238	52.75 236	41.21 241	44.37 231	28.82 242	12.87 241	27.15 239	25.01 244	23.01 238	60.83 229	61.13 227	66.88 233	54.81 234

new_pmnet		38.40 235	42.64 237	33.44 237	37.54 248	45.00 243	36.60 243	32.72 244	40.27 228	12.72 243	29.89 232	28.90 241	24.78 234	53.17 239	52.90 240	56.31 240	48.34 238

Gipuma		36.38 236	35.80 240	37.07 235	45.76 241	33.90 246	29.81 245	48.47 218	39.91 229	18.02 239	8.00 248	8.14 251	25.14 232	59.29 234	61.02 229	55.19 243	40.31 241
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
no-one		36.35 237	37.59 239	34.91 236	46.13 240	49.89 240	27.99 246	43.56 233	20.91 246	7.03 247	14.64 244	15.50 249	18.92 243	42.95 241	60.20 230	65.84 235	59.03 231

test12356		35.10 238	38.50 238	31.13 239	44.14 244	43.70 244	32.27 244	34.42 241	26.51 244	9.47 245	25.22 241	20.34 245	10.86 245	53.47 238	56.15 234	55.59 241	44.11 240

.test1245		30.81 239	29.14 242	32.77 238	59.22 224	49.27 241	41.48 239	45.63 227	35.01 235	23.06 230	28.60 235	30.15 239	27.22 228	60.42 231	0.10 246	0.01 250	0.43 248

PMMVS2		25.60 240	29.75 241	20.76 243	28.00 249	30.93 247	23.10 247	29.18 246	23.14 245	1.46 251	18.23 243	16.54 247	5.08 246	40.22 242	41.40 242	37.76 244	37.79 243

E-PMN		21.77 241	18.24 244	25.89 240	40.22 246	19.58 249	12.46 250	39.87 237	18.68 248	6.71 248	9.57 245	4.31 254	22.36 241	19.89 246	27.28 244	33.73 245	28.34 245

EMVS		20.98 242	17.15 245	25.44 241	39.51 247	19.37 250	12.66 249	39.59 239	19.10 247	6.62 249	9.27 246	4.40 253	22.43 240	17.99 247	24.40 245	31.81 246	25.53 246

MVE	19.12 19	20.47 243	23.27 243	17.20 244	12.66 251	25.41 248	10.52 251	34.14 243	14.79 249	6.53 250	8.79 247	4.68 252	16.64 244	29.49 244	41.63 241	22.73 248	38.11 242
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
testmvs		0.09 244	0.15 246	0.02 246	0.01 253	0.02 253	0.05 254	0.01 250	0.11 250	0.01 253	0.26 250	0.01 255	0.06 250	0.10 248	0.10 246	0.01 250	0.43 248

test123		0.09 244	0.14 247	0.02 246	0.00 254	0.02 253	0.02 255	0.01 250	0.09 251	0.00 254	0.30 249	0.00 256	0.08 248	0.03 249	0.09 248	0.01 250	0.45 247

sosnet-low-res		0.00 246	0.00 248	0.00 248	0.00 254	0.00 255	0.00 256	0.00 252	0.00 252	0.00 254	0.00 251	0.00 256	0.00 251	0.00 250	0.00 249	0.00 253	0.00 250

sosnet		0.00 246	0.00 248	0.00 248	0.00 254	0.00 255	0.00 256	0.00 252	0.00 252	0.00 254	0.00 251	0.00 256	0.00 251	0.00 250	0.00 249	0.00 253	0.00 250

SR-MVS					88.99 31			73.57 22				87.54 11

Anonymous202405211			72.16 91		80.85 74	81.85 79	76.88 112	65.40 71	62.89 102		46.35 205	67.99 91	62.05 122	81.15 76	80.38 79	85.97 142	84.50 97

our_test_3					67.93 204	70.99 193	66.89 190

test_part1																	95.35 2

ambc			53.42 222		64.99 213	63.36 220	49.96 231		47.07 217	37.12 205	28.97 233	16.36 248	41.82 211	75.10 171	67.34 210	71.55 224	75.72 183

MTAPA										83.48 1		86.45 15

MTMP										82.66 3		84.91 23

Patchmatch-RL test							2.85 253

tmp_tt				14.50 245	14.68 250	7.17 252	10.46 252	2.21 248	37.73 233	28.71 220	25.26 240	16.98 246	4.37 247	31.49 243	29.77 243	26.56 247

XVS					86.63 43	88.68 25	85.00 45			71.81 44		81.92 34				90.47 19

X-MVStestdata					86.63 43	88.68 25	85.00 45			71.81 44		81.92 34				90.47 19

abl_6				79.05 40	87.27 39	88.85 23	83.62 54	68.25 52	81.68 38	72.94 37	73.79 42	84.45 25	72.55 46			89.66 40	90.64 40

mPP-MVS					89.90 22							81.29 39

NP-MVS									80.10 43

Patchmtry						65.80 212	65.97 197	52.74 198		52.65 135

DeepMVS_CX						18.74 251	18.55 248	8.02 247	26.96 243	7.33 246	23.81 242	13.05 250	25.99 230	25.17 245		22.45 249	36.25 244

High-resolution multi-view benchmark