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		78.19 1	83.74 1	71.72 1	79.01 1	81.38 1	83.23 2	58.63 2	83.92 5	62.44 12	87.06 2	85.82 1	64.54 3	79.39 5	77.99 8	82.44 17	90.61 1

SMA-MVS		77.34 3	82.65 3	71.13 3	75.33 10	80.39 3	82.14 3	58.49 3	84.51 4	63.89 5	78.09 11	83.76 2	63.31 7	81.19 1	80.62 1	83.60 4	90.03 3

HSP-MVS		76.78 4	82.44 4	70.19 8	75.26 11	80.22 4	80.59 8	57.85 6	84.79 3	60.84 16	88.54 1	83.43 3	66.24 1	78.21 15	76.47 21	80.34 38	85.43 27

APDe-MVS		77.58 2	82.93 2	71.35 2	77.86 2	80.55 2	83.38 1	57.61 7	85.57 1	61.11 15	86.10 4	82.98 4	64.76 2	78.29 12	76.78 19	83.40 6	90.20 2

TSAR-MVS + MP.		75.22 10	80.06 9	69.56 13	74.61 13	72.74 45	80.59 8	55.70 20	80.80 9	62.65 10	86.25 3	82.92 5	62.07 16	76.89 25	75.66 27	81.77 29	85.19 29

SD-MVS		74.43 13	78.87 14	69.26 16	74.39 14	73.70 41	79.06 20	55.24 22	81.04 8	62.71 9	80.18 8	82.61 6	61.70 18	75.43 36	73.92 39	82.44 17	85.22 28

HPM-MVS++		76.01 6	80.47 8	70.81 4	76.60 4	74.96 31	80.18 12	58.36 4	81.96 6	63.50 7	78.80 10	82.53 7	64.40 4	78.74 8	78.84 5	81.81 27	87.46 13

CSCG		74.68 12	79.22 12	69.40 14	75.69 8	80.01 5	79.12 19	52.83 36	79.34 14	63.99 4	70.49 21	82.02 8	60.35 27	77.48 22	77.22 16	84.38 1	87.97 11

TSAR-MVS + ACMM		72.56 24	79.07 13	64.96 36	73.24 20	73.16 44	78.50 22	48.80 59	79.34 14	55.32 36	85.04 6	81.49 9	58.57 33	75.06 39	73.75 40	75.35 103	85.61 25

CNVR-MVS		75.62 8	79.91 10	70.61 5	75.76 6	78.82 10	81.66 5	57.12 9	79.77 13	63.04 8	70.69 20	81.15 10	62.99 8	80.23 3	79.54 3	83.11 7	89.16 4

DeepPCF-MVS	66.49 1	74.25 16	80.97 6	66.41 27	67.75 46	78.87 9	75.61 34	54.16 28	84.86 2	58.22 28	77.94 12	81.01 11	62.52 12	78.34 10	77.38 13	80.16 41	88.40 7

APD-MVS		75.80 7	80.90 7	69.86 12	75.42 9	78.48 12	81.43 7	57.44 8	80.45 11	59.32 22	85.28 5	80.82 12	63.96 5	76.89 25	76.08 24	81.58 33	88.30 8
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
ACMMP_Plus		76.15 5	81.17 5	70.30 6	74.09 15	79.47 6	81.59 6	57.09 10	81.38 7	63.89 5	79.02 9	80.48 13	62.24 14	80.05 4	79.12 4	82.94 10	88.64 5

MTAPA										65.14 1		80.20 14

zzz-MVS		74.25 16	77.97 20	69.91 11	73.43 19	74.06 39	79.69 14	56.44 14	80.74 10	64.98 2	68.72 26	79.98 15	62.92 10	78.24 14	77.77 12	81.99 25	86.30 18

train_agg		73.89 18	78.25 18	68.80 19	75.25 12	72.27 47	79.75 13	56.05 17	74.87 28	58.97 23	81.83 7	79.76 16	61.05 22	77.39 23	76.01 25	81.71 30	85.61 25

MCST-MVS		73.67 21	77.39 22	69.33 15	76.26 5	78.19 13	78.77 21	54.54 25	75.33 23	59.99 20	67.96 28	79.23 17	62.43 13	78.00 16	75.71 26	84.02 2	87.30 14

MP-MVS		74.31 14	78.87 14	68.99 17	73.49 18	78.56 11	79.25 18	56.51 13	75.33 23	60.69 18	75.30 15	79.12 18	61.81 17	77.78 19	77.93 9	82.18 23	88.06 10
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
SteuartSystems-ACMMP		75.23 9	79.60 11	70.13 9	76.81 3	78.92 8	81.74 4	57.99 5	75.30 25	59.83 21	75.69 14	78.45 19	60.48 25	80.58 2	79.77 2	83.94 3	88.52 6
Skip Steuart: Steuart Systems R&D Blog.
NCCC		74.27 15	77.83 21	70.13 9	75.70 7	77.41 18	80.51 10	57.09 10	78.25 17	62.28 13	65.54 33	78.26 20	62.18 15	79.13 6	78.51 6	83.01 9	87.68 12

MTMP										62.63 11		78.04 21

abl_6				64.36 40	70.08 35	77.45 17	72.88 45	50.15 51	71.31 38	54.77 43	62.79 41	77.99 22	56.80 45			81.50 34	83.91 35

HFP-MVS		74.87 11	78.86 16	70.21 7	73.99 16	77.91 14	80.36 11	56.63 12	78.41 16	64.27 3	74.54 16	77.75 23	62.96 9	78.70 9	77.82 10	83.02 8	86.91 16

ACMMPR		73.79 20	78.41 17	68.40 20	72.35 23	77.79 15	79.32 16	56.38 15	77.67 20	58.30 27	74.16 17	76.66 24	61.40 19	78.32 11	77.80 11	82.68 14	86.51 17

CP-MVS		72.63 23	76.95 24	67.59 22	70.67 30	75.53 29	77.95 26	56.01 18	75.65 22	58.82 24	69.16 25	76.48 25	60.46 26	77.66 20	77.20 17	81.65 31	86.97 15

MVS_0304		69.49 32	73.96 31	64.28 41	67.92 44	76.13 27	74.90 37	47.60 62	63.29 53	54.09 48	67.44 31	76.35 26	59.53 30	75.81 33	75.03 29	81.62 32	83.70 37

DeepC-MVS	66.32 2	73.85 19	78.10 19	68.90 18	67.92 44	79.31 7	78.16 24	59.28 1	78.24 18	61.13 14	67.36 32	76.10 27	63.40 6	79.11 7	78.41 7	83.52 5	88.16 9
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.		69.71 30	73.92 32	64.80 38	68.27 42	70.56 52	71.90 46	50.75 46	71.38 37	57.46 31	68.68 27	75.42 28	60.10 28	73.47 44	73.99 38	80.32 39	83.97 34

PGM-MVS		72.89 22	77.13 23	67.94 21	72.47 22	77.25 19	79.27 17	54.63 24	73.71 30	57.95 29	72.38 18	75.33 29	60.75 23	78.25 13	77.36 15	82.57 16	85.62 24

PHI-MVS		69.27 34	74.84 30	62.76 46	66.83 49	74.83 32	73.88 42	49.32 55	70.61 40	50.93 55	69.62 24	74.84 30	57.25 41	75.53 35	74.32 36	78.35 55	84.17 33

CDPH-MVS		71.47 27	75.82 27	66.41 27	72.97 21	77.15 20	78.14 25	54.71 23	69.88 43	53.07 51	70.98 19	74.83 31	56.95 44	76.22 29	76.57 20	82.62 15	85.09 30

XVS					70.49 32	76.96 21	74.36 40			54.48 44		74.47 32				82.24 19

X-MVStestdata					70.49 32	76.96 21	74.36 40			54.48 44		74.47 32				82.24 19

X-MVS		71.18 28	75.66 28	65.96 31	71.71 25	76.96 21	77.26 28	55.88 19	72.75 33	54.48 44	64.39 37	74.47 32	54.19 56	77.84 18	77.37 14	82.21 21	85.85 22

CANet		68.77 36	73.01 33	63.83 42	68.30 41	75.19 30	73.73 43	47.90 61	63.86 50	54.84 41	67.51 30	74.36 35	57.62 37	74.22 42	73.57 43	80.56 37	82.36 41

mPP-MVS					71.67 28							74.36 35

DeepC-MVS_fast	65.08 3	72.00 25	76.11 25	67.21 24	68.93 40	77.46 16	76.54 30	54.35 26	74.92 27	58.64 26	65.18 34	74.04 37	62.62 11	77.92 17	77.02 18	82.16 24	86.21 19
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
MSLP-MVS++		68.17 39	70.72 44	65.19 34	69.41 37	70.64 51	74.99 36	45.76 68	70.20 42	60.17 19	56.42 62	73.01 38	61.14 20	72.80 47	70.54 51	79.70 43	81.42 46

PCF-MVS	59.98 8	67.32 44	71.04 42	62.97 45	64.77 58	74.49 35	74.78 38	49.54 53	67.44 46	54.39 47	58.35 57	72.81 39	55.79 52	71.54 52	69.24 59	78.57 51	83.41 38
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
CPTT-MVS		68.76 37	73.01 33	63.81 43	65.42 56	73.66 42	76.39 32	52.08 38	72.61 34	50.33 57	60.73 50	72.65 40	59.43 31	73.32 45	72.12 45	79.19 49	85.99 21

canonicalmvs		65.62 48	72.06 36	58.11 57	63.94 66	71.05 50	64.49 98	43.18 117	74.08 29	47.35 64	64.17 38	71.97 41	51.17 97	71.87 50	70.74 49	78.51 53	80.56 48

ACMMP		71.57 26	75.84 26	66.59 26	70.30 34	76.85 24	78.46 23	53.95 29	73.52 31	55.56 34	70.13 22	71.36 42	58.55 34	77.00 24	76.23 23	82.71 13	85.81 23
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
QAPM		65.27 49	69.49 50	60.35 49	65.43 55	72.20 48	65.69 89	47.23 63	63.46 52	49.14 60	53.56 74	71.04 43	57.01 42	72.60 48	71.41 48	77.62 59	82.14 43

HQP-MVS		70.88 29	75.02 29	66.05 30	71.69 26	74.47 36	77.51 27	53.17 33	72.89 32	54.88 40	70.03 23	70.48 44	57.26 40	76.02 31	75.01 31	81.78 28	86.21 19

3Dnovator+	62.63 4	69.51 31	72.62 35	65.88 32	68.21 43	76.47 25	73.50 44	52.74 37	70.85 39	58.65 25	55.97 64	69.95 45	61.11 21	76.80 27	75.09 28	81.09 36	83.23 40

MAR-MVS		68.04 40	70.74 43	64.90 37	71.68 27	76.33 26	74.63 39	50.48 50	63.81 51	55.52 35	54.88 69	69.90 46	57.39 39	75.42 37	74.79 33	79.71 42	80.03 50
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
OPM-MVS		69.33 33	71.05 41	67.32 23	72.34 24	75.70 28	79.57 15	56.34 16	55.21 65	53.81 49	59.51 53	68.96 47	59.67 29	77.61 21	76.44 22	82.19 22	83.88 36

DELS-MVS		65.87 47	70.30 47	60.71 48	64.05 65	72.68 46	70.90 50	45.43 72	57.49 61	49.05 61	64.43 36	68.66 48	55.11 54	74.31 41	73.02 44	79.70 43	81.51 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
UA-Net		58.50 86	64.68 66	51.30 118	66.97 48	67.13 73	53.68 159	45.65 71	49.51 89	31.58 146	62.91 40	68.47 49	35.85 168	68.20 81	67.28 77	74.03 112	69.24 130

OMC-MVS		65.16 50	71.35 40	57.94 61	52.95 160	68.82 57	69.00 51	38.28 174	79.89 12	55.20 37	62.76 42	68.31 50	56.14 49	71.30 54	68.70 64	76.06 97	79.67 51

3Dnovator	60.86 6	66.99 46	70.32 46	63.11 44	66.63 50	74.52 34	71.56 48	45.76 68	67.37 47	55.00 39	54.31 73	68.19 51	58.49 35	73.97 43	73.63 42	81.22 35	80.23 49

DI_MVS_plusplus_trai		61.88 59	65.17 63	58.06 58	60.05 75	65.26 93	66.03 84	44.22 84	55.75 63	46.73 66	54.64 71	68.12 52	54.13 58	69.13 68	66.66 85	77.18 65	76.61 70

CLD-MVS		67.02 45	71.57 38	61.71 47	71.01 29	74.81 33	71.62 47	38.91 167	71.86 36	60.70 17	64.97 35	67.88 53	51.88 94	76.77 28	74.98 32	76.11 95	69.75 120
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
diffmvs		59.53 66	64.04 69	54.26 99	55.09 140	59.86 143	64.80 95	39.55 166	58.39 60	46.21 72	60.48 51	67.82 54	49.27 102	63.53 152	63.32 148	70.64 158	74.89 87

MVS_Test		62.40 58	66.23 57	57.94 61	59.77 79	64.77 98	66.50 79	41.76 142	57.26 62	49.33 59	62.68 43	67.47 55	53.50 64	68.57 75	66.25 93	76.77 72	76.58 72

MVS_111021_HR		67.62 42	70.39 45	64.39 39	69.77 36	70.45 53	71.44 49	51.72 42	60.77 58	55.06 38	62.14 46	66.40 56	58.13 36	76.13 30	74.79 33	80.19 40	82.04 44

EPNet		65.14 51	69.54 49	60.00 51	66.61 51	67.67 66	67.53 55	55.32 21	62.67 55	46.22 71	67.74 29	65.93 57	48.07 110	72.17 49	72.12 45	76.28 87	78.47 57
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
OpenMVS	57.13 9	62.81 55	65.75 59	59.39 53	66.47 52	69.52 55	64.26 100	43.07 122	61.34 57	50.19 58	47.29 120	64.41 58	54.60 55	70.18 63	68.62 66	77.73 57	78.89 54

LGP-MVS_train		68.87 35	72.03 37	65.18 35	69.33 38	74.03 40	76.67 29	53.88 30	68.46 44	52.05 54	63.21 39	63.89 59	56.31 46	75.99 32	74.43 35	82.83 12	84.18 32

TAPA-MVS	54.74 10	60.85 62	66.61 54	54.12 101	47.38 189	65.33 91	65.35 92	36.51 185	75.16 26	48.82 62	54.70 70	63.51 60	53.31 68	68.36 76	64.97 128	73.37 121	74.27 105
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
UGNet		57.03 106	65.25 62	47.44 157	46.54 192	66.73 76	56.30 136	43.28 115	50.06 84	32.99 139	62.57 44	63.26 61	33.31 178	68.25 78	67.58 73	72.20 146	78.29 58
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
Effi-MVS+		63.28 53	65.96 58	60.17 50	64.26 62	68.06 61	68.78 52	45.71 70	54.08 69	46.64 67	55.92 65	63.13 62	55.94 50	70.38 61	71.43 47	79.68 46	78.70 55

MVS_111021_LR		63.05 54	66.43 55	59.10 54	61.33 70	63.77 103	65.87 87	43.58 106	60.20 59	53.70 50	62.09 47	62.38 63	55.84 51	70.24 62	68.08 68	74.30 108	78.28 59

ACMP	61.42 5	68.72 38	71.37 39	65.64 33	69.06 39	74.45 37	75.88 33	53.30 32	68.10 45	55.74 33	61.53 49	62.29 64	56.97 43	74.70 40	74.23 37	82.88 11	84.31 31
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
EPP-MVSNet		59.39 67	65.45 61	52.32 115	60.96 72	67.70 65	58.42 123	44.75 79	49.71 86	27.23 171	59.03 54	62.20 65	43.34 132	70.71 58	69.13 60	79.25 48	79.63 52

CANet_DTU		58.88 73	64.68 66	52.12 116	55.77 133	66.75 75	63.92 101	37.04 181	53.32 72	37.45 124	59.81 52	61.81 66	44.43 126	68.25 78	67.47 76	74.12 111	75.33 84

ACMM	60.30 7	67.58 43	68.82 52	66.13 29	70.59 31	72.01 49	76.54 30	54.26 27	65.64 49	54.78 42	50.35 85	61.72 67	58.74 32	75.79 34	75.03 29	81.88 26	81.17 47
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
Vis-MVSNet		58.48 87	65.70 60	50.06 125	53.40 158	67.20 71	60.24 119	43.32 114	48.83 97	30.23 152	62.38 45	61.61 68	40.35 143	71.03 57	69.77 57	72.82 129	79.11 53
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
PVSNet_BlendedMVS		61.63 60	64.82 64	57.91 63	57.21 125	67.55 67	63.47 104	46.08 66	54.72 66	52.46 52	58.59 55	60.73 69	51.82 95	70.46 59	65.20 125	76.44 84	76.50 75

PVSNet_Blended		61.63 60	64.82 64	57.91 63	57.21 125	67.55 67	63.47 104	46.08 66	54.72 66	52.46 52	58.59 55	60.73 69	51.82 95	70.46 59	65.20 125	76.44 84	76.50 75

GG-mvs-BLEND		36.62 213	53.39 162	17.06 231	0.01 240	58.61 157	48.63 177	0.01 237	47.13 114	0.02 242	43.98 147	60.64 71	0.03 237	54.92 205	51.47 210	53.64 215	56.99 197

PVSNet_Blended_VisFu		63.65 52	66.92 53	59.83 52	60.03 76	73.44 43	66.33 80	48.95 57	52.20 79	50.81 56	56.07 63	60.25 72	53.56 61	73.23 46	70.01 56	79.30 47	83.24 39

IS_MVSNet		57.95 102	64.26 68	50.60 120	61.62 69	65.25 94	57.18 129	45.42 73	50.79 82	26.49 173	57.81 59	60.05 73	34.51 172	71.24 56	70.20 55	78.36 54	74.44 99

Effi-MVS+-dtu		60.34 64	62.32 73	58.03 60	64.31 60	67.44 69	65.99 85	42.26 139	49.55 87	42.00 106	48.92 98	59.79 74	56.27 47	68.07 87	67.03 78	77.35 64	75.45 83

CNLPA		62.78 56	66.31 56	58.65 55	58.47 84	68.41 60	65.98 86	41.22 152	78.02 19	56.04 32	46.65 123	59.50 75	57.50 38	69.67 65	65.27 123	72.70 136	76.67 69

AdaColmap		67.89 41	68.85 51	66.77 25	73.73 17	74.30 38	75.28 35	53.58 31	70.24 41	57.59 30	51.19 83	59.19 76	60.74 24	75.33 38	73.72 41	79.69 45	77.96 60

FMVSNet2		55.04 124	59.95 101	49.31 129	52.42 162	61.44 124	57.03 130	44.08 87	49.55 87	30.40 151	46.89 121	58.84 77	38.22 151	67.07 117	66.21 94	73.69 116	69.65 121

IterMVS-LS		58.30 96	61.39 76	54.71 98	59.92 78	58.40 160	59.42 120	43.64 103	48.71 100	40.25 113	57.53 60	58.55 78	52.15 92	65.42 145	65.34 121	72.85 127	75.77 79
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
GBi-Net		55.20 121	60.25 88	49.31 129	52.42 162	61.44 124	57.03 130	44.04 88	49.18 92	30.47 148	48.28 109	58.19 79	38.22 151	68.05 88	66.96 79	73.69 116	69.65 121

test1		55.20 121	60.25 88	49.31 129	52.42 162	61.44 124	57.03 130	44.04 88	49.18 92	30.47 148	48.28 109	58.19 79	38.22 151	68.05 88	66.96 79	73.69 116	69.65 121

FMVSNet3		54.78 125	59.58 109	49.17 132	52.37 165	61.31 128	56.72 134	44.04 88	49.18 92	30.47 148	48.28 109	58.19 79	38.09 154	65.48 143	65.20 125	73.31 122	69.45 129

EPNet_dtu		52.05 142	58.26 122	44.81 170	54.10 154	50.09 195	52.01 167	40.82 157	53.03 75	27.41 169	54.90 68	57.96 82	26.72 198	62.97 154	62.70 157	67.78 176	66.19 150
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
HyFIR lowres test		56.87 110	58.60 120	54.84 97	56.62 130	69.27 56	64.77 96	42.21 140	45.66 135	37.50 123	33.08 199	57.47 83	53.33 67	65.46 144	67.94 69	74.60 105	71.35 111

Anonymous20240521		58.14 101	61.96 74	53.68 102	67.45 47	64.76 99	60.54 116	48.49 60	55.62 64	33.94 136	50.35 85	57.36 84	39.51 145	69.61 66	67.49 75	72.17 147	68.53 133

TSAR-MVS + COLMAP		62.65 57	69.90 48	54.19 100	46.31 193	66.73 76	65.49 91	41.36 150	76.57 21	46.31 70	76.80 13	56.68 85	53.27 69	69.50 67	66.65 86	72.40 142	76.36 77

MS-PatchMatch		58.19 99	60.20 90	55.85 93	65.17 57	64.16 101	64.82 94	41.48 149	50.95 81	42.17 105	45.38 139	56.42 86	48.08 109	68.30 77	66.70 84	73.39 120	69.46 128

Vis-MVSNet (Re-imp)		50.37 158	57.73 127	41.80 190	57.53 96	54.35 179	45.70 196	45.24 74	49.80 85	13.43 210	58.23 58	56.42 86	20.11 210	62.96 155	63.36 147	68.76 171	58.96 191

FC-MVSNet-train		58.40 94	63.15 71	52.85 111	64.29 61	61.84 120	55.98 140	46.47 64	53.06 74	34.96 133	61.95 48	56.37 88	39.49 146	68.67 72	68.36 67	75.92 100	71.81 109

FMVSNet1		54.08 127	58.68 118	48.71 143	50.90 176	61.35 127	56.73 133	43.94 92	45.91 129	29.32 158	42.72 167	56.26 89	37.70 155	68.05 88	66.96 79	73.69 116	69.50 125

Fast-Effi-MVS+		60.36 63	63.35 70	56.87 83	58.70 81	65.86 89	65.08 93	37.11 180	53.00 76	45.36 80	52.12 79	56.07 90	56.27 47	71.28 55	69.42 58	78.71 50	75.69 81

PLC	52.09 14	59.21 69	62.47 72	55.41 96	53.24 159	64.84 97	64.47 99	40.41 160	65.92 48	44.53 93	46.19 131	55.69 91	55.33 53	68.24 80	65.30 122	74.50 106	71.09 112
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
RPSCF		46.41 189	54.42 151	37.06 206	25.70 235	45.14 212	45.39 198	20.81 228	62.79 54	35.10 131	44.92 143	55.60 92	43.56 130	56.12 198	52.45 207	51.80 218	63.91 171

CostFormer		56.57 112	59.13 115	53.60 103	57.52 97	61.12 130	66.94 62	35.95 187	53.44 70	44.68 88	55.87 66	54.44 93	48.21 108	60.37 173	58.33 182	68.27 174	70.33 118

Fast-Effi-MVS+-dtu		56.30 113	59.29 114	52.82 112	58.64 83	64.89 96	65.56 90	32.89 205	45.80 134	35.04 132	45.89 134	54.14 94	49.41 101	67.16 115	66.45 92	75.37 102	70.69 115

CHOSEN 1792x2688		55.85 115	58.01 124	53.33 105	57.26 123	62.82 116	63.29 106	41.55 148	46.65 118	38.34 118	34.55 197	53.50 95	52.43 86	67.10 116	67.56 74	67.13 179	73.92 107

PMMVS		49.20 167	54.28 154	43.28 181	34.13 221	45.70 211	48.98 175	26.09 223	46.31 122	34.92 134	55.22 67	53.47 96	47.48 113	59.43 175	59.04 177	68.05 175	60.77 183

gg-mvs-nofinetune		49.07 168	52.56 167	45.00 169	61.99 68	59.78 144	53.55 162	41.63 143	31.62 215	12.08 212	29.56 208	53.28 97	29.57 188	66.27 130	64.49 135	71.19 156	62.92 174

v18		58.68 81	60.20 90	56.90 80	57.26 123	63.28 112	66.58 78	42.42 137	48.86 96	46.37 68	49.01 96	53.05 98	52.74 78	67.40 111	65.52 119	76.02 99	74.28 104

v17		58.69 79	60.19 93	56.94 73	57.38 105	63.37 110	66.67 76	42.47 136	48.52 106	46.10 73	48.90 99	53.00 99	52.84 71	67.58 100	65.60 113	76.19 92	74.38 101

v8		58.88 73	60.57 82	56.92 77	57.35 110	65.69 90	66.69 75	42.64 132	47.89 109	45.77 75	49.04 92	52.98 100	52.77 77	67.51 106	65.57 118	76.26 88	75.30 85

v6		58.89 72	60.54 83	56.96 72	57.34 112	66.13 85	66.71 71	42.84 124	47.85 110	45.80 74	49.04 92	52.95 101	52.79 74	67.53 103	65.59 114	76.26 88	74.73 89

v1neww		58.88 73	60.54 83	56.94 73	57.33 114	66.13 85	66.70 73	42.84 124	47.84 111	45.74 76	49.02 94	52.93 102	52.78 75	67.53 103	65.59 114	76.26 88	74.73 89

v7new		58.88 73	60.54 83	56.94 73	57.33 114	66.13 85	66.70 73	42.84 124	47.84 111	45.74 76	49.02 94	52.93 102	52.78 75	67.53 103	65.59 114	76.26 88	74.73 89

v16		58.71 78	60.20 90	56.97 71	57.35 110	63.36 111	66.67 76	42.49 134	48.69 102	46.36 69	48.87 100	52.92 104	52.82 73	67.57 101	65.58 117	76.15 94	74.38 101

CDS-MVSNet		52.42 139	57.06 132	47.02 159	53.92 156	58.30 162	55.50 143	46.47 64	42.52 168	29.38 157	49.50 88	52.85 105	28.49 193	66.70 122	66.89 82	68.34 172	62.63 177
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
V42		56.97 108	60.14 95	53.28 106	48.16 184	62.78 117	66.30 81	37.93 176	47.44 113	42.68 102	48.19 112	52.59 106	51.90 93	67.46 107	65.94 98	72.72 130	76.55 74

MVSTER		57.19 105	61.11 78	52.62 113	50.82 177	58.79 156	61.55 108	37.86 177	48.81 98	41.31 108	57.43 61	52.10 107	48.60 106	68.19 83	66.75 83	75.56 101	75.68 82

v15		58.43 93	59.75 102	56.88 82	57.45 101	63.44 108	66.84 66	42.65 131	46.24 123	45.07 82	48.68 104	52.07 108	52.63 83	67.84 93	65.70 107	76.65 76	74.31 103

V14		58.44 90	59.75 102	56.90 80	57.48 100	63.46 107	66.85 65	42.68 130	46.16 124	45.03 84	48.57 105	52.04 109	52.65 82	67.93 92	65.72 106	76.69 75	74.40 100

V9		58.45 89	59.75 102	56.92 77	57.51 98	63.49 106	66.86 63	42.73 129	46.07 127	45.05 83	48.45 107	51.99 110	52.66 81	68.04 91	65.75 103	76.72 74	74.50 98

v12		58.44 90	59.74 105	56.92 77	57.54 94	63.50 105	66.84 66	42.77 128	45.96 128	44.95 86	48.31 108	51.94 111	52.67 80	68.14 84	65.75 103	76.75 73	74.55 97

v13		58.44 90	59.72 106	56.94 73	57.55 92	63.51 104	66.86 63	42.81 127	45.90 130	44.98 85	48.17 115	51.87 112	52.68 79	68.20 81	65.78 101	76.78 71	74.63 95

divwei89l23v2f112		58.56 82	60.05 99	56.81 86	57.36 107	66.18 83	66.80 68	43.11 119	45.89 131	44.60 90	48.71 102	51.84 113	52.38 87	67.45 109	65.65 108	76.63 77	74.66 92

v1141		58.56 82	60.05 99	56.81 86	57.36 107	66.18 83	66.80 68	43.11 119	45.87 132	44.60 90	48.71 102	51.83 114	52.38 87	67.46 107	65.64 111	76.63 77	74.66 92

v1		58.56 82	60.06 98	56.83 85	57.36 107	66.19 82	66.80 68	43.10 121	45.87 132	44.68 88	48.73 101	51.83 114	52.38 87	67.45 109	65.65 108	76.63 77	74.66 92

LS3D		60.20 65	61.70 75	58.45 56	64.18 63	67.77 63	67.19 57	48.84 58	61.67 56	41.27 109	45.89 134	51.81 116	54.18 57	68.78 70	66.50 91	75.03 104	69.48 126

v10		59.17 71	60.60 81	57.50 67	57.95 88	66.73 76	67.09 60	44.11 85	46.85 115	45.42 79	48.18 114	51.07 117	53.63 59	67.84 93	66.59 88	76.79 69	76.92 67

v7		59.19 70	60.62 80	57.53 66	57.96 87	67.19 72	67.09 60	44.28 83	46.84 116	45.45 78	48.19 112	51.06 118	53.62 60	67.84 93	66.59 88	76.79 69	76.60 71

v2v482		58.69 79	60.12 97	57.03 70	57.16 127	66.05 88	67.17 58	43.52 108	46.33 121	45.19 81	49.46 89	51.02 119	52.51 85	67.30 113	66.03 96	76.61 80	74.62 96

IterMVS		53.45 132	57.12 131	49.17 132	49.23 181	60.93 131	59.05 122	34.63 191	44.53 140	33.22 138	51.09 84	51.01 120	48.38 107	62.43 158	60.79 168	70.54 160	69.05 131
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
IB-MVS	54.11 11	58.36 95	60.70 79	55.62 94	58.67 82	68.02 62	61.56 107	43.15 118	46.09 125	44.06 95	44.24 146	50.99 121	48.71 105	66.70 122	70.33 52	77.60 60	78.50 56
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
v11		58.19 99	59.47 111	56.70 88	57.54 94	63.42 109	66.28 82	42.49 134	45.62 136	44.59 92	48.16 116	50.78 122	52.84 71	67.80 97	65.76 102	76.49 83	74.76 88

UniMVSNet_NR-MVSNet		56.94 109	61.14 77	52.05 117	60.02 77	65.21 95	57.44 127	52.93 35	49.37 90	24.31 182	54.62 72	50.54 123	39.04 148	68.69 71	68.84 63	78.53 52	70.72 113

UniMVSNet (Re)		55.15 123	60.39 86	49.03 135	55.31 135	64.59 100	55.77 141	50.63 47	48.66 103	20.95 190	51.47 82	50.40 124	34.41 174	67.81 96	67.89 70	77.11 68	71.88 108

pm-mvs1		51.02 153	55.55 136	45.73 165	54.16 153	58.52 158	50.92 169	42.56 133	40.32 184	25.67 176	43.66 151	50.34 125	30.06 187	65.85 138	63.97 141	70.99 157	66.21 148

v148		55.58 118	57.61 128	53.20 108	54.59 149	61.86 119	61.18 110	38.70 172	44.30 144	42.25 104	47.53 118	50.24 126	48.73 104	65.15 146	62.61 158	73.79 114	71.61 110

v1144		58.88 73	60.16 94	57.39 68	58.03 86	67.26 70	67.14 59	44.46 82	45.17 138	44.33 94	47.81 117	49.92 127	53.20 70	67.77 98	66.62 87	77.15 66	76.58 72

TAMVS		44.02 197	49.18 193	37.99 204	47.03 191	45.97 210	45.04 199	28.47 215	39.11 193	20.23 193	43.22 158	48.52 128	28.49 193	58.15 185	57.95 184	58.71 201	51.36 208

CMPMVS	37.70 17	49.24 165	52.71 165	45.19 167	45.97 195	51.23 191	47.44 184	29.31 212	43.04 155	44.69 87	34.45 198	48.35 129	43.64 129	62.59 156	59.82 174	60.08 199	69.48 126
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
v144192		58.23 98	59.40 113	56.87 83	57.56 91	66.89 74	65.70 88	45.01 77	44.06 146	42.88 99	46.61 124	48.09 130	53.49 65	66.94 118	65.90 99	76.61 80	77.29 63

v1192		58.51 85	59.66 107	57.17 69	57.82 89	67.72 64	66.21 83	44.83 78	44.15 145	43.49 97	46.68 122	47.94 131	53.55 62	67.39 112	66.51 90	77.13 67	77.20 65

test-LLR		49.28 164	50.29 187	48.10 150	55.26 136	47.16 203	49.52 172	43.48 111	39.22 190	31.98 142	43.65 152	47.93 132	41.29 140	56.80 191	55.36 191	67.08 180	61.94 178

TESTMET0.1,1		46.09 192	50.29 187	41.18 193	36.91 217	47.16 203	49.52 172	20.32 229	39.22 190	31.98 142	43.65 152	47.93 132	41.29 140	56.80 191	55.36 191	67.08 180	61.94 178

GA-MVS		55.67 116	58.33 121	52.58 114	55.23 138	63.09 113	61.08 111	40.15 162	42.95 156	37.02 126	52.61 77	47.68 134	47.51 112	65.92 137	65.35 120	74.49 107	70.68 116

Baseline_NR-MVSNet		53.50 131	57.89 125	48.37 146	54.60 147	59.25 152	56.10 137	51.84 39	49.32 91	17.92 202	45.38 139	47.68 134	36.93 164	68.11 85	65.95 97	72.84 128	69.57 124

CVMVSNet		46.38 191	52.01 173	39.81 197	42.40 207	50.26 193	46.15 193	37.68 178	40.03 186	15.09 207	46.56 126	47.56 136	33.72 177	56.50 195	55.65 189	63.80 191	67.53 135

tpm		48.82 169	51.27 180	45.96 164	54.10 154	47.35 202	56.05 138	30.23 210	46.70 117	43.21 98	52.54 78	47.55 137	37.28 162	54.11 206	50.50 211	54.90 212	60.12 187

MDTV_nov1_ep13		50.32 159	52.43 169	47.86 154	49.87 180	54.70 177	58.10 124	34.29 193	45.59 137	37.71 121	47.44 119	47.42 138	41.86 137	58.07 186	55.21 193	65.34 187	58.56 192

TranMVSNet+NR-MVSNet		55.87 114	60.14 95	50.88 119	59.46 80	63.82 102	57.93 125	52.98 34	48.94 95	20.52 192	52.87 76	47.33 139	36.81 165	69.12 69	69.03 61	77.56 62	69.89 119

MIMVSNet		43.79 198	48.53 195	38.27 202	41.46 209	48.97 198	50.81 170	32.88 206	44.55 139	22.07 186	32.05 200	47.15 140	24.76 201	58.73 180	56.09 187	57.63 206	52.14 206

v52		53.60 129	56.74 133	49.93 126	45.54 196	61.64 122	60.65 113	36.99 182	38.75 194	36.32 128	39.64 185	47.13 141	47.05 115	66.89 119	65.65 108	73.04 125	77.48 61

V4		53.60 129	56.73 134	49.93 126	45.54 196	61.64 122	60.65 113	36.99 182	38.74 196	36.33 127	39.64 185	47.12 142	47.05 115	66.89 119	65.64 111	73.04 125	77.48 61

CHOSEN 280x420		40.80 205	45.05 206	35.84 209	32.95 224	29.57 231	44.98 200	23.71 226	37.54 203	18.42 200	31.36 203	47.07 143	46.41 120	56.71 193	54.65 198	48.55 223	58.47 193

DU-MVS		55.41 119	59.59 108	50.54 122	54.60 147	62.97 114	57.44 127	51.80 40	48.62 104	24.31 182	51.99 80	47.00 144	39.04 148	68.11 85	67.75 72	76.03 98	70.72 113

v1921920		57.89 103	59.02 116	56.58 90	57.55 92	66.66 79	64.72 97	44.70 80	43.55 149	42.73 101	46.17 132	46.93 145	53.51 63	66.78 121	65.75 103	76.29 86	77.28 64

pmmvs6		48.35 172	51.64 174	44.51 173	51.92 168	57.94 164	49.44 174	42.17 141	34.45 208	24.62 181	28.87 212	46.90 146	29.07 191	64.60 149	63.08 151	69.83 163	65.68 156

test-mter		45.30 193	50.37 186	39.38 198	33.65 223	46.99 205	47.59 182	18.59 231	38.75 194	28.00 162	43.28 157	46.82 147	41.50 139	57.28 189	55.78 188	66.93 183	63.70 172

tpmp4_e23		56.84 111	57.14 130	56.49 91	62.45 67	62.05 118	67.57 54	41.56 147	54.17 68	48.57 63	49.18 90	46.54 148	50.44 99	61.93 165	58.82 179	68.34 172	67.28 139

TransMVSNet (Re)		51.92 147	55.38 140	47.88 153	60.95 73	59.90 142	53.95 156	45.14 75	39.47 189	24.85 179	43.87 149	46.51 149	29.15 189	67.55 102	65.23 124	73.26 124	65.16 163

v1240		57.55 104	58.63 119	56.29 92	57.30 120	66.48 80	63.77 102	44.56 81	42.77 165	42.48 103	45.64 137	46.28 150	53.46 66	66.32 129	65.80 100	76.16 93	77.13 66

tpmrst		48.08 176	49.88 191	45.98 163	52.71 161	48.11 200	53.62 160	33.70 198	48.70 101	39.74 114	48.96 97	46.23 151	40.29 144	50.14 215	49.28 213	55.80 209	57.71 194

EG-PatchMatch MVS		56.98 107	58.24 123	55.50 95	64.66 59	68.62 58	61.48 109	43.63 105	38.44 198	41.44 107	38.05 190	46.18 152	43.95 127	71.71 51	70.61 50	77.87 56	74.08 106

WR-MVS		48.78 170	55.06 146	41.45 192	55.50 134	60.40 132	43.77 205	49.99 52	41.92 171	8.10 225	45.24 142	45.56 153	17.47 212	61.57 167	64.60 129	73.85 113	66.14 151

anonymousdsp		52.84 135	57.78 126	47.06 158	40.24 212	58.95 155	53.70 158	33.54 200	36.51 205	32.69 141	43.88 148	45.40 154	47.97 111	67.17 114	70.28 53	74.22 109	82.29 42

MSDG		58.46 88	58.97 117	57.85 65	66.27 54	66.23 81	67.72 53	42.33 138	53.43 71	43.68 96	43.39 154	45.35 155	49.75 100	68.66 73	67.77 71	77.38 63	67.96 134

PatchmatchNet		49.92 162	51.29 179	48.32 147	51.83 170	51.86 189	53.38 163	37.63 179	47.90 108	40.83 110	48.54 106	45.30 156	45.19 124	56.86 190	53.99 202	61.08 198	54.57 203
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
v7n		55.67 116	57.46 129	53.59 104	56.06 131	65.29 92	61.06 112	43.26 116	40.17 185	37.99 120	40.79 181	45.27 157	47.09 114	67.67 99	66.21 94	76.08 96	76.82 68

ACMH+	53.71 12	59.26 68	60.28 87	58.06 58	64.17 64	68.46 59	67.51 56	50.93 45	52.46 78	35.83 130	40.83 180	45.12 158	52.32 90	69.88 64	69.00 62	77.59 61	76.21 78

thres200		52.39 140	55.37 142	48.90 140	57.39 104	60.18 136	55.60 142	43.73 100	42.93 157	27.41 169	43.35 155	45.09 159	36.61 166	66.36 127	63.92 142	72.66 137	65.78 155

tfpn111		52.44 138	55.38 140	49.01 136	57.31 116	60.24 133	55.42 145	43.77 94	42.85 159	27.51 165	42.03 174	45.06 160	37.32 157	66.38 124	64.54 130	72.71 133	66.54 142

conf200view11		52.51 137	55.51 137	49.01 136	57.31 116	60.24 133	55.42 145	43.77 94	42.85 159	27.51 165	43.00 163	45.06 160	37.32 157	66.38 124	64.54 130	72.71 133	66.54 142

thres100view900		52.04 143	54.81 149	48.80 141	57.31 116	59.33 148	55.30 150	42.92 123	42.85 159	27.81 163	43.00 163	45.06 160	36.99 163	64.74 148	63.51 145	72.47 141	65.21 162

tfpn200view9		52.53 136	55.51 137	49.06 134	57.31 116	60.24 133	55.42 145	43.77 94	42.85 159	27.81 163	43.00 163	45.06 160	37.32 157	66.38 124	64.54 130	72.71 133	66.54 142

thres400		52.38 141	55.51 137	48.74 142	57.49 99	60.10 140	55.45 144	43.54 107	42.90 158	26.72 172	43.34 156	45.03 164	36.61 166	66.20 134	64.53 134	72.66 137	66.43 145

pmmvs4		54.66 126	56.07 135	53.00 110	54.63 146	57.08 168	60.43 118	44.10 86	51.69 80	40.55 111	46.55 127	44.79 165	45.95 121	62.54 157	63.66 143	72.36 144	66.20 149

NR-MVSNet		55.35 120	59.46 112	50.56 121	61.33 70	62.97 114	57.91 126	51.80 40	48.62 104	20.59 191	51.99 80	44.73 166	34.10 175	68.58 74	68.64 65	77.66 58	70.67 117

test0.0.03 1		43.15 199	46.95 200	38.72 201	55.26 136	50.56 192	42.48 208	43.48 111	38.16 202	15.11 206	35.07 196	44.69 167	16.47 215	55.95 200	54.34 199	59.54 200	49.87 215

CR-MVSNet		50.47 156	52.61 166	47.98 152	49.03 183	52.94 183	48.27 178	38.86 169	44.41 141	39.59 115	44.34 145	44.65 168	46.63 118	58.97 178	60.31 171	65.48 185	62.66 175

view600		51.96 146	55.13 145	48.27 148	57.41 103	60.05 141	54.74 153	43.64 103	42.57 167	25.88 175	43.11 161	44.48 169	35.34 169	66.27 130	63.61 144	72.61 140	65.80 154

thres600view7		51.91 148	55.14 144	48.14 149	57.43 102	60.18 136	54.60 154	43.73 100	42.61 166	25.20 177	43.10 162	44.47 170	35.19 170	66.36 127	63.28 150	72.66 137	66.01 152

EPMVS		44.66 195	47.86 198	40.92 194	47.97 186	44.70 213	47.58 183	33.27 201	48.11 107	29.58 156	49.65 87	44.38 171	34.65 171	51.71 210	47.90 217	52.49 217	48.57 217

WR-MVS_H		47.65 179	53.67 158	40.63 195	51.45 171	59.74 146	44.71 202	49.37 54	40.69 182	7.61 227	46.04 133	44.34 172	17.32 213	57.79 187	61.18 162	73.30 123	65.86 153

tpm cat1		53.30 133	53.41 161	53.17 109	58.16 85	59.15 153	63.73 103	38.27 175	50.73 83	46.98 65	45.57 138	44.00 173	49.20 103	55.90 201	54.02 200	62.65 194	64.50 168

v748		52.93 134	55.29 143	50.19 124	51.90 169	61.31 128	56.54 135	40.05 164	39.12 192	34.82 135	39.93 184	43.83 174	43.66 128	64.26 150	63.32 148	74.15 110	75.28 86

view800		51.55 150	54.89 147	47.66 156	57.37 106	59.77 145	53.62 160	43.72 102	42.22 169	24.94 178	42.80 166	43.81 175	33.94 176	66.09 135	64.38 136	72.39 143	65.14 164

pmmvs5		47.07 186	51.02 185	42.46 186	45.18 198	51.47 190	48.23 180	33.09 204	38.17 201	28.62 161	46.60 125	43.48 176	30.74 185	58.28 184	58.63 181	68.92 170	60.48 184

tfpn_ndepth		48.34 173	52.27 170	43.76 176	54.35 151	56.46 169	47.24 186	40.92 153	43.45 151	21.04 189	41.16 179	43.22 177	28.90 192	61.57 167	60.65 169	70.12 162	59.34 189

conf0.05thres1000		50.64 154	53.84 156	46.92 161	57.02 128	59.29 150	52.29 166	43.80 93	39.84 188	23.81 185	39.26 187	43.14 178	32.52 182	65.74 139	64.04 138	72.05 149	65.53 158

FMVSNet5		40.96 204	45.81 203	35.29 210	34.30 220	44.55 214	47.28 185	28.84 214	40.76 181	21.62 187	29.85 206	42.44 179	24.77 200	57.53 188	55.00 194	54.93 211	50.56 211

FC-MVSNet-test		39.65 210	48.35 196	29.49 217	44.43 200	39.28 220	30.23 227	40.44 159	43.59 148	3.12 237	53.00 75	42.03 180	10.02 233	55.09 203	54.77 195	48.66 222	50.71 210

MDTV_nov1_ep13_2view		47.62 180	49.72 192	45.18 168	48.05 185	53.70 181	54.90 152	33.80 197	39.90 187	29.79 155	38.85 189	41.89 181	39.17 147	58.99 177	55.55 190	65.34 187	59.17 190

PEN-MVS		49.21 166	54.32 152	43.24 182	54.33 152	59.26 151	47.04 187	51.37 44	41.67 174	9.97 220	46.22 130	41.80 182	22.97 207	60.52 171	64.03 139	73.73 115	66.75 141

tfpn1000		46.75 188	51.24 181	41.51 191	54.39 150	55.60 173	43.85 204	40.90 154	41.82 172	16.71 204	41.26 178	41.58 183	23.96 202	60.76 170	60.27 173	69.26 165	57.42 195

tfpn_n400		47.56 182	51.56 176	42.90 184	54.91 142	55.28 175	46.21 190	41.59 144	41.51 176	18.54 197	42.25 171	41.54 184	27.12 195	62.41 159	61.02 165	69.05 167	56.90 198

tfpnconf		47.56 182	51.56 176	42.90 184	54.91 142	55.28 175	46.21 190	41.59 144	41.51 176	18.54 197	42.25 171	41.54 184	27.12 195	62.41 159	61.02 165	69.05 167	56.90 198

tfpnview11		47.58 181	51.57 175	42.92 183	54.94 141	55.30 174	46.21 190	41.58 146	42.10 170	18.54 197	42.25 171	41.54 184	27.12 195	62.29 162	61.12 163	69.15 166	56.40 200

ACMH	52.42 13	58.24 97	59.56 110	56.70 88	66.34 53	69.59 54	66.71 71	49.12 56	46.08 126	28.90 159	42.67 168	41.20 187	52.60 84	71.39 53	70.28 53	76.51 82	75.72 80
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
DWT-MVSNet_training		53.80 128	54.31 153	53.21 107	57.65 90	59.04 154	60.65 113	40.11 163	46.35 120	42.77 100	49.07 91	41.07 188	51.06 98	58.62 183	58.96 178	67.00 182	67.06 140

Anonymous20231206		42.28 201	45.89 202	38.07 203	51.96 167	48.98 197	43.66 206	38.81 171	38.74 196	14.32 209	26.74 214	40.90 189	20.94 208	56.64 194	54.67 197	58.71 201	54.59 202

DTE-MVSNet		48.03 178	53.28 163	41.91 189	54.64 145	57.50 166	44.63 203	51.66 43	41.02 180	7.97 226	46.26 129	40.90 189	20.24 209	60.45 172	62.89 154	72.33 145	63.97 170

testgi		38.71 211	43.64 208	32.95 213	52.30 166	48.63 199	35.59 221	35.05 190	31.58 216	9.03 224	30.29 204	40.75 191	11.19 231	55.30 202	53.47 205	54.53 214	45.48 219

CP-MVSNet		48.37 171	53.53 160	42.34 187	51.35 173	58.01 163	46.56 188	50.54 48	41.62 175	10.61 216	46.53 128	40.68 192	23.18 204	58.71 181	61.83 160	71.81 151	67.36 138

ADS-MVSNet		40.67 207	43.38 209	37.50 205	44.36 201	39.79 219	42.09 210	32.67 207	44.34 143	28.87 160	40.76 182	40.37 193	30.22 186	48.34 225	45.87 223	46.81 226	44.21 221

PS-CasMVS		48.18 174	53.25 164	42.27 188	51.26 174	57.94 164	46.51 189	50.52 49	41.30 178	10.56 218	45.35 141	40.34 194	23.04 206	58.66 182	61.79 161	71.74 153	67.38 137

PatchT		48.08 176	51.03 184	44.64 171	42.96 206	50.12 194	40.36 213	35.09 189	43.17 154	39.59 115	42.00 176	39.96 195	46.63 118	58.97 178	60.31 171	63.21 192	62.66 175

conf0.01		52.02 144	54.62 150	49.00 138	57.30 120	60.17 138	55.42 145	43.76 97	42.85 159	27.49 167	43.12 160	39.71 196	37.32 157	66.26 132	64.54 130	72.72 130	65.66 157

PatchMatch-RL		50.11 161	51.56 176	48.43 145	46.23 194	51.94 188	50.21 171	38.62 173	46.62 119	37.51 122	42.43 170	39.38 197	52.24 91	60.98 169	59.56 175	65.76 184	60.01 188

test20.03		40.38 209	44.20 207	35.92 208	53.73 157	49.05 196	38.54 215	43.49 110	32.55 212	9.54 221	27.88 213	39.12 198	12.24 226	56.28 196	54.69 196	57.96 205	49.83 216

pmmvs-eth3d		51.33 151	52.25 171	50.26 123	50.82 177	54.65 178	56.03 139	43.45 113	43.51 150	37.20 125	39.20 188	39.04 199	42.28 135	61.85 166	62.78 155	71.78 152	64.72 166

COLMAP_ROB	46.52 15	51.99 145	54.86 148	48.63 144	49.13 182	61.73 121	60.53 117	36.57 184	53.14 73	32.95 140	37.10 191	38.68 200	40.49 142	65.72 140	63.08 151	72.11 148	64.60 167
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
MVS-HIRNet		42.24 202	41.15 214	43.51 178	44.06 205	40.74 216	35.77 220	35.35 188	35.38 206	38.34 118	25.63 216	38.55 201	43.48 131	50.77 212	47.03 221	64.07 189	49.98 213

tfpnnormal		50.16 160	52.19 172	47.78 155	56.86 129	58.37 161	54.15 155	44.01 91	38.35 200	25.94 174	36.10 193	37.89 202	34.50 173	65.93 136	63.42 146	71.26 155	65.28 160

tfpn		50.58 155	53.65 159	47.00 160	57.34 112	59.31 149	52.41 165	43.76 97	41.81 173	23.86 184	42.49 169	37.80 203	32.63 181	65.68 142	64.02 140	71.99 150	64.41 169

EU-MVSNet		40.63 208	45.65 204	34.78 211	39.11 213	46.94 206	40.02 214	34.03 194	33.50 210	10.37 219	35.57 195	37.80 203	23.65 203	51.90 209	50.21 212	61.49 197	63.62 173

dps		50.42 157	51.20 183	49.51 128	55.88 132	56.07 170	53.73 157	38.89 168	43.66 147	40.36 112	45.66 136	37.63 205	45.23 123	59.05 176	56.18 185	62.94 193	60.16 186

RPMNet		46.41 189	48.72 194	43.72 177	47.77 187	52.94 183	46.02 195	33.92 195	44.41 141	31.82 145	36.89 192	37.42 206	37.41 156	53.88 207	54.02 200	65.37 186	61.47 180

thresconf0.02		48.17 175	51.22 182	44.60 172	55.14 139	55.73 172	48.95 176	41.35 151	43.43 153	21.23 188	42.03 174	37.25 207	31.19 184	62.33 161	60.61 170	69.76 164	57.17 196

conf0.002		51.76 149	54.13 155	49.00 138	57.28 122	60.15 139	55.42 145	43.75 99	42.85 159	27.49 167	43.13 159	37.12 208	37.32 157	66.23 133	64.17 137	72.72 130	65.24 161

MIMVSNet1		35.51 214	41.41 213	28.63 219	27.53 231	43.36 215	38.09 216	33.82 196	32.01 213	6.77 228	21.63 224	35.43 209	11.97 228	55.05 204	53.99 202	53.59 216	48.36 218

LTVRE_ROB	44.17 16	47.06 187	50.15 190	43.44 179	51.39 172	58.42 159	42.90 207	43.51 109	22.27 230	14.85 208	41.94 177	34.57 210	45.43 122	62.28 163	62.77 156	62.56 195	68.83 132
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
PM-MVS		44.55 196	48.13 197	40.37 196	32.85 225	46.82 207	46.11 194	29.28 213	40.48 183	29.99 153	39.98 183	34.39 211	41.80 138	56.08 199	53.88 204	62.19 196	65.31 159

USDC		51.11 152	53.71 157	48.08 151	44.76 199	55.99 171	53.01 164	40.90 154	52.49 77	36.14 129	44.67 144	33.66 212	43.27 133	63.23 153	61.10 164	70.39 161	64.82 165

gm-plane-assit		44.74 194	45.95 201	43.33 180	60.88 74	46.79 208	36.97 217	32.24 209	24.15 226	11.79 213	29.26 211	32.97 213	46.64 117	65.09 147	62.95 153	71.45 154	60.42 185

SixPastTwentyTwo		47.55 184	50.25 189	44.41 174	47.30 190	54.31 180	47.81 181	40.36 161	33.76 209	19.93 194	43.75 150	32.77 214	42.07 136	59.82 174	60.94 167	68.98 169	66.37 147

N_pmnet		32.67 220	36.85 218	27.79 221	40.55 211	32.13 230	35.80 219	26.79 221	37.24 204	9.10 222	32.02 201	30.94 215	16.30 216	47.22 226	41.21 226	38.21 229	37.21 226

TDRefinement		49.31 163	52.44 168	45.67 166	30.44 227	59.42 147	59.24 121	39.78 165	48.76 99	31.20 147	35.73 194	29.90 216	42.81 134	64.24 151	62.59 159	70.55 159	66.43 145

testpf		34.85 216	36.16 221	33.31 212	47.49 188	35.56 227	36.85 218	32.31 208	23.08 227	15.63 205	29.39 209	29.48 217	19.62 211	41.38 228	41.07 227	47.95 224	53.18 204

LP		40.79 206	41.99 211	39.38 198	40.98 210	46.49 209	42.14 209	33.66 199	35.37 207	29.89 154	29.30 210	27.81 218	32.74 179	52.55 208	52.19 208	56.87 207	50.23 212

new-patchmatchnet		33.24 219	37.20 217	28.62 220	44.32 202	38.26 224	29.68 230	36.05 186	31.97 214	6.33 229	26.59 215	27.33 219	11.12 232	50.08 216	41.05 228	44.23 227	45.15 220

pmmvs3		35.10 215	38.47 216	31.17 215	26.37 234	40.47 217	34.51 223	18.09 232	24.75 224	16.88 203	23.05 220	26.69 220	32.69 180	50.73 213	51.60 209	58.46 204	51.98 207

testus		31.33 222	36.31 220	25.52 225	37.55 215	38.40 221	25.87 231	23.58 227	26.46 222	5.97 230	24.15 218	24.92 221	12.44 225	49.14 222	48.21 216	47.73 225	42.86 222

FPMVS		38.36 212	40.41 215	35.97 207	38.92 214	39.85 218	45.50 197	25.79 224	41.13 179	18.70 196	30.10 205	24.56 222	31.86 183	49.42 220	46.80 222	55.04 210	51.03 209

test2356		33.40 218	36.53 219	29.76 216	37.51 216	38.39 222	34.68 222	27.35 217	27.88 218	10.61 216	25.54 217	24.44 223	17.15 214	49.99 217	48.32 215	51.24 219	41.16 225

1111		31.35 221	33.52 225	28.83 218	44.28 203	32.44 228	31.71 225	33.25 202	27.87 219	10.92 214	22.18 222	24.05 224	15.89 217	49.03 223	44.09 224	36.94 231	34.96 227

.test1245		22.44 229	22.23 230	22.67 227	44.28 203	32.44 228	31.71 225	33.25 202	27.87 219	10.92 214	22.18 222	24.05 224	15.89 217	49.03 223	0.01 235	0.00 239	0.06 237

PMVS	27.84 18	33.81 217	35.28 222	32.09 214	34.13 221	24.81 234	32.51 224	26.48 222	26.41 223	19.37 195	23.76 219	24.02 226	25.18 199	50.78 211	47.24 220	54.89 213	49.95 214
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
TinyColmap		47.08 185	47.56 199	46.52 162	42.35 208	53.44 182	51.77 168	40.70 158	43.44 152	31.92 144	29.78 207	23.72 227	45.04 125	61.99 164	59.54 176	67.35 178	61.03 182

Anonymous20231211		42.81 200	41.57 212	44.25 175	54.71 144	52.32 187	41.42 211	45.09 76	24.45 225	33.54 137	14.58 229	23.43 228	23.08 205	56.20 197	58.74 180	67.68 177	61.31 181

MDA-MVSNet-bldmvs		41.36 203	43.15 210	39.27 200	28.74 229	52.68 185	44.95 201	40.84 156	32.89 211	18.13 201	31.61 202	22.09 229	38.97 150	50.45 214	56.11 186	64.01 190	56.23 201

testmv		30.97 223	34.42 223	26.95 222	36.49 218	37.38 225	29.80 228	27.28 218	22.34 228	4.72 231	20.63 226	20.64 230	13.22 223	49.86 219	47.74 218	50.20 220	42.36 223

test1235678		30.97 223	34.42 223	26.95 222	36.49 218	37.38 225	29.79 229	27.28 218	22.33 229	4.72 231	20.62 227	20.64 230	13.22 223	49.87 218	47.74 218	50.20 220	42.36 223

new_pmnet		23.19 228	28.17 228	17.37 229	17.03 236	24.92 233	19.66 235	16.16 234	27.05 221	4.42 233	20.77 225	19.20 232	12.19 227	37.71 230	36.38 229	34.77 232	31.17 229

test12356		23.91 227	28.47 227	18.60 228	26.80 233	28.30 232	20.92 233	19.76 230	19.89 231	2.88 239	18.48 228	16.57 233	4.05 234	42.34 227	41.93 225	37.21 230	31.75 228

ambc			45.54 205		50.66 179	52.63 186	40.99 212		38.36 199	24.67 180	22.62 221	13.94 234	29.14 190	65.71 141	58.06 183	58.60 203	67.43 136

no-one		29.19 225	31.89 226	26.05 224	30.96 226	38.33 223	21.54 232	29.86 211	15.84 234	3.56 234	11.28 233	13.03 235	14.44 222	38.96 229	52.83 206	55.96 208	52.92 205

PMMVS2		15.84 230	19.68 231	11.35 233	15.74 237	16.95 236	13.31 236	17.64 233	16.08 233	0.36 241	13.12 230	11.47 236	1.69 236	28.82 231	27.24 231	19.38 235	24.09 232

tmp_tt				5.40 235	3.97 239	2.35 241	3.26 241	0.44 236	17.56 232	12.09 211	11.48 232	7.14 237	1.98 235	15.68 234	15.49 234	10.69 237

DeepMVS_CX						6.95 240	5.98 240	2.25 235	11.73 237	2.07 240	11.85 231	5.43 238	11.75 230	11.40 236		8.10 238	18.38 234

Gipuma		25.87 226	26.91 229	24.66 226	28.98 228	20.17 235	20.46 234	34.62 192	29.55 217	9.10 222	4.91 237	5.31 239	15.76 219	49.37 221	49.10 214	39.03 228	29.95 230
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
MVE	12.28 19	13.53 233	15.72 232	10.96 234	7.39 238	15.71 237	6.05 239	23.73 225	10.29 238	3.01 238	5.77 236	3.41 240	11.91 229	20.11 232	29.79 230	13.67 236	24.98 231
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
EMVS		14.49 232	12.45 234	16.87 232	27.02 232	12.56 239	8.13 237	27.19 220	15.05 235	3.14 236	6.69 235	2.67 241	15.08 221	14.60 235	18.05 233	20.67 234	17.56 235

E-PMN		15.09 231	13.19 233	17.30 230	27.80 230	12.62 238	7.81 238	27.54 216	14.62 236	3.19 235	6.89 234	2.52 242	15.09 220	15.93 233	20.22 232	22.38 233	19.53 233

sosnet-low-res		0.00 236	0.00 237	0.00 236	0.00 241	0.00 242	0.00 244	0.00 238	0.00 241	0.00 243	0.00 240	0.00 243	0.00 240	0.00 238	0.00 238	0.00 239	0.00 239

sosnet		0.00 236	0.00 237	0.00 236	0.00 241	0.00 242	0.00 244	0.00 238	0.00 241	0.00 243	0.00 240	0.00 243	0.00 240	0.00 238	0.00 238	0.00 239	0.00 239

testmvs		0.01 234	0.02 235	0.00 236	0.00 241	0.00 242	0.01 243	0.00 238	0.01 239	0.00 243	0.03 239	0.00 243	0.01 238	0.01 237	0.01 235	0.00 239	0.06 237

test123		0.01 234	0.02 235	0.00 236	0.00 241	0.00 242	0.00 244	0.00 238	0.01 239	0.00 243	0.04 238	0.00 243	0.01 238	0.00 238	0.01 235	0.00 239	0.07 236

our_test_3					51.15 175	57.31 167	55.12 151

Patchmatch-RL test							1.04 242

NP-MVS									72.00 35

Patchmtry						47.61 201	48.27 178	38.86 169		39.59 115

High-resolution multi-view benchmark