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	botani.	boulde.	bridge	door	exhibi.	lectur.	living.	lounge	observ.	old co.	statue	terrac.

mamv4		90.28 1	88.75 1	94.85 1	93.34 1	96.17 1	82.69 57	91.63 1	86.34 1	97.97 1	94.77 3	66.57 122	95.38 1	87.74 1	97.72 1	93.00 7

LCM-MVSNet		86.90 2	88.67 2	81.57 25	91.50 2	63.30 124	84.80 35	87.77 10	86.18 2	96.26 2	96.06 1	90.32 1	84.49 72	68.08 96	97.05 2	96.93 1

TDRefinement		86.32 3	86.33 3	86.29 2	88.64 32	81.19 5	88.84 4	90.72 2	78.27 12	87.95 18	92.53 14	79.37 15	84.79 69	74.51 52	96.15 3	92.88 8

reproduce-ours		84.97 4	85.93 4	82.10 21	86.11 57	77.53 18	87.08 13	85.81 28	78.70 10	88.94 13	91.88 24	79.74 12	86.05 32	79.90 9	95.21 16	82.72 174

our_new_method		84.97 4	85.93 4	82.10 21	86.11 57	77.53 18	87.08 13	85.81 28	78.70 10	88.94 13	91.88 24	79.74 12	86.05 32	79.90 9	95.21 16	82.72 174

reproduce_model		84.87 6	85.80 6	82.05 23	85.52 66	78.14 13	87.69 6	85.36 38	79.26 7	89.12 12	92.10 19	77.52 25	85.92 39	80.47 8	95.20 18	82.10 189

SR-MVS-dyc-post		84.75 7	85.26 9	83.21 4	86.19 50	79.18 7	87.23 9	86.27 20	77.51 14	87.65 22	90.73 50	79.20 16	85.58 51	78.11 27	94.46 39	84.89 97

HPM-MVS_fast		84.59 8	85.10 10	83.06 5	88.60 33	75.83 27	86.27 27	86.89 16	73.69 27	86.17 40	91.70 29	78.23 21	85.20 61	79.45 16	94.91 28	88.15 48

SR-MVS		84.51 9	85.27 8	82.25 19	88.52 34	77.71 15	86.81 19	85.25 40	77.42 17	86.15 41	90.24 73	81.69 5	85.94 36	77.77 30	93.58 64	83.09 160

ACMMP		84.22 10	84.84 12	82.35 18	89.23 22	76.66 26	87.65 7	85.89 26	71.03 47	85.85 45	90.58 54	78.77 18	85.78 44	79.37 19	95.17 20	84.62 109
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
LTVRE_ROB	75.46 1	84.22 10	84.98 11	81.94 24	84.82 76	75.40 29	91.60 3	87.80 8	73.52 28	88.90 15	93.06 7	71.39 73	81.53 119	81.53 4	92.15 84	88.91 38
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
HPM-MVS		84.12 12	84.63 13	82.60 14	88.21 36	74.40 35	85.24 31	87.21 14	70.69 50	85.14 57	90.42 61	78.99 17	86.62 15	80.83 6	94.93 27	86.79 64
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
CP-MVS		84.12 12	84.55 14	82.80 11	89.42 18	79.74 6	88.19 5	84.43 61	71.96 43	84.70 64	90.56 55	77.12 28	86.18 28	79.24 21	95.36 13	82.49 181

mPP-MVS		84.01 14	84.39 15	82.88 7	90.65 4	81.38 4	87.08 13	82.79 87	72.41 39	85.11 58	90.85 47	76.65 31	84.89 66	79.30 20	94.63 36	82.35 183

COLMAP_ROB	72.78 3	83.75 15	84.11 19	82.68 13	82.97 106	74.39 36	87.18 11	88.18 7	78.98 8	86.11 43	91.47 34	79.70 14	85.76 45	66.91 115	95.46 12	87.89 49
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
ACMMPR		83.62 16	83.93 21	82.69 12	89.78 11	77.51 22	87.01 17	84.19 68	70.23 51	84.49 66	90.67 53	75.15 44	86.37 20	79.58 14	94.26 52	84.18 127

APD-MVS_3200maxsize		83.57 17	84.33 16	81.31 32	82.83 109	73.53 44	85.50 30	87.45 13	74.11 23	86.45 38	90.52 58	80.02 10	84.48 73	77.73 31	94.34 50	85.93 76

region2R		83.54 18	83.86 23	82.58 15	89.82 10	77.53 18	87.06 16	84.23 67	70.19 53	83.86 73	90.72 52	75.20 43	86.27 23	79.41 18	94.25 53	83.95 132

XVS		83.51 19	83.73 24	82.85 9	89.43 16	77.61 16	86.80 20	84.66 56	72.71 32	82.87 83	90.39 65	73.86 55	86.31 21	78.84 23	94.03 56	84.64 107

LPG-MVS_test		83.47 20	84.33 16	80.90 36	87.00 40	70.41 64	82.04 61	86.35 17	69.77 55	87.75 19	91.13 38	81.83 3	86.20 26	77.13 39	95.96 6	86.08 72

HFP-MVS		83.39 21	84.03 20	81.48 27	89.25 21	75.69 28	87.01 17	84.27 64	70.23 51	84.47 67	90.43 60	76.79 29	85.94 36	79.58 14	94.23 54	82.82 170

MTAPA		83.19 22	83.87 22	81.13 34	91.16 3	78.16 12	84.87 33	80.63 132	72.08 41	84.93 59	90.79 48	74.65 49	84.42 75	80.98 5	94.75 32	80.82 214

MP-MVS		83.19 22	83.54 27	82.14 20	90.54 5	79.00 9	86.42 25	83.59 77	71.31 44	81.26 103	90.96 42	74.57 50	84.69 70	78.41 25	94.78 31	82.74 173
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
ZNCC-MVS		83.12 24	83.68 25	81.45 28	89.14 25	73.28 46	86.32 26	85.97 25	67.39 65	84.02 71	90.39 65	74.73 48	86.46 17	80.73 7	94.43 43	84.60 112

PGM-MVS		83.07 25	83.25 34	82.54 16	89.57 14	77.21 24	82.04 61	85.40 36	67.96 64	84.91 62	90.88 45	75.59 39	86.57 16	78.16 26	94.71 34	83.82 134

SteuartSystems-ACMMP		83.07 25	83.64 26	81.35 30	85.14 72	71.00 58	85.53 29	84.78 49	70.91 48	85.64 48	90.41 62	75.55 41	87.69 5	79.75 11	95.08 23	85.36 88
Skip Steuart: Steuart Systems R&D Blog.
APDe-MVS		82.88 27	84.14 18	79.08 55	84.80 78	66.72 94	86.54 23	85.11 42	72.00 42	86.65 35	91.75 28	78.20 22	87.04 11	77.93 29	94.32 51	83.47 147
Zhaojie Zeng, Yuesong Wang, Tao Guan: Matching Ambiguity-Resilient Multi-View Stereo via Adaptive Patch Deformation. Pattern Recognition
GST-MVS		82.79 28	83.27 33	81.34 31	88.99 27	73.29 45	85.94 28	85.13 41	68.58 62	84.14 70	90.21 75	73.37 59	86.41 18	79.09 22	93.98 59	84.30 126

ACMP	69.50 8	82.64 29	83.38 30	80.40 41	86.50 46	69.44 71	82.30 58	86.08 24	66.80 69	86.70 34	89.99 78	81.64 6	85.95 35	74.35 54	96.11 4	85.81 78
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
MP-MVS-pluss		82.54 30	83.46 29	79.76 45	88.88 31	68.44 80	81.57 64	86.33 19	63.17 112	85.38 55	91.26 37	76.33 33	84.67 71	83.30 2	94.96 26	86.17 71
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
ACMMP_NAP		82.33 31	83.28 32	79.46 51	89.28 19	69.09 78	83.62 46	84.98 45	64.77 94	83.97 72	91.02 41	75.53 42	85.93 38	82.00 3	94.36 48	83.35 153

SMA-MVS		82.12 32	82.68 42	80.43 40	88.90 30	69.52 69	85.12 32	84.76 50	63.53 106	84.23 69	91.47 34	72.02 67	87.16 8	79.74 13	94.36 48	84.61 110
Yufeng Yin; Xiaoyan Liu; Zichao Zhang: SMA-MVS: Segmentation-Guided Multi-Scale Anchor Deformation Patch Multi-View Stereo. IEEE Transactions on Circuits and Systems for Video Technology
ACMM	69.25 9	82.11 33	83.31 31	78.49 66	88.17 37	73.96 38	83.11 53	84.52 60	66.40 73	87.45 26	89.16 96	81.02 8	80.52 142	74.27 55	95.73 8	80.98 210
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
DPE-MVS		82.00 34	83.02 37	78.95 60	85.36 69	67.25 89	82.91 54	84.98 45	73.52 28	85.43 54	90.03 77	76.37 32	86.97 13	74.56 51	94.02 58	82.62 178
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
SED-MVS		81.78 35	83.48 28	76.67 85	86.12 54	61.06 144	83.62 46	84.72 52	72.61 35	87.38 28	89.70 83	77.48 26	85.89 42	75.29 46	94.39 44	83.08 161

PMVS	70.70 6	81.70 36	83.15 35	77.36 79	90.35 6	82.82 3	82.15 59	79.22 158	74.08 24	87.16 32	91.97 21	84.80 2	76.97 202	64.98 127	93.61 63	72.28 322
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
UA-Net		81.56 37	82.28 44	79.40 52	88.91 29	69.16 76	84.67 36	80.01 145	75.34 19	79.80 119	94.91 2	69.79 88	80.25 146	72.63 67	94.46 39	88.78 42

CPTT-MVS		81.51 38	81.76 47	80.76 38	89.20 23	78.75 10	86.48 24	82.03 101	68.80 58	80.92 108	88.52 113	72.00 68	82.39 105	74.80 48	93.04 70	81.14 204

DVP-MVS++		81.24 39	82.74 41	76.76 84	83.14 99	60.90 148	91.64 1	85.49 32	74.03 25	84.93 59	90.38 67	66.82 115	85.90 40	77.43 34	90.78 115	83.49 144

ACMH+	66.64 10	81.20 40	82.48 43	77.35 80	81.16 131	62.39 129	80.51 72	87.80 8	73.02 30	87.57 24	91.08 40	80.28 9	82.44 104	64.82 129	96.10 5	87.21 58

DVP-MVS		81.15 41	83.12 36	75.24 107	86.16 52	60.78 150	83.77 44	80.58 134	72.48 37	85.83 46	90.41 62	78.57 19	85.69 47	75.86 42	94.39 44	79.24 243
Zhenlong Yuan, Jinguo Luo, Fei Shen, Zhaoxin Li, Cong Liu, Tianlu Mao, Zhaoqi Wang: DVP-MVS: Synergize Depth-Edge and Visibility Prior for Multi-View Stereo. AAAI2025
APD-MVS		81.13 42	81.73 48	79.36 53	84.47 83	70.53 63	83.85 42	83.70 75	69.43 57	83.67 75	88.96 103	75.89 37	86.41 18	72.62 68	92.95 71	81.14 204
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
3Dnovator+	73.19 2	81.08 43	80.48 55	82.87 8	81.41 127	72.03 49	84.38 38	86.23 23	77.28 18	80.65 112	90.18 76	59.80 190	87.58 6	73.06 63	91.34 95	89.01 34

DeepC-MVS	72.44 4	81.00 44	80.83 54	81.50 26	86.70 45	70.03 68	82.06 60	87.00 15	59.89 137	80.91 109	90.53 56	72.19 64	88.56 2	73.67 60	94.52 38	85.92 77
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
OPM-MVS		80.99 45	81.63 50	79.07 56	86.86 44	69.39 72	79.41 88	84.00 73	65.64 77	85.54 52	89.28 89	76.32 34	83.47 88	74.03 57	93.57 65	84.35 123
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
LS3D		80.99 45	80.85 53	81.41 29	78.37 164	71.37 54	87.45 8	85.87 27	77.48 16	81.98 92	89.95 80	69.14 91	85.26 57	66.15 117	91.24 97	87.61 53

SF-MVS		80.72 47	81.80 46	77.48 77	82.03 119	64.40 115	83.41 50	88.46 6	65.28 85	84.29 68	89.18 94	73.73 58	83.22 92	76.01 41	93.77 61	84.81 104

XVG-ACMP-BASELINE		80.54 48	81.06 52	78.98 59	87.01 39	72.91 47	80.23 80	85.56 31	66.56 72	85.64 48	89.57 85	69.12 92	80.55 141	72.51 69	93.37 66	83.48 146

MSP-MVS		80.49 49	79.67 62	82.96 6	89.70 12	77.46 23	87.16 12	85.10 43	64.94 93	81.05 106	88.38 117	57.10 219	87.10 9	79.75 11	83.87 236	84.31 124
Zhenlong Yuan, Cong Liu, Fei Shen, Zhaoxin Li, Jingguo luo, Tianlu Mao and Zhaoqi Wang: MSP-MVS: Multi-granularity Segmentation Prior Guided Multi-View Stereo. AAAI2025
PEN-MVS		80.46 50	82.91 38	73.11 137	89.83 9	39.02 337	77.06 117	82.61 93	80.04 5	90.60 7	92.85 10	74.93 47	85.21 60	63.15 149	95.15 21	95.09 2

PS-CasMVS		80.41 51	82.86 40	73.07 138	89.93 7	39.21 334	77.15 115	81.28 115	79.74 6	90.87 5	92.73 12	75.03 46	84.93 65	63.83 141	95.19 19	95.07 3

DTE-MVSNet		80.35 52	82.89 39	72.74 153	89.84 8	37.34 354	77.16 114	81.81 105	80.45 4	90.92 4	92.95 8	74.57 50	86.12 31	63.65 142	94.68 35	94.76 6

SD-MVS		80.28 53	81.55 51	76.47 90	83.57 93	67.83 84	83.39 51	85.35 39	64.42 96	86.14 42	87.07 136	74.02 54	80.97 133	77.70 32	92.32 82	80.62 222
Zhenlong Yuan, Jiakai Cao, Zhaoxin Li, Hao Jiang and Zhaoqi Wang: SD-MVS: Segmentation-driven Deformation Multi-View Stereo with Spherical Refinement and EM optimization. AAAI2024
WR-MVS_H		80.22 54	82.17 45	74.39 115	89.46 15	42.69 307	78.24 101	82.24 97	78.21 13	89.57 10	92.10 19	68.05 101	85.59 50	66.04 120	95.62 10	94.88 5

HPM-MVS++		79.89 55	79.80 61	80.18 43	89.02 26	78.44 11	83.49 49	80.18 142	64.71 95	78.11 140	88.39 116	65.46 133	83.14 93	77.64 33	91.20 98	78.94 247

XVG-OURS-SEG-HR		79.62 56	79.99 59	78.49 66	86.46 47	74.79 33	77.15 115	85.39 37	66.73 70	80.39 115	88.85 105	74.43 53	78.33 183	74.73 50	85.79 206	82.35 183

XVG-OURS		79.51 57	79.82 60	78.58 65	86.11 57	74.96 32	76.33 127	84.95 47	66.89 67	82.75 86	88.99 102	66.82 115	78.37 181	74.80 48	90.76 118	82.40 182

CP-MVSNet		79.48 58	81.65 49	72.98 141	89.66 13	39.06 336	76.76 118	80.46 136	78.91 9	90.32 8	91.70 29	68.49 96	84.89 66	63.40 146	95.12 22	95.01 4

OMC-MVS		79.41 59	78.79 67	81.28 33	80.62 135	70.71 62	80.91 69	84.76 50	62.54 117	81.77 95	86.65 152	71.46 71	83.53 86	67.95 100	92.44 78	89.60 24

v7n		79.37 60	80.41 56	76.28 92	78.67 163	55.81 189	79.22 90	82.51 95	70.72 49	87.54 25	92.44 15	68.00 103	81.34 121	72.84 65	91.72 86	91.69 11

TSAR-MVS + MP.		79.05 61	78.81 66	79.74 46	88.94 28	67.52 87	86.61 22	81.38 113	51.71 234	77.15 151	91.42 36	65.49 132	87.20 7	79.44 17	87.17 189	84.51 118
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
mvs_tets		78.93 62	78.67 69	79.72 47	84.81 77	73.93 39	80.65 71	76.50 200	51.98 232	87.40 27	91.86 26	76.09 36	78.53 173	68.58 91	90.20 124	86.69 66

test_djsdf		78.88 63	78.27 73	80.70 39	81.42 126	71.24 56	83.98 40	75.72 207	52.27 227	87.37 30	92.25 17	68.04 102	80.56 139	72.28 72	91.15 100	90.32 21

HQP_MVS		78.77 64	78.78 68	78.72 62	85.18 70	65.18 108	82.74 55	85.49 32	65.45 80	78.23 137	89.11 97	60.83 179	86.15 29	71.09 75	90.94 107	84.82 102

anonymousdsp		78.60 65	77.80 77	81.00 35	78.01 170	74.34 37	80.09 81	76.12 202	50.51 252	89.19 11	90.88 45	71.45 72	77.78 195	73.38 61	90.60 120	90.90 17

OurMVSNet-221017-0		78.57 66	78.53 71	78.67 63	80.48 136	64.16 116	80.24 79	82.06 100	61.89 121	88.77 16	93.32 5	57.15 217	82.60 103	70.08 83	92.80 73	89.25 28

jajsoiax		78.51 67	78.16 75	79.59 49	84.65 80	73.83 41	80.42 74	76.12 202	51.33 243	87.19 31	91.51 33	73.79 57	78.44 177	68.27 94	90.13 128	86.49 69

CNVR-MVS		78.49 68	78.59 70	78.16 70	85.86 63	67.40 88	78.12 104	81.50 109	63.92 100	77.51 148	86.56 156	68.43 98	84.82 68	73.83 58	91.61 90	82.26 187

DeepPCF-MVS	71.07 5	78.48 69	77.14 84	82.52 17	84.39 86	77.04 25	76.35 125	84.05 71	56.66 171	80.27 116	85.31 182	68.56 95	87.03 12	67.39 107	91.26 96	83.50 143

DP-MVS		78.44 70	79.29 64	75.90 97	81.86 122	65.33 106	79.05 91	84.63 58	74.83 22	80.41 114	86.27 163	71.68 69	83.45 89	62.45 153	92.40 79	78.92 248

NCCC		78.25 71	78.04 76	78.89 61	85.61 65	69.45 70	79.80 85	80.99 124	65.77 76	75.55 185	86.25 165	67.42 108	85.42 52	70.10 82	90.88 113	81.81 195

test_0402		78.17 72	79.48 63	74.24 117	83.50 94	59.15 164	72.52 172	74.60 217	75.34 19	88.69 17	91.81 27	75.06 45	82.37 106	65.10 125	88.68 158	81.20 202

MM		78.15 73	77.68 78	79.55 50	80.10 139	65.47 104	80.94 68	78.74 168	71.22 45	72.40 238	88.70 107	60.51 181	87.70 4	77.40 36	89.13 152	85.48 87

AllTest		77.66 74	77.43 80	78.35 68	79.19 152	70.81 59	78.60 95	88.64 4	65.37 83	80.09 117	88.17 121	70.33 81	78.43 178	55.60 213	90.90 111	85.81 78

PS-MVSNAJss		77.54 75	77.35 82	78.13 72	84.88 75	66.37 96	78.55 96	79.59 152	53.48 218	86.29 39	92.43 16	62.39 158	80.25 146	67.90 101	90.61 119	87.77 50

ACMH	63.62 14	77.50 76	80.11 58	69.68 200	79.61 143	56.28 184	78.81 93	83.62 76	63.41 110	87.14 33	90.23 74	76.11 35	73.32 244	67.58 102	94.44 42	79.44 241
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
CDPH-MVS		77.33 77	77.06 85	78.14 71	84.21 87	63.98 119	76.07 131	83.45 78	54.20 206	77.68 147	87.18 132	69.98 85	85.37 53	68.01 98	92.72 76	85.08 94

DeepC-MVS_fast	69.89 7	77.17 78	76.33 90	79.70 48	83.90 91	67.94 82	80.06 83	83.75 74	56.73 170	74.88 196	85.32 181	65.54 131	87.79 3	65.61 124	91.14 101	83.35 153
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
EC-MVSNet		77.08 79	77.39 81	76.14 95	76.86 191	56.87 182	80.32 78	87.52 12	63.45 108	74.66 201	84.52 194	69.87 87	84.94 64	69.76 85	89.59 139	86.60 67

MVSMamba_PlusPlus		76.88 80	78.21 74	72.88 148	80.83 132	48.71 243	83.28 52	82.79 87	72.78 31	79.17 126	91.94 22	56.47 226	83.95 78	70.51 81	86.15 201	85.99 75

X-MVStestdata		76.81 81	74.79 103	82.85 9	89.43 16	77.61 16	86.80 20	84.66 56	72.71 32	82.87 83	9.95 428	73.86 55	86.31 21	78.84 23	94.03 56	84.64 107

UniMVSNet_ETH3D		76.74 82	79.02 65	69.92 198	89.27 20	43.81 294	74.47 154	71.70 239	72.33 40	85.50 53	93.65 4	77.98 23	76.88 205	54.60 225	91.64 88	89.08 32

CS-MVS		76.51 83	76.00 93	78.06 73	77.02 183	64.77 112	80.78 70	82.66 92	60.39 133	74.15 211	83.30 217	69.65 89	82.07 112	69.27 88	86.75 196	87.36 56

train_agg		76.38 84	76.55 88	75.86 98	85.47 67	69.32 74	76.42 123	78.69 169	54.00 211	76.97 153	86.74 146	66.60 120	81.10 127	72.50 70	91.56 91	77.15 272

TranMVSNet+NR-MVSNet		76.13 85	77.66 79	71.56 171	84.61 81	42.57 309	70.98 202	78.29 178	68.67 61	83.04 79	89.26 90	72.99 61	80.75 138	55.58 216	95.47 11	91.35 12

tt0805		76.12 86	78.43 72	69.20 209	81.32 128	41.37 315	76.72 119	77.64 187	63.78 103	82.06 91	87.88 126	79.78 11	79.05 163	64.33 133	92.40 79	87.17 61

SixPastTwentyTwo		75.77 87	76.34 89	74.06 120	81.69 124	54.84 196	76.47 120	75.49 209	64.10 99	87.73 21	92.24 18	50.45 260	81.30 123	67.41 105	91.46 93	86.04 74

RPSCF		75.76 88	74.37 109	79.93 44	74.81 220	77.53 18	77.53 109	79.30 157	59.44 140	78.88 129	89.80 82	71.26 74	73.09 246	57.45 195	80.89 270	89.17 31

v10		75.69 89	76.20 91	74.16 118	74.44 229	48.69 244	75.84 135	82.93 86	59.02 145	85.92 44	89.17 95	58.56 200	82.74 101	70.73 77	89.14 151	91.05 14

testf1		75.66 90	76.57 86	72.95 142	67.07 334	67.62 85	76.10 129	80.68 129	64.95 91	86.58 36	90.94 43	71.20 75	71.68 268	60.46 168	91.13 102	79.56 237

APD_test2		75.66 90	76.57 86	72.95 142	67.07 334	67.62 85	76.10 129	80.68 129	64.95 91	86.58 36	90.94 43	71.20 75	71.68 268	60.46 168	91.13 102	79.56 237

Anonymous20231211		75.54 92	77.19 83	70.59 182	77.67 176	45.70 282	74.73 148	80.19 141	68.80 58	82.95 82	92.91 9	66.26 124	76.76 207	58.41 190	92.77 74	89.30 27

MVS_0304		75.45 93	74.66 105	77.83 74	75.58 210	61.53 137	78.29 99	77.18 194	63.15 114	69.97 272	87.20 131	57.54 215	87.05 10	74.05 56	88.96 155	84.89 97

Effi-MVS+-dtu		75.43 94	72.28 152	84.91 3	77.05 181	83.58 2	78.47 97	77.70 186	57.68 156	74.89 195	78.13 297	64.80 140	84.26 77	56.46 205	85.32 214	86.88 63

F-COLMAP		75.29 95	73.99 117	79.18 54	81.73 123	71.90 50	81.86 63	82.98 84	59.86 138	72.27 239	84.00 202	64.56 142	83.07 96	51.48 247	87.19 188	82.56 180

casdiffmvs_mvg		75.26 96	76.18 92	72.52 158	72.87 259	49.47 238	72.94 170	84.71 54	59.49 139	80.90 110	88.81 106	70.07 84	79.71 154	67.40 106	88.39 161	88.40 46
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
HQP-MVS		75.24 97	75.01 102	75.94 96	82.37 113	58.80 169	77.32 111	84.12 69	59.08 141	71.58 248	85.96 175	58.09 206	85.30 55	67.38 109	89.16 148	83.73 139

TAPA-MVS	65.27 12	75.16 98	74.29 111	77.77 75	74.86 219	68.08 81	77.89 105	84.04 72	55.15 186	76.19 180	83.39 211	66.91 113	80.11 150	60.04 176	90.14 127	85.13 92
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
IS-MVSNet		75.10 99	75.42 100	74.15 119	79.23 150	48.05 253	79.43 86	78.04 182	70.09 54	79.17 126	88.02 125	53.04 245	83.60 83	58.05 192	93.76 62	90.79 18

v8		75.07 100	75.64 97	73.35 131	73.42 244	47.46 264	75.20 138	81.45 111	60.05 135	85.64 48	89.26 90	58.08 208	81.80 116	69.71 87	87.97 169	90.79 18

APD_test1		75.04 101	75.38 101	74.02 121	69.89 296	70.15 66	76.46 121	79.71 148	65.50 79	82.99 81	88.60 112	66.94 112	72.35 257	59.77 179	88.54 159	79.56 237

UniMVSNet (Re)		75.00 102	75.48 99	73.56 129	83.14 99	47.92 255	70.41 211	81.04 123	63.67 104	79.54 121	86.37 161	62.83 152	81.82 115	57.10 199	95.25 15	90.94 16

PHI-MVS		74.92 103	74.36 110	76.61 86	76.40 196	62.32 130	80.38 75	83.15 82	54.16 208	73.23 228	80.75 251	62.19 161	83.86 80	68.02 97	90.92 110	83.65 140

DU-MVS		74.91 104	75.57 98	72.93 145	83.50 94	45.79 279	69.47 221	80.14 143	65.22 86	81.74 97	87.08 134	61.82 164	81.07 129	56.21 207	94.98 24	91.93 9

UniMVSNet_NR-MVSNet		74.90 105	75.65 96	72.64 156	83.04 104	45.79 279	69.26 225	78.81 164	66.66 71	81.74 97	86.88 141	63.26 148	81.07 129	56.21 207	94.98 24	91.05 14

SPE-MVS-test		74.89 106	74.23 112	76.86 83	77.01 184	62.94 127	78.98 92	84.61 59	58.62 148	70.17 269	80.80 250	66.74 119	81.96 113	61.74 156	89.40 146	85.69 84

nrg030		74.87 107	75.99 94	71.52 172	74.90 218	49.88 237	74.10 160	82.58 94	54.55 198	83.50 77	89.21 92	71.51 70	75.74 215	61.24 160	92.34 81	88.94 37

Vis-MVSNet		74.85 108	74.56 106	75.72 99	81.63 125	64.64 113	76.35 125	79.06 160	62.85 115	73.33 226	88.41 115	62.54 156	79.59 157	63.94 140	82.92 247	82.94 165
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
MSLP-MVS++		74.48 109	75.78 95	70.59 182	84.66 79	62.40 128	78.65 94	84.24 66	60.55 132	77.71 146	81.98 235	63.12 149	77.64 197	62.95 150	88.14 164	71.73 327

AdaColmap		74.22 110	74.56 106	73.20 134	81.95 120	60.97 146	79.43 86	80.90 125	65.57 78	72.54 236	81.76 239	70.98 78	85.26 57	47.88 284	90.00 129	73.37 306

CSCG		74.12 111	74.39 108	73.33 132	79.35 147	61.66 136	77.45 110	81.98 102	62.47 119	79.06 128	80.19 261	61.83 163	78.79 169	59.83 178	87.35 179	79.54 240

test_fmvsmconf0.01_n		73.91 112	73.64 124	74.71 108	69.79 300	66.25 97	75.90 133	79.90 146	46.03 296	76.48 174	85.02 185	67.96 105	73.97 239	74.47 53	87.22 186	83.90 133

PAPM_NR		73.91 112	74.16 113	73.16 135	81.90 121	53.50 207	81.28 66	81.40 112	66.17 74	73.30 227	83.31 216	59.96 186	83.10 95	58.45 189	81.66 264	82.87 168

EPP-MVSNet		73.86 114	73.38 128	75.31 105	78.19 166	53.35 209	80.45 73	77.32 191	65.11 89	76.47 175	86.80 142	49.47 265	83.77 81	53.89 234	92.72 76	88.81 41

K. test v3		73.67 115	73.61 125	73.87 123	79.78 141	55.62 193	74.69 150	62.04 321	66.16 75	84.76 63	93.23 6	49.47 265	80.97 133	65.66 123	86.67 197	85.02 96

NR-MVSNet		73.62 116	74.05 116	72.33 163	83.50 94	43.71 295	65.65 279	77.32 191	64.32 97	75.59 184	87.08 134	62.45 157	81.34 121	54.90 220	95.63 9	91.93 9

balanced_conf03		73.59 117	74.06 115	72.17 166	77.48 179	47.72 260	81.43 65	82.20 98	54.38 199	79.19 125	87.68 128	54.41 237	83.57 84	63.98 137	85.78 207	85.22 89

DP-MVS Recon		73.57 118	72.69 144	76.23 93	82.85 108	63.39 122	74.32 155	82.96 85	57.75 155	70.35 265	81.98 235	64.34 144	84.41 76	49.69 262	89.95 131	80.89 212

CNLPA		73.44 119	73.03 139	74.66 109	78.27 165	75.29 30	75.99 132	78.49 173	65.39 82	75.67 183	83.22 222	61.23 172	66.77 317	53.70 236	85.33 213	81.92 193

MCST-MVS		73.42 120	73.34 131	73.63 127	81.28 129	59.17 163	74.80 146	83.13 83	45.50 300	72.84 231	83.78 207	65.15 137	80.99 131	64.54 130	89.09 154	80.73 218

v1192		73.40 121	73.42 126	73.32 133	74.65 226	48.67 245	72.21 176	81.73 106	52.76 223	81.85 93	84.56 192	57.12 218	82.24 110	68.58 91	87.33 181	89.06 33

114514_t		73.40 121	73.33 132	73.64 126	84.15 89	57.11 180	78.20 102	80.02 144	43.76 317	72.55 235	86.07 173	64.00 145	83.35 91	60.14 174	91.03 106	80.45 225

FC-MVSNet-test		73.32 123	74.78 104	68.93 219	79.21 151	36.57 356	71.82 189	79.54 154	57.63 160	82.57 88	90.38 67	59.38 193	78.99 165	57.91 193	94.56 37	91.23 13

v1144		73.29 124	73.39 127	73.01 139	74.12 235	48.11 251	72.01 181	81.08 122	53.83 215	81.77 95	84.68 187	58.07 209	81.91 114	68.10 95	86.86 192	88.99 36

test_fmvsmconf0.1_n		73.26 125	72.82 143	74.56 110	69.10 307	66.18 99	74.65 152	79.34 156	45.58 299	75.54 186	83.91 203	67.19 110	73.88 242	73.26 62	86.86 192	83.63 141

GeoE		73.14 126	73.77 122	71.26 176	78.09 168	52.64 212	74.32 155	79.56 153	56.32 174	76.35 178	83.36 215	70.76 79	77.96 191	63.32 147	81.84 258	83.18 158

baseline		73.10 127	73.96 118	70.51 184	71.46 271	46.39 276	72.08 178	84.40 62	55.95 178	76.62 166	86.46 159	67.20 109	78.03 190	64.22 134	87.27 185	87.11 62

h-mvs33		73.08 128	71.61 162	77.48 77	83.89 92	72.89 48	70.47 209	71.12 256	54.28 202	77.89 141	83.41 210	49.04 269	80.98 132	63.62 143	90.77 117	78.58 251

TSAR-MVS + GP.		73.08 128	71.60 163	77.54 76	78.99 159	70.73 61	74.96 141	69.38 271	60.73 131	74.39 207	78.44 291	57.72 213	82.78 100	60.16 172	89.60 138	79.11 245

v1240		73.06 130	73.14 134	72.84 150	74.74 222	47.27 268	71.88 188	81.11 119	51.80 233	82.28 90	84.21 198	56.22 228	82.34 107	68.82 90	87.17 189	88.91 38

casdiffmvs		73.06 130	73.84 119	70.72 180	71.32 273	46.71 272	70.93 203	84.26 65	55.62 181	77.46 149	87.10 133	67.09 111	77.81 193	63.95 138	86.83 194	87.64 52
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
IterMVS-LS		73.01 132	73.12 136	72.66 155	73.79 240	49.90 233	71.63 191	78.44 174	58.22 150	80.51 113	86.63 153	58.15 204	79.62 155	62.51 151	88.20 163	88.48 44
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CANet		73.00 133	71.84 156	76.48 89	75.82 207	61.28 140	74.81 144	80.37 139	63.17 112	62.43 344	80.50 255	61.10 176	85.16 63	64.00 136	84.34 232	83.01 164

v144192		72.99 134	73.06 138	72.77 151	74.58 227	47.48 263	71.90 187	80.44 137	51.57 236	81.46 101	84.11 201	58.04 210	82.12 111	67.98 99	87.47 176	88.70 43

MVS_111021_HR		72.98 135	72.97 141	72.99 140	80.82 133	65.47 104	68.81 232	72.77 231	57.67 157	75.76 182	82.38 230	71.01 77	77.17 200	61.38 159	86.15 201	76.32 280

fmvsm_s_conf0.5_n_3		72.97 136	74.13 114	69.47 203	71.40 272	58.36 173	73.07 168	80.64 131	56.86 166	75.49 188	84.67 188	67.86 106	72.33 258	75.68 44	81.54 266	77.73 265

v1921920		72.96 137	72.98 140	72.89 147	74.67 223	47.58 262	71.92 186	80.69 128	51.70 235	81.69 99	83.89 204	56.58 224	82.25 109	68.34 93	87.36 178	88.82 40

test_fmvsmconf_n		72.91 138	72.40 150	74.46 111	68.62 311	66.12 100	74.21 159	78.80 166	45.64 298	74.62 202	83.25 219	66.80 118	73.86 243	72.97 64	86.66 198	83.39 150

CLD-MVS		72.88 139	72.36 151	74.43 114	77.03 182	54.30 200	68.77 235	83.43 79	52.12 229	76.79 162	74.44 328	69.54 90	83.91 79	55.88 210	93.25 69	85.09 93
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
EI-MVSNet-Vis-set		72.78 140	71.87 155	75.54 103	74.77 221	59.02 167	72.24 175	71.56 242	63.92 100	78.59 132	71.59 350	66.22 125	78.60 172	67.58 102	80.32 281	89.00 35

ETV-MVS		72.72 141	72.16 154	74.38 116	76.90 189	55.95 186	73.34 166	84.67 55	62.04 120	72.19 242	70.81 355	65.90 128	85.24 59	58.64 187	84.96 221	81.95 192

PCF-MVS	63.80 13	72.70 142	71.69 158	75.72 99	78.10 167	60.01 157	73.04 169	81.50 109	45.34 305	79.66 120	84.35 197	65.15 137	82.65 102	48.70 273	89.38 147	84.50 119
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
EI-MVSNet-UG-set		72.63 143	71.68 159	75.47 104	74.67 223	58.64 172	72.02 180	71.50 243	63.53 106	78.58 134	71.39 354	65.98 126	78.53 173	67.30 112	80.18 284	89.23 29

Anonymous20240529		72.56 144	73.79 121	68.86 221	76.89 190	45.21 285	68.80 234	77.25 193	67.16 66	76.89 157	90.44 59	65.95 127	74.19 237	50.75 254	90.00 129	87.18 60

FIs		72.56 144	73.80 120	68.84 222	78.74 162	37.74 350	71.02 201	79.83 147	56.12 175	80.88 111	89.45 87	58.18 202	78.28 184	56.63 201	93.36 67	90.51 20

v2v482		72.55 146	72.58 146	72.43 160	72.92 258	46.72 271	71.41 194	79.13 159	55.27 184	81.17 105	85.25 183	55.41 232	81.13 126	67.25 113	85.46 209	89.43 26

test_fmvsmvis_n_1920		72.36 147	72.49 147	71.96 167	71.29 274	64.06 118	72.79 171	81.82 104	40.23 348	81.25 104	81.04 247	70.62 80	68.69 293	69.74 86	83.60 242	83.14 159

hse-mvs2		72.32 148	70.66 175	77.31 81	83.10 103	71.77 51	69.19 227	71.45 245	54.28 202	77.89 141	78.26 293	49.04 269	79.23 160	63.62 143	89.13 152	80.92 211

sasdasda		72.29 149	73.38 128	69.04 213	74.23 230	47.37 265	73.93 162	83.18 80	54.36 200	76.61 167	81.64 241	72.03 65	75.34 219	57.12 197	87.28 183	84.40 120

canonicalmvs		72.29 149	73.38 128	69.04 213	74.23 230	47.37 265	73.93 162	83.18 80	54.36 200	76.61 167	81.64 241	72.03 65	75.34 219	57.12 197	87.28 183	84.40 120

Effi-MVS+		72.10 151	72.28 152	71.58 170	74.21 233	50.33 226	74.72 149	82.73 90	62.62 116	70.77 261	76.83 308	69.96 86	80.97 133	60.20 170	78.43 305	83.45 149

MVS_111021_LR		72.10 151	71.82 157	72.95 142	79.53 145	73.90 40	70.45 210	66.64 286	56.87 165	76.81 161	81.76 239	68.78 93	71.76 266	61.81 154	83.74 238	73.18 308

fmvsm_l_conf0.5_n_3		71.98 153	71.68 159	72.88 148	72.84 260	64.15 117	73.48 164	77.11 195	48.97 272	71.31 256	84.18 199	67.98 104	71.60 270	68.86 89	80.43 280	82.89 166

pmmvs6		71.82 154	73.66 123	66.31 252	75.94 205	42.01 311	66.99 261	72.53 234	63.45 108	76.43 176	92.78 11	72.95 62	69.69 285	51.41 249	90.46 121	87.22 57

PLC	62.01 16	71.79 155	70.28 178	76.33 91	80.31 138	68.63 79	78.18 103	81.24 116	54.57 197	67.09 309	80.63 253	59.44 191	81.74 118	46.91 291	84.17 233	78.63 249
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
MGCFI-Net		71.70 156	73.10 137	67.49 238	73.23 248	43.08 303	72.06 179	82.43 96	54.58 196	75.97 181	82.00 233	72.42 63	75.22 221	57.84 194	87.34 180	84.18 127

BP-MVS1		71.60 157	70.06 179	76.20 94	74.07 236	55.22 194	74.29 157	73.44 224	57.29 162	73.87 219	84.65 189	32.57 359	83.49 87	72.43 71	87.94 170	89.89 23

VDDNet		71.60 157	73.13 135	67.02 245	86.29 48	41.11 317	69.97 215	66.50 287	68.72 60	74.74 197	91.70 29	59.90 187	75.81 213	48.58 275	91.72 86	84.15 129

3Dnovator	65.95 11	71.50 159	71.22 168	72.34 162	73.16 249	63.09 125	78.37 98	78.32 176	57.67 157	72.22 241	84.61 191	54.77 233	78.47 175	60.82 166	81.07 269	75.45 286

FA-MVS(test-final)		71.27 160	71.06 169	71.92 168	73.96 237	52.32 214	76.45 122	76.12 202	59.07 144	74.04 216	86.18 166	52.18 249	79.43 159	59.75 180	81.76 259	84.03 130

WR-MVS		71.20 161	72.48 148	67.36 240	84.98 74	35.70 364	64.43 296	68.66 277	65.05 90	81.49 100	86.43 160	57.57 214	76.48 209	50.36 258	93.32 68	89.90 22

V42		71.06 162	70.83 172	71.72 169	67.25 330	47.14 269	65.94 273	80.35 140	51.35 242	83.40 78	83.23 220	59.25 194	78.80 168	65.91 121	80.81 273	89.23 29

FMVSNet1		71.06 162	72.48 148	66.81 246	77.65 177	40.68 324	71.96 183	73.03 226	61.14 125	79.45 123	90.36 70	60.44 182	75.20 223	50.20 259	88.05 166	84.54 114

dcpmvs_2		71.02 164	72.65 145	66.16 253	76.06 204	50.49 224	71.97 182	79.36 155	50.34 253	82.81 85	83.63 208	64.38 143	67.27 308	61.54 158	83.71 240	80.71 220

API-MVS		70.97 165	71.51 165	69.37 204	75.20 213	55.94 187	80.99 67	76.84 197	62.48 118	71.24 257	77.51 303	61.51 168	80.96 136	52.04 243	85.76 208	71.22 333

GDP-MVS		70.84 166	69.24 187	75.62 101	76.44 195	55.65 191	74.62 153	82.78 89	49.63 262	72.10 243	83.79 206	31.86 367	82.84 99	64.93 128	87.01 191	88.39 47

VDD-MVS		70.81 167	71.44 166	68.91 220	79.07 157	46.51 273	67.82 248	70.83 260	61.23 124	74.07 214	88.69 108	59.86 188	75.62 216	51.11 251	90.28 123	84.61 110

EG-PatchMatch MVS		70.70 168	70.88 171	70.16 192	82.64 112	58.80 169	71.48 192	73.64 222	54.98 187	76.55 170	81.77 238	61.10 176	78.94 166	54.87 221	80.84 272	72.74 316

Baseline_NR-MVSNet		70.62 169	73.19 133	62.92 284	76.97 185	34.44 372	68.84 230	70.88 259	60.25 134	79.50 122	90.53 56	61.82 164	69.11 290	54.67 224	95.27 14	85.22 89

alignmvs		70.54 170	71.00 170	69.15 211	73.50 242	48.04 254	69.85 218	79.62 149	53.94 214	76.54 171	82.00 233	59.00 196	74.68 230	57.32 196	87.21 187	84.72 105

MG-MVS		70.47 171	71.34 167	67.85 234	79.26 149	40.42 328	74.67 151	75.15 213	58.41 149	68.74 293	88.14 124	56.08 229	83.69 82	59.90 177	81.71 263	79.43 242

RRT-MVS		70.33 172	70.73 173	69.14 212	71.93 267	45.24 284	75.10 139	75.08 214	60.85 130	78.62 131	87.36 130	49.54 264	78.64 171	60.16 172	77.90 313	83.55 142

AUN-MVS		70.22 173	67.88 213	77.22 82	82.96 107	71.61 52	69.08 228	71.39 246	49.17 268	71.70 246	78.07 298	37.62 338	79.21 161	61.81 154	89.15 150	80.82 214

UGNet		70.20 174	69.05 190	73.65 125	76.24 198	63.64 120	75.87 134	72.53 234	61.48 123	60.93 354	86.14 169	52.37 248	77.12 201	50.67 255	85.21 215	80.17 231
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
PVSNet_Blended_VisFu		70.04 175	68.88 193	73.53 130	82.71 110	63.62 121	74.81 144	81.95 103	48.53 275	67.16 308	79.18 282	51.42 255	78.38 180	54.39 229	79.72 293	78.60 250

Fast-Effi-MVS+-dtu		70.00 176	68.74 197	73.77 124	73.47 243	64.53 114	71.36 195	78.14 181	55.81 180	68.84 291	74.71 325	65.36 134	75.75 214	52.00 244	79.00 298	81.03 207

DPM-MVS		69.98 177	69.22 189	72.26 164	82.69 111	58.82 168	70.53 208	81.23 117	47.79 284	64.16 326	80.21 259	51.32 256	83.12 94	60.14 174	84.95 222	74.83 292

MVSFormer		69.93 178	69.03 191	72.63 157	74.93 216	59.19 161	83.98 40	75.72 207	52.27 227	63.53 338	76.74 309	43.19 301	80.56 139	72.28 72	78.67 302	78.14 258

MVS_Test		69.84 179	70.71 174	67.24 241	67.49 328	43.25 302	69.87 217	81.22 118	52.69 224	71.57 251	86.68 149	62.09 162	74.51 232	66.05 119	78.74 300	83.96 131

c3_l		69.82 180	69.89 181	69.61 201	66.24 341	43.48 298	68.12 245	79.61 151	51.43 238	77.72 145	80.18 262	54.61 236	78.15 189	63.62 143	87.50 175	87.20 59

test_fmvsm_n_1920		69.63 181	68.45 200	73.16 135	70.56 283	65.86 102	70.26 212	78.35 175	37.69 365	74.29 209	78.89 287	61.10 176	68.10 299	65.87 122	79.07 297	85.53 86

TransMVSNet (Re)		69.62 182	71.63 161	63.57 273	76.51 194	35.93 362	65.75 278	71.29 250	61.05 126	75.02 193	89.90 81	65.88 129	70.41 281	49.79 261	89.48 142	84.38 122

EI-MVSNet		69.61 183	69.01 192	71.41 174	73.94 238	49.90 233	71.31 197	71.32 248	58.22 150	75.40 190	70.44 357	58.16 203	75.85 211	62.51 151	79.81 290	88.48 44

Gipuma		69.55 184	72.83 142	59.70 312	63.63 362	53.97 203	80.08 82	75.93 205	64.24 98	73.49 223	88.93 104	57.89 212	62.46 338	59.75 180	91.55 92	62.67 390
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
tttt0517		69.46 185	67.79 215	74.46 111	75.34 211	52.72 211	75.05 140	63.27 314	54.69 193	78.87 130	84.37 196	26.63 394	81.15 125	63.95 138	87.93 171	89.51 25

eth_miper_zixun_eth		69.42 186	68.73 198	71.50 173	67.99 320	46.42 274	67.58 250	78.81 164	50.72 250	78.13 139	80.34 258	50.15 262	80.34 144	60.18 171	84.65 225	87.74 51

BH-untuned		69.39 187	69.46 183	69.18 210	77.96 171	56.88 181	68.47 242	77.53 188	56.77 168	77.79 144	79.63 272	60.30 184	80.20 149	46.04 299	80.65 276	70.47 340

v148		69.38 188	69.39 184	69.36 205	69.14 306	44.56 289	68.83 231	72.70 232	54.79 191	78.59 132	84.12 200	54.69 234	76.74 208	59.40 183	82.20 252	86.79 64

PAPR		69.20 189	68.66 199	70.82 179	75.15 215	47.77 258	75.31 137	81.11 119	49.62 264	66.33 311	79.27 279	61.53 167	82.96 97	48.12 281	81.50 267	81.74 198

QAPM		69.18 190	69.26 186	68.94 218	71.61 269	52.58 213	80.37 76	78.79 167	49.63 262	73.51 222	85.14 184	53.66 241	79.12 162	55.11 218	75.54 329	75.11 291

fmvsm_s_conf0.1_n_2		69.14 191	68.42 201	71.28 175	68.30 316	57.60 178	65.06 287	69.91 266	48.24 276	74.56 204	82.84 223	55.55 231	69.73 283	70.66 79	80.69 275	86.52 68

LCM-MVSNet-Re		69.10 192	71.57 164	61.70 293	70.37 288	34.30 374	61.45 316	79.62 149	56.81 167	89.59 9	88.16 123	68.44 97	72.94 247	42.30 319	87.33 181	77.85 264

EPNet		69.10 192	67.32 220	74.46 111	68.33 315	61.27 141	77.56 107	63.57 311	60.95 128	56.62 378	82.75 224	51.53 254	81.24 124	54.36 230	90.20 124	80.88 213
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
fmvsm_s_conf0.5_n_2		68.93 194	68.23 206	71.02 178	67.78 324	57.58 179	64.74 290	69.56 270	48.16 278	74.38 208	82.32 231	56.00 230	69.68 286	70.65 80	80.52 279	85.80 82

mvsmamba		68.87 195	67.30 222	73.57 128	76.58 193	53.70 206	84.43 37	74.25 219	45.38 304	76.63 165	84.55 193	35.85 345	85.27 56	49.54 265	78.49 304	81.75 197

DELS-MVS		68.83 196	68.31 202	70.38 185	70.55 285	48.31 247	63.78 302	82.13 99	54.00 211	68.96 284	75.17 321	58.95 197	80.06 151	58.55 188	82.74 249	82.76 171
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
Fast-Effi-MVS+		68.81 197	68.30 203	70.35 187	74.66 225	48.61 246	66.06 272	78.32 176	50.62 251	71.48 254	75.54 316	68.75 94	79.59 157	50.55 257	78.73 301	82.86 169

mmtdpeth		68.76 198	70.55 176	63.40 277	67.06 336	56.26 185	68.73 237	71.22 254	55.47 183	70.09 270	88.64 111	65.29 136	56.89 362	58.94 186	89.50 141	77.04 277

OpenMVS	62.51 15	68.76 198	68.75 196	68.78 223	70.56 283	53.91 204	78.29 99	77.35 190	48.85 273	70.22 267	83.52 209	52.65 247	76.93 203	55.31 217	81.99 254	75.49 285

VPA-MVSNet		68.71 200	70.37 177	63.72 271	76.13 200	38.06 348	64.10 298	71.48 244	56.60 173	74.10 213	88.31 118	64.78 141	69.72 284	47.69 286	90.15 126	83.37 152

BH-RMVSNet		68.69 201	68.20 208	70.14 193	76.40 196	53.90 205	64.62 293	73.48 223	58.01 152	73.91 218	81.78 237	59.09 195	78.22 185	48.59 274	77.96 312	78.31 254

EIA-MVS		68.59 202	67.16 223	72.90 146	75.18 214	55.64 192	69.39 222	81.29 114	52.44 226	64.53 322	70.69 356	60.33 183	82.30 108	54.27 231	76.31 323	80.75 217

pm-mvs1		68.40 203	69.85 182	64.04 269	73.10 253	39.94 331	64.61 294	70.50 262	55.52 182	73.97 217	89.33 88	63.91 146	68.38 296	49.68 263	88.02 167	83.81 135

miper_ehance_all_eth		68.36 204	68.16 209	68.98 216	65.14 353	43.34 300	67.07 260	78.92 163	49.11 269	76.21 179	77.72 300	53.48 242	77.92 192	61.16 162	84.59 227	85.68 85

GBi-Net		68.30 205	68.79 194	66.81 246	73.14 250	40.68 324	71.96 183	73.03 226	54.81 188	74.72 198	90.36 70	48.63 275	75.20 223	47.12 288	85.37 210	84.54 114

test1		68.30 205	68.79 194	66.81 246	73.14 250	40.68 324	71.96 183	73.03 226	54.81 188	74.72 198	90.36 70	48.63 275	75.20 223	47.12 288	85.37 210	84.54 114

FE-MVS		68.29 207	66.96 227	72.26 164	74.16 234	54.24 201	77.55 108	73.42 225	57.65 159	72.66 233	84.91 186	32.02 366	81.49 120	48.43 277	81.85 257	81.04 206

DIV-MVS_self_test		68.27 208	68.26 204	68.29 229	64.98 354	43.67 296	65.89 274	74.67 215	50.04 259	76.86 159	82.43 228	48.74 273	75.38 217	60.94 164	89.81 134	85.81 78

cl____		68.26 209	68.26 204	68.29 229	64.98 354	43.67 296	65.89 274	74.67 215	50.04 259	76.86 159	82.42 229	48.74 273	75.38 217	60.92 165	89.81 134	85.80 82

TinyColmap		67.98 210	69.28 185	64.08 267	67.98 321	46.82 270	70.04 213	75.26 211	53.05 220	77.36 150	86.79 143	59.39 192	72.59 254	45.64 302	88.01 168	72.83 314

xiu_mvs_v1_base_debu		67.87 211	67.07 224	70.26 188	79.13 154	61.90 133	67.34 254	71.25 251	47.98 280	67.70 301	74.19 333	61.31 169	72.62 251	56.51 202	78.26 308	76.27 281

xiu_mvs_v1_base		67.87 211	67.07 224	70.26 188	79.13 154	61.90 133	67.34 254	71.25 251	47.98 280	67.70 301	74.19 333	61.31 169	72.62 251	56.51 202	78.26 308	76.27 281

xiu_mvs_v1_base_debi		67.87 211	67.07 224	70.26 188	79.13 154	61.90 133	67.34 254	71.25 251	47.98 280	67.70 301	74.19 333	61.31 169	72.62 251	56.51 202	78.26 308	76.27 281

MAR-MVS		67.72 214	66.16 233	72.40 161	74.45 228	64.99 111	74.87 142	77.50 189	48.67 274	65.78 315	68.58 382	57.01 221	77.79 194	46.68 294	81.92 255	74.42 299
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
IterMVS-SCA-FT		67.68 215	66.07 235	72.49 159	73.34 246	58.20 175	63.80 301	65.55 295	48.10 279	76.91 156	82.64 227	45.20 288	78.84 167	61.20 161	77.89 314	80.44 226

LF4IMVS		67.50 216	67.31 221	68.08 232	58.86 391	61.93 132	71.43 193	75.90 206	44.67 311	72.42 237	80.20 260	57.16 216	70.44 279	58.99 185	86.12 203	71.88 325

fmvsm_l_conf0.5_n		67.48 217	66.88 229	69.28 208	67.41 329	62.04 131	70.69 207	69.85 267	39.46 351	69.59 277	81.09 246	58.15 204	68.73 292	67.51 104	78.16 311	77.07 276

FMVSNet2		67.48 217	68.21 207	65.29 258	73.14 250	38.94 338	68.81 232	71.21 255	54.81 188	76.73 163	86.48 158	48.63 275	74.60 231	47.98 283	86.11 204	82.35 183

MSDG		67.47 219	67.48 219	67.46 239	70.70 279	54.69 198	66.90 264	78.17 179	60.88 129	70.41 264	74.76 323	61.22 174	73.18 245	47.38 287	76.87 319	74.49 297

diffmvs		67.42 220	67.50 218	67.20 242	62.26 368	45.21 285	64.87 289	77.04 196	48.21 277	71.74 245	79.70 270	58.40 201	71.17 273	64.99 126	80.27 282	85.22 89
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
fmvsm_s_conf0.1_n_a		67.37 221	66.36 231	70.37 186	70.86 276	61.17 142	74.00 161	57.18 340	40.77 343	68.83 292	80.88 249	63.11 150	67.61 304	66.94 114	74.72 336	82.33 186

cl22		67.14 222	66.51 230	69.03 215	63.20 363	43.46 299	66.88 265	76.25 201	49.22 267	74.48 205	77.88 299	45.49 287	77.40 199	60.64 167	84.59 227	86.24 70

ANet_high		67.08 223	69.94 180	58.51 322	57.55 397	27.09 405	58.43 342	76.80 198	63.56 105	82.40 89	91.93 23	59.82 189	64.98 329	50.10 260	88.86 157	83.46 148

LFMVS		67.06 224	67.89 212	64.56 263	78.02 169	38.25 345	70.81 206	59.60 328	65.18 87	71.06 259	86.56 156	43.85 297	75.22 221	46.35 296	89.63 137	80.21 230

thisisatest0530		67.05 225	65.16 245	72.73 154	73.10 253	50.55 223	71.26 199	63.91 309	50.22 256	74.46 206	80.75 251	26.81 393	80.25 146	59.43 182	86.50 199	87.37 55

fmvsm_s_conf0.5_n_a		67.00 226	65.95 238	70.17 191	69.72 301	61.16 143	73.34 166	56.83 343	40.96 340	68.36 295	80.08 264	62.84 151	67.57 305	66.90 116	74.50 340	81.78 196

fmvsm_l_conf0.5_n_a		66.66 227	65.97 237	68.72 224	67.09 332	61.38 139	70.03 214	69.15 274	38.59 359	68.41 294	80.36 257	56.56 225	68.32 297	66.10 118	77.45 316	76.46 278

fmvsm_s_conf0.1_n		66.60 228	65.54 239	69.77 199	68.99 308	59.15 164	72.12 177	56.74 345	40.72 345	68.25 298	80.14 263	61.18 175	66.92 311	67.34 111	74.40 341	83.23 157

MIMVSNet1		66.57 229	69.23 188	58.59 321	81.26 130	37.73 351	64.06 299	57.62 333	57.02 164	78.40 136	90.75 49	62.65 153	58.10 359	41.77 325	89.58 140	79.95 232

tfpnnormal		66.48 230	67.93 211	62.16 290	73.40 245	36.65 355	63.45 304	64.99 299	55.97 177	72.82 232	87.80 127	57.06 220	69.10 291	48.31 279	87.54 173	80.72 219

KD-MVS_self_test		66.38 231	67.51 217	62.97 282	61.76 370	34.39 373	58.11 345	75.30 210	50.84 249	77.12 152	85.42 180	56.84 222	69.44 287	51.07 252	91.16 99	85.08 94

SDMVSNet		66.36 232	67.85 214	61.88 292	73.04 256	46.14 278	58.54 340	71.36 247	51.42 239	68.93 287	82.72 225	65.62 130	62.22 341	54.41 228	84.67 223	77.28 268

mvs5depth		66.35 233	67.98 210	61.47 297	62.43 366	51.05 219	69.38 223	69.24 273	56.74 169	73.62 220	89.06 100	46.96 282	58.63 355	55.87 211	88.49 160	74.73 293

fmvsm_s_conf0.5_n		66.34 234	65.27 242	69.57 202	68.20 317	59.14 166	71.66 190	56.48 346	40.92 341	67.78 300	79.46 274	61.23 172	66.90 312	67.39 107	74.32 344	82.66 177

Anonymous202405211		66.02 235	66.89 228	63.43 276	74.22 232	38.14 346	59.00 335	66.13 289	63.33 111	69.76 276	85.95 176	51.88 250	70.50 278	44.23 310	87.52 174	81.64 199

miper_enhance_ethall		65.86 236	65.05 252	68.28 231	61.62 372	42.62 308	64.74 290	77.97 183	42.52 327	73.42 225	72.79 343	49.66 263	77.68 196	58.12 191	84.59 227	84.54 114

RPMNet		65.77 237	65.08 251	67.84 235	66.37 338	48.24 249	70.93 203	86.27 20	54.66 194	61.35 348	86.77 145	33.29 353	85.67 49	55.93 209	70.17 374	69.62 349

VPNet		65.58 238	67.56 216	59.65 313	79.72 142	30.17 394	60.27 327	62.14 317	54.19 207	71.24 257	86.63 153	58.80 198	67.62 303	44.17 311	90.87 114	81.18 203

PVSNet_BlendedMVS		65.38 239	64.30 253	68.61 225	69.81 297	49.36 239	65.60 281	78.96 161	45.50 300	59.98 357	78.61 289	51.82 251	78.20 186	44.30 308	84.11 234	78.27 255

TAMVS		65.31 240	63.75 259	69.97 197	82.23 117	59.76 159	66.78 266	63.37 313	45.20 306	69.79 275	79.37 278	47.42 281	72.17 259	34.48 375	85.15 217	77.99 262

test_yl		65.11 241	65.09 249	65.18 259	70.59 281	40.86 320	63.22 309	72.79 229	57.91 153	68.88 289	79.07 285	42.85 304	74.89 227	45.50 304	84.97 218	79.81 233

DCV-MVSNet		65.11 241	65.09 249	65.18 259	70.59 281	40.86 320	63.22 309	72.79 229	57.91 153	68.88 289	79.07 285	42.85 304	74.89 227	45.50 304	84.97 218	79.81 233

mvs_anonymous		65.08 243	65.49 240	63.83 270	63.79 360	37.60 352	66.52 269	69.82 268	43.44 322	73.46 224	86.08 172	58.79 199	71.75 267	51.90 245	75.63 328	82.15 188

FMVSNet3		65.00 244	65.16 245	64.52 264	69.47 302	37.56 353	66.63 267	70.38 263	51.55 237	74.72 198	83.27 218	37.89 336	74.44 233	47.12 288	85.37 210	81.57 200

ECVR-MVS		64.82 245	65.22 243	63.60 272	78.80 160	31.14 389	66.97 262	56.47 347	54.23 204	69.94 273	88.68 109	37.23 339	74.81 229	45.28 307	89.41 144	84.86 100

BH-w/o		64.81 246	64.29 254	66.36 251	76.08 203	54.71 197	65.61 280	75.23 212	50.10 258	71.05 260	71.86 349	54.33 238	79.02 164	38.20 348	76.14 324	65.36 376

EGC-MVSNET		64.77 247	61.17 281	75.60 102	86.90 43	74.47 34	84.04 39	68.62 278	0.60 430	1.13 432	91.61 32	65.32 135	74.15 238	64.01 135	88.28 162	78.17 257

test1111		64.62 248	65.19 244	62.93 283	79.01 158	29.91 395	65.45 282	54.41 357	54.09 209	71.47 255	88.48 114	37.02 340	74.29 236	46.83 293	89.94 132	84.58 113

cascas		64.59 249	62.77 271	70.05 195	75.27 212	50.02 230	61.79 315	71.61 240	42.46 328	63.68 335	68.89 378	49.33 267	80.35 143	47.82 285	84.05 235	79.78 235

TR-MVS		64.59 249	63.54 262	67.73 237	75.75 209	50.83 222	63.39 305	70.29 264	49.33 266	71.55 252	74.55 326	50.94 257	78.46 176	40.43 333	75.69 327	73.89 303

PM-MVS		64.49 251	63.61 261	67.14 244	76.68 192	75.15 31	68.49 241	42.85 409	51.17 246	77.85 143	80.51 254	45.76 284	66.31 320	52.83 242	76.35 322	59.96 399

jason		64.47 252	62.84 270	69.34 207	76.91 187	59.20 160	67.15 259	65.67 292	35.29 379	65.16 319	76.74 309	44.67 292	70.68 275	54.74 223	79.28 296	78.14 258
jason: jason.
xiu_mvs_v2_base		64.43 253	63.96 257	65.85 257	77.72 175	51.32 218	63.63 303	72.31 237	45.06 309	61.70 345	69.66 369	62.56 154	73.93 241	49.06 270	73.91 346	72.31 321

pmmvs-eth3d		64.41 254	63.27 266	67.82 236	75.81 208	60.18 156	69.49 220	62.05 320	38.81 358	74.13 212	82.23 232	43.76 298	68.65 294	42.53 318	80.63 278	74.63 294

CDS-MVSNet		64.33 255	62.66 272	69.35 206	80.44 137	58.28 174	65.26 284	65.66 293	44.36 312	67.30 307	75.54 316	43.27 300	71.77 265	37.68 352	84.44 230	78.01 261
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
PS-MVSNAJ		64.27 256	63.73 260	65.90 256	77.82 173	51.42 217	63.33 306	72.33 236	45.09 308	61.60 346	68.04 384	62.39 158	73.95 240	49.07 269	73.87 347	72.34 320

ab-mvs		64.11 257	65.13 248	61.05 302	71.99 266	38.03 349	67.59 249	68.79 276	49.08 270	65.32 318	86.26 164	58.02 211	66.85 315	39.33 337	79.79 292	78.27 255

CANet_DTU		64.04 258	63.83 258	64.66 262	68.39 312	42.97 305	73.45 165	74.50 218	52.05 231	54.78 388	75.44 319	43.99 296	70.42 280	53.49 238	78.41 306	80.59 223

VNet		64.01 259	65.15 247	60.57 307	73.28 247	35.61 365	57.60 347	67.08 284	54.61 195	66.76 310	83.37 213	56.28 227	66.87 313	42.19 321	85.20 216	79.23 244

sd_testset		63.55 260	65.38 241	58.07 324	73.04 256	38.83 340	57.41 348	65.44 296	51.42 239	68.93 287	82.72 225	63.76 147	58.11 358	41.05 329	84.67 223	77.28 268

Anonymous20240521		63.55 260	66.07 235	55.99 335	66.18 343	44.04 293	68.77 235	68.80 275	46.99 289	72.57 234	85.84 177	39.87 322	50.22 379	53.40 241	92.23 83	73.71 305

lupinMVS		63.36 262	61.49 279	68.97 217	74.93 216	59.19 161	65.80 277	64.52 305	34.68 385	63.53 338	74.25 331	43.19 301	70.62 276	53.88 235	78.67 302	77.10 273

ET-MVSNet_ETH3D		63.32 263	60.69 287	71.20 177	70.15 294	55.66 190	65.02 288	64.32 306	43.28 326	68.99 283	72.05 348	25.46 400	78.19 188	54.16 233	82.80 248	79.74 236

MVSTER		63.29 264	61.60 278	68.36 227	59.77 386	46.21 277	60.62 324	71.32 248	41.83 331	75.40 190	79.12 283	30.25 382	75.85 211	56.30 206	79.81 290	83.03 163

OpenMVS_ROB	54.93 17	63.23 265	63.28 265	63.07 280	69.81 297	45.34 283	68.52 240	67.14 283	43.74 318	70.61 263	79.22 280	47.90 279	72.66 250	48.75 272	73.84 348	71.21 334

IterMVS		63.12 266	62.48 273	65.02 261	66.34 340	52.86 210	63.81 300	62.25 316	46.57 292	71.51 253	80.40 256	44.60 293	66.82 316	51.38 250	75.47 330	75.38 288
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
HyFIR lowres test		63.01 267	60.47 288	70.61 181	83.04 104	54.10 202	59.93 330	72.24 238	33.67 390	69.00 282	75.63 315	38.69 330	76.93 203	36.60 362	75.45 331	80.81 216

GA-MVS		62.91 268	61.66 275	66.66 250	67.09 332	44.49 290	61.18 320	69.36 272	51.33 243	69.33 280	74.47 327	36.83 341	74.94 226	50.60 256	74.72 336	80.57 224

PVSNet_Blended		62.90 269	61.64 276	66.69 249	69.81 297	49.36 239	61.23 319	78.96 161	42.04 329	59.98 357	68.86 379	51.82 251	78.20 186	44.30 308	77.77 315	72.52 317

USDC		62.80 270	63.10 268	61.89 291	65.19 350	43.30 301	67.42 253	74.20 220	35.80 378	72.25 240	84.48 195	45.67 285	71.95 264	37.95 350	84.97 218	70.42 342

MonoMVSNet		62.75 271	63.42 263	60.73 306	65.60 347	40.77 322	72.49 173	70.56 261	52.49 225	75.07 192	79.42 276	39.52 326	69.97 282	46.59 295	69.06 380	71.44 329

Vis-MVSNet (Re-imp)		62.74 272	63.21 267	61.34 300	72.19 264	31.56 386	67.31 258	53.87 359	53.60 217	69.88 274	83.37 213	40.52 318	70.98 274	41.40 327	86.78 195	81.48 201

patch_mono-2		62.73 273	64.08 256	58.68 320	70.36 289	55.87 188	60.84 322	64.11 308	41.23 336	64.04 327	78.22 294	60.00 185	48.80 383	54.17 232	83.71 240	71.37 330

D2MVS		62.58 274	61.05 283	67.20 242	63.85 359	47.92 255	56.29 354	69.58 269	39.32 352	70.07 271	78.19 295	34.93 348	72.68 249	53.44 239	83.74 238	81.00 209

CL-MVSNet_self_test		62.44 275	63.40 264	59.55 314	72.34 263	32.38 381	56.39 353	64.84 301	51.21 245	67.46 305	81.01 248	50.75 258	63.51 336	38.47 346	88.12 165	82.75 172

MDA-MVSNet-bldmvs		62.34 276	61.73 274	64.16 265	61.64 371	49.90 233	48.11 394	57.24 339	53.31 219	80.95 107	79.39 277	49.00 271	61.55 343	45.92 300	80.05 285	81.03 207

miper_lstm_enhance		61.97 277	61.63 277	62.98 281	60.04 380	45.74 281	47.53 396	70.95 257	44.04 313	73.06 229	78.84 288	39.72 323	60.33 346	55.82 212	84.64 226	82.88 167

wuyk23d		61.97 277	66.25 232	49.12 374	58.19 396	60.77 152	66.32 270	52.97 367	55.93 179	90.62 6	86.91 140	73.07 60	35.98 422	20.63 424	91.63 89	50.62 411

thres600view7		61.82 279	61.38 280	63.12 279	71.81 268	34.93 369	64.64 292	56.99 341	54.78 192	70.33 266	79.74 268	32.07 364	72.42 256	38.61 344	83.46 243	82.02 190

SSC-MVS		61.79 280	66.08 234	48.89 376	76.91 187	10.00 434	53.56 373	47.37 394	68.20 63	76.56 169	89.21 92	54.13 239	57.59 360	54.75 222	74.07 345	79.08 246

PAPM		61.79 280	60.37 289	66.05 254	76.09 201	41.87 312	69.30 224	76.79 199	40.64 346	53.80 393	79.62 273	44.38 294	82.92 98	29.64 397	73.11 352	73.36 307

MVP-Stereo		61.56 282	59.22 296	68.58 226	79.28 148	60.44 154	69.20 226	71.57 241	43.58 320	56.42 379	78.37 292	39.57 325	76.46 210	34.86 374	60.16 407	68.86 356
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
CMPMVS	48.73 20	61.54 283	60.89 284	63.52 274	61.08 374	51.55 216	68.07 246	68.00 281	33.88 387	65.87 313	81.25 244	37.91 335	67.71 301	49.32 268	82.60 250	71.31 332
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
test2506		61.23 284	60.85 285	62.38 288	78.80 160	27.88 403	67.33 257	37.42 422	54.23 204	67.55 304	88.68 109	17.87 426	74.39 234	46.33 297	89.41 144	84.86 100

thres100view900		61.17 285	61.09 282	61.39 298	72.14 265	35.01 368	65.42 283	56.99 341	55.23 185	70.71 262	79.90 266	32.07 364	72.09 260	35.61 370	81.73 260	77.08 274

Patchmtry		60.91 286	63.01 269	54.62 342	66.10 344	26.27 411	67.47 252	56.40 348	54.05 210	72.04 244	86.66 150	33.19 354	60.17 347	43.69 312	87.45 177	77.42 266

EU-MVSNet		60.82 287	60.80 286	60.86 305	68.37 313	41.16 316	72.27 174	68.27 280	26.96 410	69.08 281	75.71 314	32.09 363	67.44 306	55.59 215	78.90 299	73.97 301

pmmvs4		60.78 288	59.04 298	66.00 255	73.06 255	57.67 177	64.53 295	60.22 326	36.91 371	65.96 312	77.27 304	39.66 324	68.54 295	38.87 341	74.89 335	71.80 326

thres400		60.77 289	59.97 291	63.15 278	70.78 277	35.35 366	63.27 307	57.47 334	53.00 221	68.31 296	77.09 306	32.45 361	72.09 260	35.61 370	81.73 260	82.02 190

MVS		60.62 290	59.97 291	62.58 286	68.13 319	47.28 267	68.59 238	73.96 221	32.19 394	59.94 359	68.86 379	50.48 259	77.64 197	41.85 324	75.74 326	62.83 388

thisisatest0515		60.48 291	57.86 309	68.34 228	67.25 330	46.42 274	60.58 325	62.14 317	40.82 342	63.58 337	69.12 373	26.28 396	78.34 182	48.83 271	82.13 253	80.26 229

tfpn200view9		60.35 292	59.97 291	61.51 295	70.78 277	35.35 366	63.27 307	57.47 334	53.00 221	68.31 296	77.09 306	32.45 361	72.09 260	35.61 370	81.73 260	77.08 274

ppachtmachnet_test		60.26 293	59.61 294	62.20 289	67.70 326	44.33 291	58.18 344	60.96 324	40.75 344	65.80 314	72.57 344	41.23 311	63.92 333	46.87 292	82.42 251	78.33 253

WB-MVS		60.04 294	64.19 255	47.59 379	76.09 201	10.22 433	52.44 379	46.74 396	65.17 88	74.07 214	87.48 129	53.48 242	55.28 366	49.36 267	72.84 353	77.28 268

Patchmatch-RL test		59.95 295	59.12 297	62.44 287	72.46 262	54.61 199	59.63 331	47.51 393	41.05 339	74.58 203	74.30 330	31.06 376	65.31 326	51.61 246	79.85 289	67.39 363

1314		59.83 296	58.86 300	62.74 285	65.71 346	44.78 288	68.59 238	72.63 233	33.54 392	61.05 352	67.29 390	43.62 299	71.26 272	49.49 266	67.84 388	72.19 323

IB-MVS	49.67 18	59.69 297	56.96 316	67.90 233	68.19 318	50.30 227	61.42 317	65.18 298	47.57 286	55.83 382	67.15 391	23.77 406	79.60 156	43.56 314	79.97 286	73.79 304
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
1112_ss		59.48 298	58.99 299	60.96 304	77.84 172	42.39 310	61.42 317	68.45 279	37.96 363	59.93 360	67.46 387	45.11 290	65.07 328	40.89 331	71.81 362	75.41 287

FPMVS		59.43 299	60.07 290	57.51 327	77.62 178	71.52 53	62.33 313	50.92 376	57.40 161	69.40 279	80.00 265	39.14 328	61.92 342	37.47 355	66.36 391	39.09 422

CVMVSNet		59.21 300	58.44 304	61.51 295	73.94 238	47.76 259	71.31 197	64.56 304	26.91 412	60.34 356	70.44 357	36.24 344	67.65 302	53.57 237	68.66 383	69.12 354

CR-MVSNet		58.96 301	58.49 303	60.36 309	66.37 338	48.24 249	70.93 203	56.40 348	32.87 393	61.35 348	86.66 150	33.19 354	63.22 337	48.50 276	70.17 374	69.62 349

reproduce_monomvs		58.94 302	58.14 307	61.35 299	59.70 387	40.98 319	60.24 328	63.51 312	45.85 297	68.95 285	75.31 320	18.27 424	65.82 322	51.47 248	79.97 286	77.26 271

EPNet_dtu		58.93 303	58.52 302	60.16 311	67.91 322	47.70 261	69.97 215	58.02 332	49.73 261	47.28 413	73.02 342	38.14 332	62.34 339	36.57 363	85.99 205	70.43 341
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
Test_1112_low_res		58.78 304	58.69 301	59.04 319	79.41 146	38.13 347	57.62 346	66.98 285	34.74 383	59.62 363	77.56 302	42.92 303	63.65 335	38.66 343	70.73 370	75.35 289

PatchMatch-RL		58.68 305	57.72 310	61.57 294	76.21 199	73.59 43	61.83 314	49.00 388	47.30 288	61.08 350	68.97 375	50.16 261	59.01 352	36.06 369	68.84 382	52.10 409

SCA		58.57 306	58.04 308	60.17 310	70.17 292	41.07 318	65.19 285	53.38 365	43.34 325	61.00 353	73.48 337	45.20 288	69.38 288	40.34 334	70.31 373	70.05 343

testing3		58.28 307	58.38 305	58.00 325	77.45 180	26.12 412	60.78 323	43.00 408	56.02 176	70.18 268	75.76 313	13.27 434	67.24 309	48.02 282	80.89 270	80.65 221

CHOSEN 1792x2688		58.09 308	56.30 321	63.45 275	79.95 140	50.93 221	54.07 371	65.59 294	28.56 406	61.53 347	74.33 329	41.09 314	66.52 319	33.91 378	67.69 389	72.92 311

HY-MVS	49.31 19	57.96 309	57.59 312	59.10 318	66.85 337	36.17 359	65.13 286	65.39 297	39.24 355	54.69 390	78.14 296	44.28 295	67.18 310	33.75 380	70.79 369	73.95 302

baseline1		57.82 310	58.36 306	56.19 334	69.17 305	30.76 392	62.94 311	55.21 352	46.04 295	63.83 332	78.47 290	41.20 312	63.68 334	39.44 336	68.99 381	74.13 300

thres200		57.55 311	57.02 315	59.17 316	67.89 323	34.93 369	58.91 338	57.25 338	50.24 255	64.01 328	71.46 352	32.49 360	71.39 271	31.31 388	79.57 294	71.19 335

CostFormer		57.35 312	56.14 322	60.97 303	63.76 361	38.43 342	67.50 251	60.22 326	37.14 370	59.12 365	76.34 311	32.78 357	71.99 263	39.12 340	69.27 379	72.47 318

SSC-MVS3.2		57.01 313	59.50 295	49.57 370	67.73 325	25.95 413	46.68 399	51.75 374	51.41 241	63.84 331	79.66 271	53.28 244	50.34 378	37.85 351	83.28 245	72.41 319

testing3-2		56.85 314	57.62 311	54.53 343	75.84 206	22.23 423	51.26 384	49.10 386	61.04 127	63.74 334	79.73 269	22.29 413	59.44 350	31.16 390	84.43 231	81.92 193

test_fmvs3		56.78 315	55.99 324	59.12 317	53.96 416	48.09 252	58.76 339	66.22 288	27.54 408	76.66 164	68.69 381	25.32 402	51.31 375	53.42 240	73.38 350	77.97 263

our_test_3		56.46 316	56.51 319	56.30 333	67.70 326	39.66 333	55.36 362	52.34 371	40.57 347	63.85 330	69.91 368	40.04 321	58.22 357	43.49 315	75.29 334	71.03 338

ttmdpeth		56.40 317	55.45 328	59.25 315	55.63 407	40.69 323	58.94 337	49.72 382	36.22 374	65.39 316	86.97 138	23.16 409	56.69 363	42.30 319	80.74 274	80.36 227

tpm2		56.12 318	54.64 335	60.55 308	66.24 341	36.01 360	68.14 244	56.77 344	33.60 391	58.25 368	75.52 318	30.25 382	74.33 235	33.27 381	69.76 378	71.32 331

tpmvs		55.84 319	55.45 328	57.01 329	60.33 378	33.20 379	65.89 274	59.29 330	47.52 287	56.04 380	73.60 336	31.05 377	68.06 300	40.64 332	64.64 395	69.77 347

gg-mvs-nofinetune		55.75 320	56.75 318	52.72 352	62.87 364	28.04 402	68.92 229	41.36 417	71.09 46	50.80 403	92.63 13	20.74 416	66.86 314	29.97 395	72.41 356	63.25 387

testing91		55.74 321	55.29 331	57.08 328	70.63 280	30.85 391	54.94 366	56.31 350	50.34 253	57.08 372	70.10 365	24.50 404	65.86 321	36.98 360	76.75 320	74.53 296

test20.03		55.74 321	57.51 313	50.42 363	59.89 385	32.09 383	50.63 385	49.01 387	50.11 257	65.07 320	83.23 220	45.61 286	48.11 388	30.22 393	83.82 237	71.07 337

MS-PatchMatch		55.59 323	54.89 333	57.68 326	69.18 304	49.05 242	61.00 321	62.93 315	35.98 376	58.36 367	68.93 377	36.71 342	66.59 318	37.62 354	63.30 399	57.39 405

baseline2		55.57 324	52.74 345	64.05 268	65.26 349	44.11 292	62.38 312	54.43 356	39.03 356	51.21 401	67.35 389	33.66 352	72.45 255	37.14 357	64.22 397	75.60 284

MVStest1		55.38 325	54.97 332	56.58 332	43.72 429	40.07 330	59.13 333	47.09 395	34.83 381	76.53 172	84.65 189	13.55 433	53.30 372	55.04 219	80.23 283	76.38 279

XXY-MVS		55.19 326	57.40 314	48.56 378	64.45 357	34.84 371	51.54 382	53.59 361	38.99 357	63.79 333	79.43 275	56.59 223	45.57 395	36.92 361	71.29 366	65.25 377

testing99		55.16 327	54.56 336	56.98 330	70.13 295	30.58 393	54.55 369	54.11 358	49.53 265	56.76 376	70.14 364	22.76 411	65.79 323	36.99 359	76.04 325	74.57 295

FMVSNet5		55.08 328	55.54 327	53.71 345	65.80 345	33.50 378	56.22 355	52.50 369	43.72 319	61.06 351	83.38 212	25.46 400	54.87 367	30.11 394	81.64 265	72.75 315

test_fmvs2		54.80 329	54.11 339	56.88 331	51.76 420	49.95 232	56.70 352	65.80 291	26.22 413	69.42 278	65.25 395	31.82 368	49.98 380	49.63 264	70.36 372	70.71 339

PatchmatchNet		54.60 330	54.27 337	55.59 338	65.17 352	39.08 335	66.92 263	51.80 373	39.89 349	58.39 366	73.12 341	31.69 370	58.33 356	43.01 317	58.38 413	69.38 352
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
MIMVSNet		54.39 331	56.12 323	49.20 372	72.57 261	30.91 390	59.98 329	48.43 390	41.66 332	55.94 381	83.86 205	41.19 313	50.42 377	26.05 408	75.38 332	66.27 371

Syy-MVS		54.13 332	55.45 328	50.18 364	68.77 309	23.59 417	55.02 363	44.55 402	43.80 315	58.05 369	64.07 397	46.22 283	58.83 353	46.16 298	72.36 357	68.12 359

Anonymous20231206		54.13 332	55.82 325	49.04 375	70.89 275	35.96 361	51.73 381	50.87 377	34.86 380	62.49 343	79.22 280	42.52 307	44.29 405	27.95 404	81.88 256	66.88 367

JIA-IIPM		54.03 334	51.62 354	61.25 301	59.14 390	55.21 195	59.10 334	47.72 391	50.85 248	50.31 407	85.81 178	20.10 418	63.97 332	36.16 367	55.41 418	64.55 384

tpm cat1		54.02 335	52.63 347	58.19 323	64.85 356	39.86 332	66.26 271	57.28 337	32.16 395	56.90 374	70.39 359	32.75 358	65.30 327	34.29 376	58.79 410	69.41 351

testgi		54.00 336	56.86 317	45.45 388	58.20 395	25.81 414	49.05 390	49.50 384	45.43 303	67.84 299	81.17 245	51.81 253	43.20 409	29.30 398	79.41 295	67.34 365

WB-MVSnew		53.94 337	54.76 334	51.49 358	71.53 270	28.05 401	58.22 343	50.36 379	37.94 364	59.16 364	70.17 363	49.21 268	51.94 374	24.49 415	71.80 363	74.47 298

WBMVS		53.38 338	54.14 338	51.11 360	70.16 293	26.66 407	50.52 387	51.64 375	39.32 352	63.08 341	77.16 305	23.53 407	55.56 364	31.99 385	79.88 288	71.11 336

testing222		53.37 339	52.50 349	55.98 336	70.51 286	29.68 396	56.20 356	51.85 372	46.19 294	56.76 376	68.94 376	19.18 422	65.39 325	25.87 411	76.98 318	72.87 313

PatchT		53.35 340	56.47 320	43.99 395	64.19 358	17.46 426	59.15 332	43.10 407	52.11 230	54.74 389	86.95 139	29.97 385	49.98 380	43.62 313	74.40 341	64.53 385

testing11		53.13 341	52.26 351	55.75 337	70.44 287	31.73 385	54.75 367	52.40 370	44.81 310	52.36 398	68.40 383	21.83 414	65.74 324	32.64 384	72.73 354	69.78 346

test_vis1_n_1920		52.96 342	53.50 341	51.32 359	59.15 389	44.90 287	56.13 357	64.29 307	30.56 404	59.87 361	60.68 408	40.16 320	47.47 389	48.25 280	62.46 401	61.58 396

UWE-MVS		52.94 343	52.70 346	53.65 346	73.56 241	27.49 404	57.30 349	49.57 383	38.56 360	62.79 342	71.42 353	19.49 421	60.41 345	24.33 417	77.33 317	73.06 309

new-patchmatchnet		52.89 344	55.76 326	44.26 394	59.94 384	6.31 435	37.36 419	50.76 378	41.10 337	64.28 325	79.82 267	44.77 291	48.43 387	36.24 366	87.61 172	78.03 260

test_fmvs1_n		52.70 345	52.01 352	54.76 340	53.83 417	50.36 225	55.80 359	65.90 290	24.96 417	65.39 316	60.64 409	27.69 391	48.46 385	45.88 301	67.99 386	65.46 375

YYNet1		52.58 346	53.50 341	49.85 366	54.15 413	36.45 358	40.53 412	46.55 398	38.09 362	75.52 187	73.31 340	41.08 315	43.88 406	41.10 328	71.14 368	69.21 353

MDA-MVSNet_test_wron		52.57 347	53.49 343	49.81 367	54.24 412	36.47 357	40.48 413	46.58 397	38.13 361	75.47 189	73.32 339	41.05 316	43.85 407	40.98 330	71.20 367	69.10 355

pmmvs5		52.49 348	52.58 348	52.21 354	54.99 410	32.38 381	55.45 361	53.84 360	32.15 396	55.49 384	74.81 322	38.08 333	57.37 361	34.02 377	74.40 341	66.88 367

UnsupCasMVSNet_eth		52.26 349	53.29 344	49.16 373	55.08 409	33.67 377	50.03 388	58.79 331	37.67 366	63.43 340	74.75 324	41.82 309	45.83 393	38.59 345	59.42 409	67.98 362

N_pmnet		52.06 350	51.11 359	54.92 339	59.64 388	71.03 57	37.42 418	61.62 323	33.68 389	57.12 371	72.10 345	37.94 334	31.03 424	29.13 403	71.35 365	62.70 389

KD-MVS_2432*1600		52.05 351	51.58 355	53.44 348	52.11 418	31.20 387	44.88 405	64.83 302	41.53 333	64.37 323	70.03 366	15.61 430	64.20 330	36.25 364	74.61 338	64.93 381

miper_refine_blended		52.05 351	51.58 355	53.44 348	52.11 418	31.20 387	44.88 405	64.83 302	41.53 333	64.37 323	70.03 366	15.61 430	64.20 330	36.25 364	74.61 338	64.93 381

test_vis3_rt		51.94 353	51.04 360	54.65 341	46.32 427	50.13 229	44.34 407	78.17 179	23.62 421	68.95 285	62.81 401	21.41 415	38.52 420	41.49 326	72.22 359	75.30 290

PVSNet	43.83 21	51.56 354	51.17 358	52.73 351	68.34 314	38.27 344	48.22 393	53.56 363	36.41 373	54.29 391	64.94 396	34.60 349	54.20 370	30.34 392	69.87 376	65.71 374

test_fmvs1		51.51 355	50.86 363	53.48 347	49.72 423	49.35 241	54.11 370	64.96 300	24.64 419	63.66 336	59.61 412	28.33 390	48.45 386	45.38 306	67.30 390	62.66 391

myMVS_eth3d28		51.35 356	51.99 353	49.44 371	69.21 303	22.51 421	49.82 389	49.11 385	49.00 271	55.03 386	70.31 360	22.73 412	52.88 373	24.33 417	78.39 307	72.92 311

test_vis1_n		51.27 357	50.41 367	53.83 344	56.99 399	50.01 231	56.75 351	60.53 325	25.68 415	59.74 362	57.86 413	29.40 387	47.41 390	43.10 316	63.66 398	64.08 386

test_cas_vis1_n_1920		50.90 358	50.92 362	50.83 362	54.12 415	47.80 257	51.44 383	54.61 355	26.95 411	63.95 329	60.85 407	37.86 337	44.97 400	45.53 303	62.97 400	59.72 400

tpm		50.60 359	52.42 350	45.14 390	65.18 351	26.29 410	60.30 326	43.50 405	37.41 368	57.01 373	79.09 284	30.20 384	42.32 410	32.77 383	66.36 391	66.81 369

test-LLR		50.43 360	50.69 365	49.64 368	60.76 375	41.87 312	53.18 374	45.48 400	43.41 323	49.41 408	60.47 410	29.22 388	44.73 402	42.09 322	72.14 360	62.33 394

myMVS_eth3d		50.36 361	50.52 366	49.88 365	68.77 309	22.69 419	55.02 363	44.55 402	43.80 315	58.05 369	64.07 397	14.16 432	58.83 353	33.90 379	72.36 357	68.12 359

ETVMVS		50.32 362	49.87 370	51.68 356	70.30 291	26.66 407	52.33 380	43.93 404	43.54 321	54.91 387	67.95 385	20.01 419	60.17 347	22.47 420	73.40 349	68.22 358

tpmrst		50.15 363	51.38 357	46.45 385	56.05 403	24.77 415	64.40 297	49.98 380	36.14 375	53.32 395	69.59 370	35.16 347	48.69 384	39.24 338	58.51 412	65.89 372

UnsupCasMVSNet_bld		50.01 364	51.03 361	46.95 381	58.61 392	32.64 380	48.31 392	53.27 366	34.27 386	60.47 355	71.53 351	41.40 310	47.07 391	30.68 391	60.78 406	61.13 397

dmvs_re		49.91 365	50.77 364	47.34 380	59.98 381	38.86 339	53.18 374	53.58 362	39.75 350	55.06 385	61.58 406	36.42 343	44.40 404	29.15 402	68.23 384	58.75 402

WTY-MVS		49.39 366	50.31 368	46.62 384	61.22 373	32.00 384	46.61 400	49.77 381	33.87 388	54.12 392	69.55 371	41.96 308	45.40 397	31.28 389	64.42 396	62.47 392

UBG		49.18 367	49.35 371	48.66 377	70.36 289	26.56 409	50.53 386	45.61 399	37.43 367	53.37 394	65.97 392	23.03 410	54.20 370	26.29 406	71.54 364	65.20 378

ADS-MVSNet2		48.76 368	47.25 377	53.29 350	55.90 405	40.54 327	47.34 397	54.99 354	31.41 401	50.48 404	72.06 346	31.23 373	54.26 369	25.93 409	55.93 415	65.07 379

test-mter		48.56 369	48.20 374	49.64 368	60.76 375	41.87 312	53.18 374	45.48 400	31.91 399	49.41 408	60.47 410	18.34 423	44.73 402	42.09 322	72.14 360	62.33 394

Patchmatch-test		47.93 370	49.96 369	41.84 399	57.42 398	24.26 416	48.75 391	41.49 416	39.30 354	56.79 375	73.48 337	30.48 381	33.87 423	29.29 399	72.61 355	67.39 363

test0.0.03 1		47.72 371	48.31 373	45.93 386	55.53 408	29.39 397	46.40 401	41.21 418	43.41 323	55.81 383	67.65 386	29.22 388	43.77 408	25.73 412	69.87 376	64.62 383

sss		47.59 372	48.32 372	45.40 389	56.73 402	33.96 375	45.17 403	48.51 389	32.11 398	52.37 397	65.79 393	40.39 319	41.91 413	31.85 386	61.97 403	60.35 398

pmmvs3		46.71 373	45.09 383	51.55 357	56.76 401	48.25 248	55.78 360	39.53 421	24.13 420	50.35 406	63.40 399	15.90 429	51.08 376	29.29 399	70.69 371	55.33 408

test_vis1_rt		46.70 374	45.24 382	51.06 361	44.58 428	51.04 220	39.91 414	67.56 282	21.84 425	51.94 399	50.79 421	33.83 351	39.77 417	35.25 373	61.50 404	62.38 393

EPMVS		45.74 375	46.53 378	43.39 397	54.14 414	22.33 422	55.02 363	35.00 425	34.69 384	51.09 402	70.20 362	25.92 398	42.04 412	37.19 356	55.50 417	65.78 373

MVS-HIRNet		45.53 376	47.29 376	40.24 402	62.29 367	26.82 406	56.02 358	37.41 423	29.74 405	43.69 423	81.27 243	33.96 350	55.48 365	24.46 416	56.79 414	38.43 423

dmvs_testset		45.26 377	47.51 375	38.49 405	59.96 383	14.71 429	58.50 341	43.39 406	41.30 335	51.79 400	56.48 414	39.44 327	49.91 382	21.42 422	55.35 419	50.85 410

TESTMET0.1,1		45.17 378	44.93 384	45.89 387	56.02 404	38.31 343	53.18 374	41.94 415	27.85 407	44.86 419	56.47 415	17.93 425	41.50 415	38.08 349	68.06 385	57.85 403

E-PMN		45.17 378	45.36 381	44.60 392	50.07 421	42.75 306	38.66 416	42.29 413	46.39 293	39.55 424	51.15 420	26.00 397	45.37 398	37.68 352	76.41 321	45.69 417

PMMVS		44.69 380	43.95 389	46.92 382	50.05 422	53.47 208	48.08 395	42.40 411	22.36 423	44.01 422	53.05 418	42.60 306	45.49 396	31.69 387	61.36 405	41.79 420

ADS-MVSNet		44.62 381	45.58 380	41.73 400	55.90 405	20.83 424	47.34 397	39.94 420	31.41 401	50.48 404	72.06 346	31.23 373	39.31 418	25.93 409	55.93 415	65.07 379

EMVS		44.61 382	44.45 387	45.10 391	48.91 424	43.00 304	37.92 417	41.10 419	46.75 291	38.00 426	48.43 423	26.42 395	46.27 392	37.11 358	75.38 332	46.03 416

UWE-MVS-28		44.18 383	44.37 388	43.61 396	60.10 379	16.96 427	52.62 378	33.27 426	36.79 372	48.86 410	69.47 372	19.96 420	45.65 394	13.40 427	64.83 394	68.23 357

dp		44.09 384	44.88 385	41.72 401	58.53 394	23.18 418	54.70 368	42.38 412	34.80 382	44.25 421	65.61 394	24.48 405	44.80 401	29.77 396	49.42 421	57.18 406

test_f		43.79 385	45.63 379	38.24 406	42.29 432	38.58 341	34.76 421	47.68 392	22.22 424	67.34 306	63.15 400	31.82 368	30.60 425	39.19 339	62.28 402	45.53 418

mvsany_test3		43.76 386	41.01 390	52.01 355	48.09 425	57.74 176	42.47 409	23.85 432	23.30 422	64.80 321	62.17 404	27.12 392	40.59 416	29.17 401	48.11 422	57.69 404

DSMNet-mixed		43.18 387	44.66 386	38.75 404	54.75 411	28.88 400	57.06 350	27.42 429	13.47 427	47.27 414	77.67 301	38.83 329	39.29 419	25.32 414	60.12 408	48.08 413

CHOSEN 280x420		41.62 388	39.89 393	46.80 383	61.81 369	51.59 215	33.56 422	35.74 424	27.48 409	37.64 427	53.53 416	23.24 408	42.09 411	27.39 405	58.64 411	46.72 415

PVSNet_0	36.71 22	41.12 389	40.78 392	42.14 398	59.97 382	40.13 329	40.97 411	42.24 414	30.81 403	44.86 419	49.41 422	40.70 317	45.12 399	23.15 419	34.96 425	41.16 421

mvsany_test1		37.88 390	35.74 395	44.28 393	47.28 426	49.90 233	36.54 420	24.37 431	19.56 426	45.76 415	53.46 417	32.99 356	37.97 421	26.17 407	35.52 424	44.99 419

PMMVS2		37.74 391	40.87 391	28.36 408	42.41 431	5.35 436	24.61 423	27.75 428	32.15 396	47.85 412	70.27 361	35.85 345	29.51 426	19.08 425	67.85 387	50.22 412

new_pmnet		37.55 392	39.80 394	30.79 407	56.83 400	16.46 428	39.35 415	30.65 427	25.59 416	45.26 417	61.60 405	24.54 403	28.02 427	21.60 421	52.80 420	47.90 414

MVE	27.91 23	36.69 393	35.64 396	39.84 403	43.37 430	35.85 363	19.49 424	24.61 430	24.68 418	39.05 425	62.63 403	38.67 331	27.10 428	21.04 423	47.25 423	56.56 407
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
dongtai		31.66 394	32.98 397	27.71 409	58.58 393	12.61 431	45.02 404	14.24 435	41.90 330	47.93 411	43.91 424	10.65 435	41.81 414	14.06 426	20.53 428	28.72 425

kuosan		22.02 395	23.52 399	17.54 411	41.56 433	11.24 432	41.99 410	13.39 436	26.13 414	28.87 428	30.75 426	9.72 436	21.94 430	4.77 431	14.49 429	19.43 426

test_method		19.26 396	19.12 400	19.71 410	9.09 435	1.91 438	7.79 426	53.44 364	1.42 429	10.27 431	35.80 425	17.42 427	25.11 429	12.44 428	24.38 427	32.10 424

cdsmvs_eth3d_5k		17.71 397	23.62 398	0.00 416	0.00 439	0.00 441	0.00 427	70.17 265	0.00 434	0.00 435	74.25 331	68.16 100	0.00 435	0.00 434	0.00 433	0.00 431

tmp_tt		11.98 398	14.73 401	3.72 413	2.28 436	4.62 437	19.44 425	14.50 434	0.47 431	21.55 429	9.58 429	25.78 399	4.57 432	11.61 429	27.37 426	1.96 428

ab-mvs-re		5.62 399	7.50 402	0.00 416	0.00 439	0.00 441	0.00 427	0.00 440	0.00 434	0.00 435	67.46 387	0.00 439	0.00 435	0.00 434	0.00 433	0.00 431

pcd_1.5k_mvsjas		5.20 400	6.93 403	0.00 416	0.00 439	0.00 441	0.00 427	0.00 440	0.00 434	0.00 435	0.00 434	62.39 158	0.00 435	0.00 434	0.00 433	0.00 431

test123		4.43 401	5.78 404	0.39 415	0.97 437	0.28 439	46.33 402	0.45 438	0.31 432	0.62 433	1.50 432	0.61 438	0.11 434	0.56 432	0.63 431	0.77 430

testmvs		4.06 402	5.28 405	0.41 414	0.64 438	0.16 440	42.54 408	0.31 439	0.26 433	0.50 434	1.40 433	0.77 437	0.17 433	0.56 432	0.55 432	0.90 429

mmdepth		0.00 403	0.00 406	0.00 416	0.00 439	0.00 441	0.00 427	0.00 440	0.00 434	0.00 435	0.00 434	0.00 439	0.00 435	0.00 434	0.00 433	0.00 431

monomultidepth		0.00 403	0.00 406	0.00 416	0.00 439	0.00 441	0.00 427	0.00 440	0.00 434	0.00 435	0.00 434	0.00 439	0.00 435	0.00 434	0.00 433	0.00 431

test_blank		0.00 403	0.00 406	0.00 416	0.00 439	0.00 441	0.00 427	0.00 440	0.00 434	0.00 435	0.00 434	0.00 439	0.00 435	0.00 434	0.00 433	0.00 431

uanet_test		0.00 403	0.00 406	0.00 416	0.00 439	0.00 441	0.00 427	0.00 440	0.00 434	0.00 435	0.00 434	0.00 439	0.00 435	0.00 434	0.00 433	0.00 431

DCPMVS		0.00 403	0.00 406	0.00 416	0.00 439	0.00 441	0.00 427	0.00 440	0.00 434	0.00 435	0.00 434	0.00 439	0.00 435	0.00 434	0.00 433	0.00 431

sosnet-low-res		0.00 403	0.00 406	0.00 416	0.00 439	0.00 441	0.00 427	0.00 440	0.00 434	0.00 435	0.00 434	0.00 439	0.00 435	0.00 434	0.00 433	0.00 431

sosnet		0.00 403	0.00 406	0.00 416	0.00 439	0.00 441	0.00 427	0.00 440	0.00 434	0.00 435	0.00 434	0.00 439	0.00 435	0.00 434	0.00 433	0.00 431

uncertanet		0.00 403	0.00 406	0.00 416	0.00 439	0.00 441	0.00 427	0.00 440	0.00 434	0.00 435	0.00 434	0.00 439	0.00 435	0.00 434	0.00 433	0.00 431

Regformer		0.00 403	0.00 406	0.00 416	0.00 439	0.00 441	0.00 427	0.00 440	0.00 434	0.00 435	0.00 434	0.00 439	0.00 435	0.00 434	0.00 433	0.00 431

uanet		0.00 403	0.00 406	0.00 416	0.00 439	0.00 441	0.00 427	0.00 440	0.00 434	0.00 435	0.00 434	0.00 439	0.00 435	0.00 434	0.00 433	0.00 431

WAC-MVS						22.69 419								36.10 368

FOURS1					89.19 24	77.84 14	91.64 1	89.11 3	84.05 3	91.57 3

MSC_two_6792asdad				79.02 57	83.14 99	67.03 91		80.75 126					86.24 24	77.27 37	94.85 29	83.78 136

PC_three_1452									46.98 290	81.83 94	86.28 162	66.55 123	84.47 74	63.31 148	90.78 115	83.49 144

No_MVS				79.02 57	83.14 99	67.03 91		80.75 126					86.24 24	77.27 37	94.85 29	83.78 136

test_one_0601					85.84 64	61.45 138		85.63 30	75.27 21	85.62 51	90.38 67	76.72 30

eth-test2					0.00 439

eth-test					0.00 439

ZD-MVS					83.91 90	69.36 73		81.09 121	58.91 147	82.73 87	89.11 97	75.77 38	86.63 14	72.73 66	92.93 72

RE-MVS-def			85.50 7		86.19 50	79.18 7	87.23 9	86.27 20	77.51 14	87.65 22	90.73 50	81.38 7		78.11 27	94.46 39	84.89 97

IU-MVS					86.12 54	60.90 148		80.38 138	45.49 302	81.31 102				75.64 45	94.39 44	84.65 106

OPU-MVS				78.65 64	83.44 97	66.85 93	83.62 46				86.12 170	66.82 115	86.01 34	61.72 157	89.79 136	83.08 161

test_241102_TWO								84.80 48	72.61 35	84.93 59	89.70 83	77.73 24	85.89 42	75.29 46	94.22 55	83.25 155

test_241102_ONE					86.12 54	61.06 144		84.72 52	72.64 34	87.38 28	89.47 86	77.48 26	85.74 46

9.14			80.22 57		80.68 134		80.35 77	87.69 11	59.90 136	83.00 80	88.20 120	74.57 50	81.75 117	73.75 59	93.78 60

save fliter					87.00 40	67.23 90	79.24 89	77.94 184	56.65 172

test_0728_THIRD									74.03 25	85.83 46	90.41 62	75.58 40	85.69 47	77.43 34	94.74 33	84.31 124

test_0728_SECOND				76.57 87	86.20 49	60.57 153	83.77 44	85.49 32					85.90 40	75.86 42	94.39 44	83.25 155

test0726					86.16 52	60.78 150	83.81 43	85.10 43	72.48 37	85.27 56	89.96 79	78.57 19

GSMVS																70.05 343

test_part2					85.90 60	66.44 95				84.61 65

sam_mvs1												31.41 371				70.05 343

sam_mvs												31.21 375

ambc				70.10 194	77.74 174	50.21 228	74.28 158	77.93 185		79.26 124	88.29 119	54.11 240	79.77 153	64.43 131	91.10 104	80.30 228

MTGPA								80.63 132

test_post1							66.63 267				2.08 430	30.66 380	59.33 351	40.34 334

test_post											1.99 431	30.91 378	54.76 368

patchmatchnet-post											68.99 374	31.32 372	69.38 288

GG-mvs-BLEND				52.24 353	60.64 377	29.21 399	69.73 219	42.41 410		45.47 416	52.33 419	20.43 417	68.16 298	25.52 413	65.42 393	59.36 401

MTMP							84.83 34	19.26 433

gm-plane-assit					62.51 365	33.91 376			37.25 369		62.71 402		72.74 248	38.70 342

test9_res														72.12 74	91.37 94	77.40 267

TEST9					85.47 67	69.32 74	76.42 123	78.69 169	53.73 216	76.97 153	86.74 146	66.84 114	81.10 127

test_8					85.09 73	67.89 83	76.26 128	78.66 171	54.00 211	76.89 157	86.72 148	66.60 120	80.89 137

agg_prior2														70.70 78	90.93 109	78.55 252

agg_prior					84.44 85	66.02 101		78.62 172		76.95 155			80.34 144

TestCases				78.35 68	79.19 152	70.81 59		88.64 4	65.37 83	80.09 117	88.17 121	70.33 81	78.43 178	55.60 213	90.90 111	85.81 78

test_prior4						70.14 67	77.57 106

test_prior2							75.57 136		58.92 146	76.53 172	86.78 144	67.83 107		69.81 84	92.76 75

test_prior				75.27 106	82.15 118	59.85 158		84.33 63					83.39 90			82.58 179

旧先验2							71.17 200		45.11 307	78.54 135			61.28 344	59.19 184

新几何2							71.33 196

新几何1				69.99 196	88.37 35	71.34 55		62.08 319	43.85 314	74.99 194	86.11 171	52.85 246	70.57 277	50.99 253	83.23 246	68.05 361

旧先验1					84.55 82	60.36 155		63.69 310			87.05 137	54.65 235			83.34 244	69.66 348

无先验							74.82 143	70.94 258	47.75 285				76.85 206	54.47 226		72.09 324

原ACMM2							74.78 147

原ACMM1				73.90 122	85.90 60	65.15 110		81.67 107	50.97 247	74.25 210	86.16 168	61.60 166	83.54 85	56.75 200	91.08 105	73.00 310

test222					87.30 38	69.15 77	67.85 247	59.59 329	41.06 338	73.05 230	85.72 179	48.03 278			80.65 276	66.92 366

testdata2													67.30 307	48.34 278

segment_acmp												68.30 99

testdata				64.13 266	85.87 62	63.34 123		61.80 322	47.83 283	76.42 177	86.60 155	48.83 272	62.31 340	54.46 227	81.26 268	66.74 370

testdata1							68.34 243		57.24 163

test12				76.51 88	82.28 116	60.94 147		81.64 108		73.60 221		64.88 139	85.19 62		90.42 122	83.38 151

plane_prior7					85.18 70	66.21 98

plane_prior6					84.18 88	65.31 107						60.83 179

plane_prior5								85.49 32					86.15 29	71.09 75	90.94 107	84.82 102

plane_prior4											89.11 97

plane_prior3						65.67 103			63.82 102	78.23 137

plane_prior2							82.74 55		65.45 80

plane_prior1					84.46 84

plane_prior						65.18 108	80.06 83		61.88 122						89.91 133

n2								0.00 440

nn								0.00 440

door-mid								55.02 353

lessismore_v0				72.75 152	79.60 144	56.83 183		57.37 336		83.80 74	89.01 101	47.45 280	78.74 170	64.39 132	86.49 200	82.69 176

LGP-MVS_train				80.90 36	87.00 40	70.41 64		86.35 17	69.77 55	87.75 19	91.13 38	81.83 3	86.20 26	77.13 39	95.96 6	86.08 72

test11								82.71 91

door								52.91 368

HQP5-MVS						58.80 169

HQP-NCC					82.37 113		77.32 111		59.08 141	71.58 248

ACMP_Plane					82.37 113		77.32 111		59.08 141	71.58 248

BP-MVS														67.38 109

HQP4-MVS										71.59 247			85.31 54			83.74 138

HQP3-MVS								84.12 69							89.16 148

HQP2-MVS												58.09 206

NP-MVS					83.34 98	63.07 126					85.97 174

MDTV_nov1_ep13_2view						18.41 425	53.74 372		31.57 400	44.89 418		29.90 386		32.93 382		71.48 328

MDTV_nov1_ep13			54.05 340		65.54 348	29.30 398	59.00 335	55.22 351	35.96 377	52.44 396	75.98 312	30.77 379	59.62 349	38.21 347	73.33 351

ACMMP++_ref															89.47 143

ACMMP++															91.96 85

Test By Simon												62.56 154

ITE_SJBPF				80.35 42	76.94 186	73.60 42		80.48 135	66.87 68	83.64 76	86.18 166	70.25 83	79.90 152	61.12 163	88.95 156	87.56 54

DeepMVS_CX				11.83 412	15.51 434	13.86 430		11.25 437	5.76 428	20.85 430	26.46 427	17.06 428	9.22 431	9.69 430	13.82 430	12.42 427

High-resolution multi-view benchmark