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 58	91.63 1	86.34 1	97.97 1	94.77 3	66.57 127	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	63.30 128	84.80 35	87.77 11	86.18 2	96.26 2	96.06 1	90.32 1	84.49 72	68.08 106	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 16	79.37 15	84.79 69	74.51 56	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 29	78.70 10	88.94 13	91.88 27	79.74 12	86.05 32	79.90 10	95.21 18	82.72 191

our_new_method		84.97 4	85.93 4	82.10 21	86.11 57	77.53 18	87.08 13	85.81 29	78.70 10	88.94 13	91.88 27	79.74 12	86.05 32	79.90 10	95.21 18	82.72 191

reproduce_model		84.87 6	85.80 6	82.05 23	85.52 66	78.14 13	87.69 6	85.36 39	79.26 7	89.12 12	92.10 21	77.52 26	85.92 39	80.47 9	95.20 20	82.10 208

SR-MVS-dyc-post		84.75 7	85.26 9	83.21 4	86.19 50	79.18 7	87.23 9	86.27 21	77.51 14	87.65 22	90.73 54	79.20 16	85.58 51	78.11 28	94.46 41	84.89 110

HPM-MVS_fast		84.59 8	85.10 10	83.06 5	88.60 33	75.83 27	86.27 27	86.89 17	73.69 27	86.17 41	91.70 33	78.23 22	85.20 61	79.45 17	94.91 30	88.15 50

SR-MVS		84.51 9	85.27 8	82.25 19	88.52 34	77.71 15	86.81 19	85.25 41	77.42 17	86.15 42	90.24 77	81.69 5	85.94 36	77.77 31	93.58 66	83.09 176

ACMMP		84.22 10	84.84 13	82.35 18	89.23 22	76.66 26	87.65 7	85.89 27	71.03 48	85.85 46	90.58 58	78.77 18	85.78 44	79.37 20	95.17 22	84.62 123
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 12	81.94 24	84.82 77	75.40 29	91.60 3	87.80 9	73.52 29	88.90 15	93.06 9	71.39 74	81.53 127	81.53 5	92.15 86	88.91 40
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 14	82.60 14	88.21 36	74.40 35	85.24 31	87.21 15	70.69 51	85.14 58	90.42 65	78.99 17	86.62 15	80.83 7	94.93 29	86.79 69
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 15	82.80 11	89.42 18	79.74 6	88.19 5	84.43 62	71.96 44	84.70 65	90.56 59	77.12 29	86.18 28	79.24 22	95.36 15	82.49 198

mPP-MVS		84.01 14	84.39 16	82.88 7	90.65 4	81.38 4	87.08 13	82.79 91	72.41 40	85.11 59	90.85 51	76.65 32	84.89 66	79.30 21	94.63 38	82.35 201

COLMAP_ROB	72.78 3	83.75 15	84.11 20	82.68 13	82.97 109	74.39 36	87.18 11	88.18 8	78.98 8	86.11 44	91.47 38	79.70 14	85.76 45	66.91 125	95.46 14	87.89 52
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 22	82.69 12	89.78 11	77.51 22	87.01 17	84.19 72	70.23 52	84.49 67	90.67 57	75.15 45	86.37 20	79.58 15	94.26 54	84.18 141

APD-MVS_3200maxsize		83.57 17	84.33 17	81.31 32	82.83 112	73.53 44	85.50 30	87.45 14	74.11 23	86.45 39	90.52 62	80.02 10	84.48 73	77.73 32	94.34 52	85.93 85

region2R		83.54 18	83.86 24	82.58 15	89.82 10	77.53 18	87.06 16	84.23 71	70.19 54	83.86 74	90.72 56	75.20 44	86.27 23	79.41 19	94.25 55	83.95 147

XVS		83.51 19	83.73 25	82.85 9	89.43 16	77.61 16	86.80 20	84.66 57	72.71 33	82.87 84	90.39 69	73.86 56	86.31 21	78.84 24	94.03 58	84.64 121

LPG-MVS_test		83.47 20	84.33 17	80.90 36	87.00 40	70.41 64	82.04 62	86.35 18	69.77 56	87.75 19	91.13 42	81.83 3	86.20 26	77.13 40	95.96 6	86.08 81

lecture		83.41 21	85.02 11	78.58 66	83.87 94	67.26 91	84.47 37	88.27 7	73.64 28	87.35 31	91.96 24	78.55 21	82.92 100	81.59 4	95.50 11	85.56 95

HFP-MVS		83.39 22	84.03 21	81.48 27	89.25 21	75.69 28	87.01 17	84.27 68	70.23 52	84.47 68	90.43 64	76.79 30	85.94 36	79.58 15	94.23 56	82.82 187

MTAPA		83.19 23	83.87 23	81.13 34	91.16 3	78.16 12	84.87 33	80.63 138	72.08 42	84.93 60	90.79 52	74.65 50	84.42 75	80.98 6	94.75 34	80.82 239

MP-MVS		83.19 23	83.54 28	82.14 20	90.54 5	79.00 9	86.42 25	83.59 81	71.31 45	81.26 104	90.96 46	74.57 51	84.69 70	78.41 26	94.78 33	82.74 190
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
ZNCC-MVS		83.12 25	83.68 26	81.45 28	89.14 25	73.28 46	86.32 26	85.97 26	67.39 68	84.02 72	90.39 69	74.73 49	86.46 17	80.73 8	94.43 45	84.60 126

PGM-MVS		83.07 26	83.25 35	82.54 16	89.57 14	77.21 24	82.04 62	85.40 37	67.96 65	84.91 63	90.88 49	75.59 40	86.57 16	78.16 27	94.71 36	83.82 149

SteuartSystems-ACMMP		83.07 26	83.64 27	81.35 30	85.14 73	71.00 58	85.53 29	84.78 50	70.91 49	85.64 49	90.41 66	75.55 42	87.69 5	79.75 12	95.08 25	85.36 100
Skip Steuart: Steuart Systems R&D Blog.
APDe-MVS		82.88 28	84.14 19	79.08 56	84.80 79	66.72 97	86.54 23	85.11 43	72.00 43	86.65 36	91.75 32	78.20 23	87.04 11	77.93 30	94.32 53	83.47 162
Zhaojie Zeng, Yuesong Wang, Tao Guan: Matching Ambiguity-Resilient Multi-View Stereo via Adaptive Patch Deformation. Pattern Recognition
GST-MVS		82.79 29	83.27 34	81.34 31	88.99 27	73.29 45	85.94 28	85.13 42	68.58 63	84.14 71	90.21 79	73.37 60	86.41 18	79.09 23	93.98 61	84.30 140

ACMP	69.50 8	82.64 30	83.38 31	80.40 41	86.50 46	69.44 73	82.30 59	86.08 25	66.80 73	86.70 35	89.99 82	81.64 6	85.95 35	74.35 58	96.11 4	85.81 87
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
MP-MVS-pluss		82.54 31	83.46 30	79.76 45	88.88 31	68.44 82	81.57 65	86.33 20	63.17 118	85.38 56	91.26 41	76.33 34	84.67 71	83.30 2	94.96 28	86.17 80
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
ACMMP_NAP		82.33 32	83.28 33	79.46 51	89.28 19	69.09 80	83.62 47	84.98 46	64.77 100	83.97 73	91.02 45	75.53 43	85.93 38	82.00 3	94.36 50	83.35 168

SMA-MVS		82.12 33	82.68 43	80.43 40	88.90 30	69.52 71	85.12 32	84.76 51	63.53 112	84.23 70	91.47 38	72.02 68	87.16 8	79.74 14	94.36 50	84.61 124
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 34	83.31 32	78.49 68	88.17 37	73.96 38	83.11 54	84.52 61	66.40 78	87.45 26	89.16 100	81.02 8	80.52 150	74.27 59	95.73 8	80.98 235
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
DPE-MVS		82.00 35	83.02 38	78.95 61	85.36 69	67.25 92	82.91 55	84.98 46	73.52 29	85.43 55	90.03 81	76.37 33	86.97 13	74.56 54	94.02 60	82.62 195
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
SED-MVS		81.78 36	83.48 29	76.67 90	86.12 54	61.06 148	83.62 47	84.72 53	72.61 36	87.38 28	89.70 87	77.48 27	85.89 42	75.29 47	94.39 46	83.08 177

PMVS	70.70 6	81.70 37	83.15 36	77.36 84	90.35 6	82.82 3	82.15 60	79.22 169	74.08 24	87.16 33	91.97 23	84.80 2	76.97 210	64.98 138	93.61 65	72.28 356
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
UA-Net		81.56 38	82.28 45	79.40 52	88.91 29	69.16 78	84.67 36	80.01 152	75.34 19	79.80 120	94.91 2	69.79 92	80.25 154	72.63 72	94.46 41	88.78 44

CPTT-MVS		81.51 39	81.76 48	80.76 38	89.20 23	78.75 10	86.48 24	82.03 105	68.80 59	80.92 109	88.52 117	72.00 69	82.39 110	74.80 49	93.04 72	81.14 229

DVP-MVS++		81.24 40	82.74 42	76.76 89	83.14 102	60.90 152	91.64 1	85.49 33	74.03 25	84.93 60	90.38 71	66.82 120	85.90 40	77.43 35	90.78 120	83.49 159

ACMH+	66.64 10	81.20 41	82.48 44	77.35 85	81.16 134	62.39 133	80.51 73	87.80 9	73.02 31	87.57 24	91.08 44	80.28 9	82.44 109	64.82 140	96.10 5	87.21 61

DVP-MVS		81.15 42	83.12 37	75.24 113	86.16 52	60.78 154	83.77 45	80.58 140	72.48 38	85.83 47	90.41 66	78.57 19	85.69 47	75.86 43	94.39 46	79.24 270
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 43	81.73 49	79.36 53	84.47 84	70.53 63	83.85 43	83.70 79	69.43 58	83.67 76	88.96 107	75.89 38	86.41 18	72.62 73	92.95 73	81.14 229
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
3Dnovator+	73.19 2	81.08 44	80.48 56	82.87 8	81.41 130	72.03 49	84.38 39	86.23 24	77.28 18	80.65 113	90.18 80	59.80 209	87.58 6	73.06 68	91.34 99	89.01 36

DeepC-MVS	72.44 4	81.00 45	80.83 55	81.50 26	86.70 45	70.03 68	82.06 61	87.00 16	59.89 144	80.91 110	90.53 60	72.19 65	88.56 2	73.67 64	94.52 40	85.92 86
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 46	81.63 51	79.07 57	86.86 44	69.39 74	79.41 91	84.00 77	65.64 83	85.54 53	89.28 93	76.32 35	83.47 90	74.03 61	93.57 67	84.35 137
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
LS3D		80.99 46	80.85 54	81.41 29	78.37 172	71.37 54	87.45 8	85.87 28	77.48 16	81.98 93	89.95 84	69.14 95	85.26 57	66.15 127	91.24 101	87.61 56

SF-MVS		80.72 48	81.80 47	77.48 81	82.03 122	64.40 119	83.41 51	88.46 6	65.28 91	84.29 69	89.18 98	73.73 59	83.22 94	76.01 42	93.77 63	84.81 117

XVG-ACMP-BASELINE		80.54 49	81.06 53	78.98 60	87.01 39	72.91 47	80.23 81	85.56 32	66.56 77	85.64 49	89.57 89	69.12 96	80.55 149	72.51 74	93.37 68	83.48 161

MSP-MVS		80.49 50	79.67 63	82.96 6	89.70 12	77.46 23	87.16 12	85.10 44	64.94 99	81.05 107	88.38 121	57.10 245	87.10 9	79.75 12	83.87 253	84.31 138
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 51	82.91 39	73.11 145	89.83 9	39.02 370	77.06 120	82.61 97	80.04 5	90.60 7	92.85 12	74.93 48	85.21 60	63.15 160	95.15 23	95.09 2

PS-CasMVS		80.41 52	82.86 41	73.07 146	89.93 7	39.21 367	77.15 118	81.28 120	79.74 6	90.87 5	92.73 14	75.03 47	84.93 65	63.83 152	95.19 21	95.07 3

DTE-MVSNet		80.35 53	82.89 40	72.74 164	89.84 8	37.34 387	77.16 117	81.81 109	80.45 4	90.92 4	92.95 10	74.57 51	86.12 31	63.65 153	94.68 37	94.76 6

SD-MVS		80.28 54	81.55 52	76.47 95	83.57 96	67.83 86	83.39 52	85.35 40	64.42 102	86.14 43	87.07 142	74.02 55	80.97 141	77.70 33	92.32 84	80.62 247
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 55	82.17 46	74.39 121	89.46 15	42.69 338	78.24 104	82.24 101	78.21 13	89.57 10	92.10 21	68.05 106	85.59 50	66.04 130	95.62 10	94.88 5

HPM-MVS++		79.89 56	79.80 62	80.18 43	89.02 26	78.44 11	83.49 50	80.18 148	64.71 101	78.11 144	88.39 120	65.46 140	83.14 95	77.64 34	91.20 102	78.94 274

XVG-OURS-SEG-HR		79.62 57	79.99 60	78.49 68	86.46 47	74.79 33	77.15 118	85.39 38	66.73 74	80.39 116	88.85 109	74.43 54	78.33 191	74.73 51	85.79 214	82.35 201

XVG-OURS		79.51 58	79.82 61	78.58 66	86.11 57	74.96 32	76.33 132	84.95 48	66.89 71	82.75 87	88.99 106	66.82 120	78.37 189	74.80 49	90.76 123	82.40 200

CP-MVSNet		79.48 59	81.65 50	72.98 150	89.66 13	39.06 369	76.76 121	80.46 142	78.91 9	90.32 8	91.70 33	68.49 100	84.89 66	63.40 157	95.12 24	95.01 4

OMC-MVS		79.41 60	78.79 68	81.28 33	80.62 138	70.71 62	80.91 70	84.76 51	62.54 123	81.77 96	86.65 159	71.46 72	83.53 88	67.95 110	92.44 80	89.60 24

v7n		79.37 61	80.41 57	76.28 97	78.67 171	55.81 203	79.22 93	82.51 99	70.72 50	87.54 25	92.44 17	68.00 108	81.34 129	72.84 70	91.72 89	91.69 11

TSAR-MVS + MP.		79.05 62	78.81 67	79.74 46	88.94 28	67.52 89	86.61 22	81.38 118	51.71 251	77.15 159	91.42 40	65.49 139	87.20 7	79.44 18	87.17 197	84.51 132
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 63	78.67 70	79.72 47	84.81 78	73.93 39	80.65 72	76.50 212	51.98 249	87.40 27	91.86 29	76.09 37	78.53 181	68.58 101	90.20 129	86.69 71

test_djsdf		78.88 64	78.27 74	80.70 39	81.42 129	71.24 56	83.98 41	75.72 223	52.27 242	87.37 30	92.25 19	68.04 107	80.56 147	72.28 77	91.15 104	90.32 21

HQP_MVS		78.77 65	78.78 69	78.72 63	85.18 70	65.18 111	82.74 56	85.49 33	65.45 86	78.23 141	89.11 101	60.83 193	86.15 29	71.09 82	90.94 112	84.82 115

anonymousdsp		78.60 66	77.80 78	81.00 35	78.01 179	74.34 37	80.09 82	76.12 218	50.51 271	89.19 11	90.88 49	71.45 73	77.78 203	73.38 65	90.60 125	90.90 17

OurMVSNet-221017-0		78.57 67	78.53 72	78.67 64	80.48 139	64.16 120	80.24 80	82.06 104	61.89 127	88.77 16	93.32 6	57.15 243	82.60 106	70.08 92	92.80 75	89.25 30

jajsoiax		78.51 68	78.16 76	79.59 49	84.65 81	73.83 41	80.42 75	76.12 218	51.33 260	87.19 32	91.51 37	73.79 58	78.44 185	68.27 104	90.13 133	86.49 75

CNVR-MVS		78.49 69	78.59 71	78.16 72	85.86 63	67.40 90	78.12 107	81.50 114	63.92 106	77.51 154	86.56 163	68.43 102	84.82 68	73.83 62	91.61 93	82.26 205

DeepPCF-MVS	71.07 5	78.48 70	77.14 87	82.52 17	84.39 87	77.04 25	76.35 130	84.05 75	56.66 180	80.27 117	85.31 191	68.56 99	87.03 12	67.39 117	91.26 100	83.50 158

DP-MVS		78.44 71	79.29 65	75.90 102	81.86 125	65.33 109	79.05 94	84.63 59	74.83 22	80.41 115	86.27 170	71.68 70	83.45 91	62.45 165	92.40 81	78.92 275

NCCC		78.25 72	78.04 77	78.89 62	85.61 65	69.45 72	79.80 88	80.99 130	65.77 82	75.55 196	86.25 172	67.42 113	85.42 52	70.10 91	90.88 118	81.81 218

test_0402		78.17 73	79.48 64	74.24 123	83.50 97	59.15 171	72.52 181	74.60 234	75.34 19	88.69 17	91.81 31	75.06 46	82.37 111	65.10 136	88.68 166	81.20 227

MM		78.15 74	77.68 79	79.55 50	80.10 142	65.47 107	80.94 69	78.74 179	71.22 46	72.40 263	88.70 111	60.51 197	87.70 4	77.40 37	89.13 158	85.48 97

AllTest		77.66 75	77.43 81	78.35 70	79.19 158	70.81 59	78.60 98	88.64 4	65.37 89	80.09 118	88.17 125	70.33 84	78.43 186	55.60 237	90.90 116	85.81 87

PS-MVSNAJss		77.54 76	77.35 85	78.13 74	84.88 76	66.37 99	78.55 99	79.59 161	53.48 232	86.29 40	92.43 18	62.39 168	80.25 154	67.90 111	90.61 124	87.77 53

Elysia		77.52 77	77.43 81	77.78 77	79.01 164	60.26 160	76.55 123	84.34 64	67.82 66	78.73 132	87.94 130	58.68 222	83.79 81	74.70 52	89.10 160	89.28 28

StellarMVS		77.52 77	77.43 81	77.78 77	79.01 164	60.26 160	76.55 123	84.34 64	67.82 66	78.73 132	87.94 130	58.68 222	83.79 81	74.70 52	89.10 160	89.28 28

ACMH	63.62 14	77.50 79	80.11 59	69.68 215	79.61 149	56.28 197	78.81 96	83.62 80	63.41 116	87.14 34	90.23 78	76.11 36	73.32 261	67.58 112	94.44 44	79.44 268
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
CDPH-MVS		77.33 80	77.06 88	78.14 73	84.21 88	63.98 123	76.07 136	83.45 82	54.20 218	77.68 152	87.18 138	69.98 89	85.37 53	68.01 108	92.72 78	85.08 107

DeepC-MVS_fast	69.89 7	77.17 81	76.33 93	79.70 48	83.90 92	67.94 84	80.06 84	83.75 78	56.73 179	74.88 213	85.32 190	65.54 138	87.79 3	65.61 135	91.14 105	83.35 168
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 82	77.39 84	76.14 100	76.86 205	56.87 195	80.32 79	87.52 13	63.45 114	74.66 218	84.52 204	69.87 91	84.94 64	69.76 95	89.59 145	86.60 72

MVSMamba_PlusPlus		76.88 83	78.21 75	72.88 158	80.83 135	48.71 263	83.28 53	82.79 91	72.78 32	79.17 127	91.94 25	56.47 252	83.95 78	70.51 90	86.15 209	85.99 84

X-MVStestdata		76.81 84	74.79 107	82.85 9	89.43 16	77.61 16	86.80 20	84.66 57	72.71 33	82.87 84	9.95 462	73.86 56	86.31 21	78.84 24	94.03 58	84.64 121

UniMVSNet_ETH3D		76.74 85	79.02 66	69.92 213	89.27 20	43.81 325	74.47 159	71.70 264	72.33 41	85.50 54	93.65 4	77.98 24	76.88 214	54.60 254	91.64 91	89.08 34

CS-MVS		76.51 86	76.00 96	78.06 75	77.02 194	64.77 116	80.78 71	82.66 96	60.39 140	74.15 229	83.30 234	69.65 93	82.07 117	69.27 98	86.75 204	87.36 59

train_agg		76.38 87	76.55 91	75.86 103	85.47 67	69.32 76	76.42 128	78.69 180	54.00 223	76.97 161	86.74 153	66.60 125	81.10 135	72.50 75	91.56 94	77.15 301

NormalMVS		76.15 88	75.08 105	79.36 53	83.87 94	70.01 69	79.92 86	84.34 64	58.60 156	75.21 204	84.02 216	52.85 273	81.82 121	61.45 173	95.50 11	86.24 77

TranMVSNet+NR-MVSNet		76.13 89	77.66 80	71.56 183	84.61 82	42.57 340	70.98 213	78.29 189	68.67 62	83.04 80	89.26 94	72.99 62	80.75 146	55.58 240	95.47 13	91.35 12

tt0805		76.12 90	78.43 73	69.20 225	81.32 131	41.37 346	76.72 122	77.64 198	63.78 109	82.06 92	87.88 132	79.78 11	79.05 171	64.33 144	92.40 81	87.17 65

SixPastTwentyTwo		75.77 91	76.34 92	74.06 126	81.69 127	54.84 214	76.47 125	75.49 225	64.10 105	87.73 21	92.24 20	50.45 291	81.30 131	67.41 115	91.46 96	86.04 83

RPSCF		75.76 92	74.37 113	79.93 44	74.81 234	77.53 18	77.53 112	79.30 166	59.44 147	78.88 130	89.80 86	71.26 75	73.09 263	57.45 219	80.89 300	89.17 33

v10		75.69 93	76.20 94	74.16 124	74.44 243	48.69 264	75.84 140	82.93 90	59.02 152	85.92 45	89.17 99	58.56 224	82.74 104	70.73 86	89.14 157	91.05 14

testf1		75.66 94	76.57 89	72.95 151	67.07 366	67.62 87	76.10 134	80.68 135	64.95 97	86.58 37	90.94 47	71.20 76	71.68 287	60.46 184	91.13 106	79.56 264

APD_test2		75.66 94	76.57 89	72.95 151	67.07 366	67.62 87	76.10 134	80.68 135	64.95 97	86.58 37	90.94 47	71.20 76	71.68 287	60.46 184	91.13 106	79.56 264

Anonymous20231211		75.54 96	77.19 86	70.59 196	77.67 185	45.70 309	74.73 153	80.19 147	68.80 59	82.95 83	92.91 11	66.26 129	76.76 216	58.41 209	92.77 76	89.30 27

MVS_0304		75.45 97	74.66 109	77.83 76	75.58 224	61.53 141	78.29 102	77.18 206	63.15 120	69.97 299	87.20 137	57.54 240	87.05 10	74.05 60	88.96 163	84.89 110

Effi-MVS+-dtu		75.43 98	72.28 164	84.91 3	77.05 192	83.58 2	78.47 100	77.70 197	57.68 165	74.89 212	78.13 331	64.80 148	84.26 77	56.46 229	85.32 224	86.88 68

F-COLMAP		75.29 99	73.99 123	79.18 55	81.73 126	71.90 50	81.86 64	82.98 88	59.86 145	72.27 264	84.00 218	64.56 151	83.07 98	51.48 278	87.19 196	82.56 197

casdiffmvs_mvg		75.26 100	76.18 95	72.52 169	72.87 275	49.47 258	72.94 178	84.71 55	59.49 146	80.90 111	88.81 110	70.07 88	79.71 162	67.40 116	88.39 169	88.40 48
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		75.24 101	75.01 106	75.94 101	82.37 116	58.80 178	77.32 114	84.12 73	59.08 148	71.58 275	85.96 184	58.09 231	85.30 55	67.38 119	89.16 154	83.73 154

TAPA-MVS	65.27 12	75.16 102	74.29 116	77.77 79	74.86 233	68.08 83	77.89 108	84.04 76	55.15 196	76.19 189	83.39 228	66.91 118	80.11 158	60.04 193	90.14 132	85.13 104
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
IS-MVSNet		75.10 103	75.42 103	74.15 125	79.23 156	48.05 277	79.43 89	78.04 193	70.09 55	79.17 127	88.02 129	53.04 272	83.60 85	58.05 213	93.76 64	90.79 18

v8		75.07 104	75.64 100	73.35 138	73.42 259	47.46 289	75.20 143	81.45 116	60.05 142	85.64 49	89.26 94	58.08 233	81.80 124	69.71 97	87.97 177	90.79 18

APD_test1		75.04 105	75.38 104	74.02 127	69.89 326	70.15 66	76.46 126	79.71 157	65.50 85	82.99 82	88.60 116	66.94 117	72.35 275	59.77 196	88.54 167	79.56 264

UniMVSNet (Re)		75.00 106	75.48 102	73.56 136	83.14 102	47.92 279	70.41 222	81.04 128	63.67 110	79.54 122	86.37 168	62.83 162	81.82 121	57.10 223	95.25 17	90.94 16

PHI-MVS		74.92 107	74.36 114	76.61 91	76.40 210	62.32 134	80.38 76	83.15 86	54.16 220	73.23 249	80.75 278	62.19 173	83.86 80	68.02 107	90.92 115	83.65 155

DU-MVS		74.91 108	75.57 101	72.93 154	83.50 97	45.79 306	69.47 235	80.14 149	65.22 92	81.74 98	87.08 140	61.82 178	81.07 137	56.21 231	94.98 26	91.93 9

UniMVSNet_NR-MVSNet		74.90 109	75.65 99	72.64 167	83.04 107	45.79 306	69.26 241	78.81 175	66.66 76	81.74 98	86.88 147	63.26 158	81.07 137	56.21 231	94.98 26	91.05 14

SPE-MVS-test		74.89 110	74.23 117	76.86 88	77.01 195	62.94 131	78.98 95	84.61 60	58.62 155	70.17 296	80.80 277	66.74 124	81.96 119	61.74 170	89.40 152	85.69 93

nrg030		74.87 111	75.99 97	71.52 184	74.90 232	49.88 257	74.10 166	82.58 98	54.55 209	83.50 78	89.21 96	71.51 71	75.74 227	61.24 176	92.34 83	88.94 39

Vis-MVSNet		74.85 112	74.56 110	75.72 104	81.63 128	64.64 117	76.35 130	79.06 171	62.85 121	73.33 247	88.41 119	62.54 166	79.59 165	63.94 151	82.92 267	82.94 181
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
fmvsm_s_conf0.5_n_9		74.56 113	74.30 115	75.34 110	77.17 191	64.87 115	72.62 180	76.17 217	54.54 210	78.32 140	86.14 176	65.14 146	75.72 228	73.10 67	85.55 218	85.42 98

MSLP-MVS++		74.48 114	75.78 98	70.59 196	84.66 80	62.40 132	78.65 97	84.24 70	60.55 139	77.71 151	81.98 258	63.12 159	77.64 205	62.95 161	88.14 172	71.73 361

AdaColmap		74.22 115	74.56 110	73.20 142	81.95 123	60.97 150	79.43 89	80.90 131	65.57 84	72.54 261	81.76 263	70.98 79	85.26 57	47.88 317	90.00 134	73.37 340

CSCG		74.12 116	74.39 112	73.33 139	79.35 153	61.66 140	77.45 113	81.98 106	62.47 125	79.06 129	80.19 289	61.83 177	78.79 177	59.83 195	87.35 187	79.54 267

SymmetryMVS		74.00 117	72.85 150	77.43 83	85.17 72	70.01 69	79.92 86	68.48 311	58.60 156	75.21 204	84.02 216	52.85 273	81.82 121	61.45 173	89.99 136	80.47 250

test_fmvsmconf0.01_n		73.91 118	73.64 130	74.71 114	69.79 330	66.25 100	75.90 138	79.90 153	46.03 323	76.48 183	85.02 194	67.96 110	73.97 255	74.47 57	87.22 194	83.90 148

PAPM_NR		73.91 118	74.16 119	73.16 143	81.90 124	53.50 225	81.28 67	81.40 117	66.17 80	73.30 248	83.31 233	59.96 204	83.10 97	58.45 208	81.66 289	82.87 185

EPP-MVSNet		73.86 120	73.38 136	75.31 111	78.19 175	53.35 227	80.45 74	77.32 202	65.11 95	76.47 184	86.80 148	49.47 297	83.77 83	53.89 263	92.72 78	88.81 43

K. test v3		73.67 121	73.61 132	73.87 129	79.78 146	55.62 207	74.69 155	62.04 355	66.16 81	84.76 64	93.23 8	49.47 297	80.97 141	65.66 134	86.67 205	85.02 109

NR-MVSNet		73.62 122	74.05 122	72.33 174	83.50 97	43.71 326	65.65 301	77.32 202	64.32 103	75.59 195	87.08 140	62.45 167	81.34 129	54.90 249	95.63 9	91.93 9

balanced_conf03		73.59 123	74.06 121	72.17 178	77.48 188	47.72 284	81.43 66	82.20 102	54.38 211	79.19 126	87.68 134	54.41 264	83.57 86	63.98 148	85.78 215	85.22 101

DP-MVS Recon		73.57 124	72.69 154	76.23 98	82.85 111	63.39 126	74.32 161	82.96 89	57.75 164	70.35 292	81.98 258	64.34 153	84.41 76	49.69 294	89.95 137	80.89 237

CNLPA		73.44 125	73.03 147	74.66 115	78.27 173	75.29 30	75.99 137	78.49 184	65.39 88	75.67 194	83.22 239	61.23 186	66.77 347	53.70 266	85.33 223	81.92 216

MCST-MVS		73.42 126	73.34 139	73.63 133	81.28 132	59.17 170	74.80 151	83.13 87	45.50 327	72.84 255	83.78 224	65.15 144	80.99 139	64.54 141	89.09 162	80.73 243

v1192		73.40 127	73.42 134	73.32 140	74.65 240	48.67 265	72.21 186	81.73 110	52.76 237	81.85 94	84.56 202	57.12 244	82.24 115	68.58 101	87.33 189	89.06 35

114514_t		73.40 127	73.33 140	73.64 132	84.15 90	57.11 193	78.20 105	80.02 151	43.76 350	72.55 260	86.07 182	64.00 154	83.35 93	60.14 191	91.03 111	80.45 251

FC-MVSNet-test		73.32 129	74.78 108	68.93 235	79.21 157	36.57 389	71.82 200	79.54 163	57.63 169	82.57 89	90.38 71	59.38 213	78.99 173	57.91 214	94.56 39	91.23 13

v1144		73.29 130	73.39 135	73.01 148	74.12 249	48.11 275	72.01 192	81.08 127	53.83 227	81.77 96	84.68 197	58.07 234	81.91 120	68.10 105	86.86 200	88.99 38

test_fmvsmconf0.1_n		73.26 131	72.82 153	74.56 116	69.10 337	66.18 102	74.65 157	79.34 165	45.58 326	75.54 197	83.91 220	67.19 115	73.88 258	73.26 66	86.86 200	83.63 156

GeoE		73.14 132	73.77 128	71.26 188	78.09 177	52.64 230	74.32 161	79.56 162	56.32 183	76.35 187	83.36 232	70.76 81	77.96 199	63.32 158	81.84 283	83.18 173

baseline		73.10 133	73.96 124	70.51 198	71.46 296	46.39 303	72.08 189	84.40 63	55.95 188	76.62 175	86.46 166	67.20 114	78.03 198	64.22 145	87.27 193	87.11 66

h-mvs33		73.08 134	71.61 177	77.48 81	83.89 93	72.89 48	70.47 220	71.12 282	54.28 214	77.89 145	83.41 227	49.04 303	80.98 140	63.62 154	90.77 122	78.58 278

TSAR-MVS + GP.		73.08 134	71.60 178	77.54 80	78.99 167	70.73 61	74.96 146	69.38 298	60.73 138	74.39 225	78.44 325	57.72 238	82.78 103	60.16 189	89.60 144	79.11 272

v1240		73.06 136	73.14 142	72.84 160	74.74 236	47.27 293	71.88 199	81.11 124	51.80 250	82.28 91	84.21 208	56.22 254	82.34 112	68.82 100	87.17 197	88.91 40

casdiffmvs		73.06 136	73.84 125	70.72 194	71.32 298	46.71 298	70.93 214	84.26 69	55.62 191	77.46 156	87.10 139	67.09 116	77.81 201	63.95 149	86.83 202	87.64 55
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
IterMVS-LS		73.01 138	73.12 144	72.66 166	73.79 255	49.90 253	71.63 202	78.44 185	58.22 159	80.51 114	86.63 160	58.15 229	79.62 163	62.51 163	88.20 171	88.48 46
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CANet		73.00 139	71.84 170	76.48 94	75.82 221	61.28 144	74.81 149	80.37 145	63.17 118	62.43 376	80.50 283	61.10 190	85.16 63	64.00 147	84.34 249	83.01 180

v144192		72.99 140	73.06 146	72.77 162	74.58 241	47.48 288	71.90 198	80.44 143	51.57 253	81.46 102	84.11 214	58.04 235	82.12 116	67.98 109	87.47 184	88.70 45

MVS_111021_HR		72.98 141	72.97 149	72.99 149	80.82 136	65.47 107	68.81 250	72.77 253	57.67 166	75.76 192	82.38 250	71.01 78	77.17 208	61.38 175	86.15 209	76.32 313

fmvsm_s_conf0.5_n_3		72.97 142	74.13 120	69.47 219	71.40 297	58.36 184	73.07 175	80.64 137	56.86 175	75.49 199	84.67 198	67.86 111	72.33 276	75.68 45	81.54 291	77.73 294

v1921920		72.96 143	72.98 148	72.89 157	74.67 237	47.58 286	71.92 197	80.69 134	51.70 252	81.69 100	83.89 221	56.58 250	82.25 114	68.34 103	87.36 186	88.82 42

test_fmvsmconf_n		72.91 144	72.40 161	74.46 117	68.62 341	66.12 103	74.21 165	78.80 177	45.64 325	74.62 220	83.25 236	66.80 123	73.86 259	72.97 69	86.66 206	83.39 165

CLD-MVS		72.88 145	72.36 162	74.43 120	77.03 193	54.30 218	68.77 253	83.43 83	52.12 246	76.79 171	74.44 362	69.54 94	83.91 79	55.88 234	93.25 71	85.09 106
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
fmvsm_s_conf0.5_n_8		72.87 146	72.85 150	72.93 154	72.25 285	59.01 175	72.35 183	80.13 150	56.32 183	75.74 193	84.12 212	60.14 202	75.05 239	71.71 80	82.90 268	84.75 118

EI-MVSNet-Vis-set		72.78 147	71.87 168	75.54 108	74.77 235	59.02 174	72.24 185	71.56 268	63.92 106	78.59 135	71.59 384	66.22 130	78.60 180	67.58 112	80.32 312	89.00 37

ETV-MVS		72.72 148	72.16 166	74.38 122	76.90 203	55.95 199	73.34 173	84.67 56	62.04 126	72.19 267	70.81 389	65.90 134	85.24 59	58.64 205	84.96 231	81.95 215

PCF-MVS	63.80 13	72.70 149	71.69 172	75.72 104	78.10 176	60.01 163	73.04 176	81.50 114	45.34 332	79.66 121	84.35 207	65.15 144	82.65 105	48.70 306	89.38 153	84.50 133
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
EI-MVSNet-UG-set		72.63 150	71.68 173	75.47 109	74.67 237	58.64 182	72.02 191	71.50 269	63.53 112	78.58 137	71.39 388	65.98 132	78.53 181	67.30 122	80.18 315	89.23 31

KinetiMVS		72.61 151	72.54 157	72.82 161	71.47 295	55.27 208	68.54 258	76.50 212	61.70 129	74.95 210	86.08 180	59.17 215	76.95 211	69.96 93	84.45 246	86.24 77

Anonymous20240529		72.56 152	73.79 127	68.86 237	76.89 204	45.21 313	68.80 252	77.25 204	67.16 69	76.89 165	90.44 63	65.95 133	74.19 253	50.75 285	90.00 134	87.18 64

FIs		72.56 152	73.80 126	68.84 238	78.74 170	37.74 383	71.02 212	79.83 154	56.12 185	80.88 112	89.45 91	58.18 227	78.28 192	56.63 225	93.36 69	90.51 20

v2v482		72.55 154	72.58 156	72.43 171	72.92 274	46.72 297	71.41 205	79.13 170	55.27 194	81.17 106	85.25 192	55.41 258	81.13 134	67.25 123	85.46 219	89.43 26

SSM_0404		72.51 155	72.15 167	73.60 134	78.20 174	55.86 202	74.41 160	79.83 154	53.69 229	73.98 235	84.18 209	62.26 171	82.50 107	58.21 210	84.60 242	82.43 199

sc_t1		72.50 156	74.23 117	67.33 263	80.05 143	46.99 295	66.58 289	69.48 297	66.28 79	77.62 153	91.83 30	70.98 79	68.62 321	53.86 265	91.40 97	86.37 76

test_fmvsmvis_n_1920		72.36 157	72.49 158	71.96 179	71.29 300	64.06 122	72.79 179	81.82 108	40.23 382	81.25 105	81.04 273	70.62 82	68.69 318	69.74 96	83.60 260	83.14 174

hse-mvs2		72.32 158	70.66 193	77.31 86	83.10 106	71.77 51	69.19 243	71.45 271	54.28 214	77.89 145	78.26 327	49.04 303	79.23 168	63.62 154	89.13 158	80.92 236

sasdasda		72.29 159	73.38 136	69.04 229	74.23 244	47.37 290	73.93 168	83.18 84	54.36 212	76.61 176	81.64 266	72.03 66	75.34 232	57.12 221	87.28 191	84.40 134

canonicalmvs		72.29 159	73.38 136	69.04 229	74.23 244	47.37 290	73.93 168	83.18 84	54.36 212	76.61 176	81.64 266	72.03 66	75.34 232	57.12 221	87.28 191	84.40 134

SSM_0407		72.15 161	71.85 169	73.06 147	76.92 198	55.22 209	73.59 170	79.83 154	53.69 229	73.08 250	84.18 209	62.26 171	81.98 118	58.21 210	84.91 234	81.99 212

Effi-MVS+		72.10 162	72.28 164	71.58 182	74.21 247	50.33 246	74.72 154	82.73 94	62.62 122	70.77 288	76.83 342	69.96 90	80.97 141	60.20 187	78.43 337	83.45 164

MVS_111021_LR		72.10 162	71.82 171	72.95 151	79.53 151	73.90 40	70.45 221	66.64 320	56.87 174	76.81 170	81.76 263	68.78 97	71.76 285	61.81 168	83.74 256	73.18 342

fmvsm_l_conf0.5_n_3		71.98 164	71.68 173	72.88 158	72.84 276	64.15 121	73.48 171	77.11 207	48.97 296	71.31 283	84.18 209	67.98 109	71.60 289	68.86 99	80.43 311	82.89 183

pmmvs6		71.82 165	73.66 129	66.31 279	75.94 219	42.01 342	66.99 281	72.53 257	63.45 114	76.43 185	92.78 13	72.95 63	69.69 310	51.41 280	90.46 126	87.22 60

PLC	62.01 16	71.79 166	70.28 196	76.33 96	80.31 141	68.63 81	78.18 106	81.24 121	54.57 208	67.09 340	80.63 281	59.44 211	81.74 126	46.91 324	84.17 250	78.63 276
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
MGCFI-Net		71.70 167	73.10 145	67.49 260	73.23 263	43.08 334	72.06 190	82.43 100	54.58 207	75.97 191	82.00 256	72.42 64	75.22 234	57.84 215	87.34 188	84.18 141

BP-MVS1		71.60 168	70.06 197	76.20 99	74.07 250	55.22 209	74.29 163	73.44 241	57.29 171	73.87 238	84.65 199	32.57 393	83.49 89	72.43 76	87.94 178	89.89 23

VDDNet		71.60 168	73.13 143	67.02 271	86.29 48	41.11 348	69.97 228	66.50 321	68.72 61	74.74 214	91.70 33	59.90 206	75.81 224	48.58 308	91.72 89	84.15 143

tt0320-xc		71.50 170	73.63 131	65.08 289	79.77 147	40.46 360	64.80 316	68.86 305	67.08 70	76.84 169	93.24 7	70.33 84	66.77 347	49.76 293	92.02 87	88.02 51

3Dnovator	65.95 11	71.50 170	71.22 183	72.34 173	73.16 264	63.09 129	78.37 101	78.32 187	57.67 166	72.22 266	84.61 201	54.77 260	78.47 183	60.82 182	81.07 299	75.45 319

fmvsm_s_conf0.5_n_5		71.46 172	71.62 176	70.99 192	73.89 254	59.95 164	73.02 177	73.08 243	45.15 338	77.30 158	84.06 215	64.73 150	70.08 305	71.20 81	82.10 278	82.92 182

viewmacassd2359aftdt		71.41 173	72.29 163	68.78 239	71.32 298	44.81 316	70.11 225	81.51 113	52.64 239	74.95 210	86.79 149	66.02 131	74.50 247	62.43 166	84.86 237	87.03 67

tt0320		71.34 174	73.47 133	64.97 291	79.92 145	40.81 353	65.22 308	69.07 302	66.72 75	76.15 190	93.36 5	70.35 83	66.90 340	49.31 301	91.09 109	87.21 61

FA-MVS(test-final)		71.27 175	71.06 185	71.92 180	73.96 251	52.32 232	76.45 127	76.12 218	59.07 151	74.04 234	86.18 173	52.18 278	79.43 167	59.75 197	81.76 284	84.03 145

WR-MVS		71.20 176	72.48 159	67.36 262	84.98 75	35.70 397	64.43 324	68.66 309	65.05 96	81.49 101	86.43 167	57.57 239	76.48 218	50.36 289	93.32 70	89.90 22

LuminaMVS		71.15 177	70.79 190	72.24 177	77.20 190	58.34 185	72.18 187	76.20 216	54.91 198	77.74 149	81.93 260	49.17 302	76.31 220	62.12 167	85.66 217	82.07 209

V42		71.06 178	70.83 188	71.72 181	67.25 362	47.14 294	65.94 295	80.35 146	51.35 259	83.40 79	83.23 237	59.25 214	78.80 176	65.91 131	80.81 303	89.23 31

FMVSNet1		71.06 178	72.48 159	66.81 273	77.65 186	40.68 356	71.96 194	73.03 244	61.14 132	79.45 124	90.36 74	60.44 198	75.20 236	50.20 290	88.05 174	84.54 128

dcpmvs_2		71.02 180	72.65 155	66.16 280	76.06 218	50.49 244	71.97 193	79.36 164	50.34 272	82.81 86	83.63 225	64.38 152	67.27 336	61.54 172	83.71 258	80.71 245

API-MVS		70.97 181	71.51 180	69.37 220	75.20 227	55.94 200	80.99 68	76.84 209	62.48 124	71.24 284	77.51 337	61.51 182	80.96 144	52.04 274	85.76 216	71.22 367

GDP-MVS		70.84 182	69.24 210	75.62 106	76.44 209	55.65 205	74.62 158	82.78 93	49.63 282	72.10 268	83.79 223	31.86 401	82.84 102	64.93 139	87.01 199	88.39 49

VDD-MVS		70.81 183	71.44 181	68.91 236	79.07 163	46.51 300	67.82 268	70.83 286	61.23 131	74.07 232	88.69 112	59.86 207	75.62 229	51.11 282	90.28 128	84.61 124

fmvsm_l_conf0.5_n_9		70.73 184	71.08 184	69.67 216	70.44 314	58.80 178	70.21 224	75.11 230	48.15 304	73.50 243	82.69 246	65.69 136	68.05 328	70.87 85	83.02 266	82.16 206

EG-PatchMatch MVS		70.70 185	70.88 187	70.16 207	82.64 115	58.80 178	71.48 203	73.64 239	54.98 197	76.55 179	81.77 262	61.10 190	78.94 174	54.87 250	80.84 302	72.74 350

Baseline_NR-MVSNet		70.62 186	73.19 141	62.92 314	76.97 196	34.44 405	68.84 247	70.88 285	60.25 141	79.50 123	90.53 60	61.82 178	69.11 315	54.67 253	95.27 16	85.22 101

alignmvs		70.54 187	71.00 186	69.15 227	73.50 257	48.04 278	69.85 231	79.62 158	53.94 226	76.54 180	82.00 256	59.00 217	74.68 244	57.32 220	87.21 195	84.72 119

MG-MVS		70.47 188	71.34 182	67.85 254	79.26 155	40.42 361	74.67 156	75.15 229	58.41 158	68.74 323	88.14 128	56.08 255	83.69 84	59.90 194	81.71 288	79.43 269

RRT-MVS		70.33 189	70.73 191	69.14 228	71.93 290	45.24 312	75.10 144	75.08 231	60.85 137	78.62 134	87.36 136	49.54 296	78.64 179	60.16 189	77.90 345	83.55 157

mamba_0408		70.32 190	69.35 206	73.24 141	76.92 198	55.22 209	56.61 383	79.27 167	52.14 244	73.08 250	83.14 240	60.53 195	82.50 107	57.51 217	84.91 234	81.99 212

viewmanbaseed2359cas		70.24 191	70.83 188	68.48 244	69.99 325	44.55 320	69.48 234	81.01 129	50.87 265	73.61 240	84.84 196	64.00 154	74.31 251	60.24 186	83.43 262	86.56 73

AUN-MVS		70.22 192	67.88 237	77.22 87	82.96 110	71.61 52	69.08 244	71.39 272	49.17 290	71.70 271	78.07 332	37.62 372	79.21 169	61.81 168	89.15 156	80.82 239

UGNet		70.20 193	69.05 213	73.65 131	76.24 212	63.64 124	75.87 139	72.53 257	61.48 130	60.93 387	86.14 176	52.37 277	77.12 209	50.67 286	85.21 225	80.17 258
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
fmvsm_s_conf0.5_n_4		70.18 194	69.83 202	71.24 189	71.65 292	58.59 183	69.29 240	71.66 265	48.69 298	71.62 272	82.11 254	59.94 205	70.03 306	74.52 55	78.96 330	85.10 105

fmvsm_s_conf0.5_n_6		70.08 195	69.97 198	70.39 199	72.99 273	58.93 176	68.84 247	76.40 214	49.08 292	68.75 322	81.65 265	57.34 241	71.97 282	70.91 84	83.81 255	80.26 255

PVSNet_Blended_VisFu		70.04 196	68.88 216	73.53 137	82.71 113	63.62 125	74.81 149	81.95 107	48.53 300	67.16 339	79.18 316	51.42 284	78.38 188	54.39 258	79.72 324	78.60 277

Fast-Effi-MVS+-dtu		70.00 197	68.74 220	73.77 130	73.47 258	64.53 118	71.36 206	78.14 192	55.81 190	68.84 320	74.71 359	65.36 141	75.75 226	52.00 275	79.00 329	81.03 232

DPM-MVS		69.98 198	69.22 212	72.26 175	82.69 114	58.82 177	70.53 219	81.23 122	47.79 310	64.16 357	80.21 287	51.32 285	83.12 96	60.14 191	84.95 232	74.83 325

MVSFormer		69.93 199	69.03 214	72.63 168	74.93 230	59.19 168	83.98 41	75.72 223	52.27 242	63.53 370	76.74 343	43.19 335	80.56 147	72.28 77	78.67 334	78.14 287

MVS_Test		69.84 200	70.71 192	67.24 265	67.49 360	43.25 333	69.87 230	81.22 123	52.69 238	71.57 278	86.68 156	62.09 174	74.51 246	66.05 129	78.74 332	83.96 146

c3_l		69.82 201	69.89 200	69.61 217	66.24 373	43.48 329	68.12 265	79.61 160	51.43 255	77.72 150	80.18 290	54.61 263	78.15 197	63.62 154	87.50 183	87.20 63

test_fmvsm_n_1920		69.63 202	68.45 224	73.16 143	70.56 310	65.86 105	70.26 223	78.35 186	37.69 399	74.29 227	78.89 321	61.10 190	68.10 326	65.87 132	79.07 328	85.53 96

TransMVSNet (Re)		69.62 203	71.63 175	63.57 303	76.51 208	35.93 395	65.75 300	71.29 276	61.05 133	75.02 208	89.90 85	65.88 135	70.41 303	49.79 292	89.48 148	84.38 136

EI-MVSNet		69.61 204	69.01 215	71.41 186	73.94 252	49.90 253	71.31 208	71.32 274	58.22 159	75.40 201	70.44 391	58.16 228	75.85 222	62.51 163	79.81 321	88.48 46

Gipuma		69.55 205	72.83 152	59.70 343	63.63 396	53.97 221	80.08 83	75.93 221	64.24 104	73.49 244	88.93 108	57.89 237	62.46 369	59.75 197	91.55 95	62.67 424
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
tttt0517		69.46 206	67.79 239	74.46 117	75.34 225	52.72 229	75.05 145	63.27 348	54.69 204	78.87 131	84.37 206	26.63 428	81.15 133	63.95 149	87.93 179	89.51 25

eth_miper_zixun_eth		69.42 207	68.73 221	71.50 185	67.99 351	46.42 301	67.58 270	78.81 175	50.72 268	78.13 143	80.34 286	50.15 293	80.34 152	60.18 188	84.65 240	87.74 54

BH-untuned		69.39 208	69.46 204	69.18 226	77.96 180	56.88 194	68.47 261	77.53 199	56.77 177	77.79 148	79.63 300	60.30 201	80.20 157	46.04 332	80.65 307	70.47 374

v148		69.38 209	69.39 205	69.36 221	69.14 336	44.56 319	68.83 249	72.70 255	54.79 202	78.59 135	84.12 212	54.69 261	76.74 217	59.40 200	82.20 276	86.79 69

viewmsd2359difaftdt		69.22 210	69.68 203	67.83 256	68.17 349	46.57 299	66.42 291	68.93 304	50.60 270	77.48 155	83.94 219	68.16 104	73.84 260	58.49 207	84.92 233	83.10 175

PAPR		69.20 211	68.66 222	70.82 193	75.15 229	47.77 282	75.31 142	81.11 124	49.62 284	66.33 342	79.27 313	61.53 181	82.96 99	48.12 314	81.50 293	81.74 222

QAPM		69.18 212	69.26 209	68.94 234	71.61 293	52.58 231	80.37 77	78.79 178	49.63 282	73.51 242	85.14 193	53.66 268	79.12 170	55.11 243	75.54 363	75.11 324

fmvsm_s_conf0.1_n_2		69.14 213	68.42 225	71.28 187	68.30 346	57.60 191	65.06 311	69.91 292	48.24 301	74.56 222	82.84 242	55.55 257	69.73 308	70.66 88	80.69 306	86.52 74

LCM-MVSNet-Re		69.10 214	71.57 179	61.70 323	70.37 316	34.30 407	61.45 345	79.62 158	56.81 176	89.59 9	88.16 127	68.44 101	72.94 264	42.30 352	87.33 189	77.85 293

EPNet		69.10 214	67.32 245	74.46 117	68.33 345	61.27 145	77.56 110	63.57 345	60.95 135	56.62 411	82.75 243	51.53 283	81.24 132	54.36 259	90.20 129	80.88 238
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
fmvsm_s_conf0.5_n_2		68.93 216	68.23 230	71.02 191	67.78 355	57.58 192	64.74 318	69.56 296	48.16 303	74.38 226	82.32 251	56.00 256	69.68 311	70.65 89	80.52 310	85.80 91

mvsmamba		68.87 217	67.30 247	73.57 135	76.58 207	53.70 224	84.43 38	74.25 236	45.38 331	76.63 174	84.55 203	35.85 379	85.27 56	49.54 297	78.49 336	81.75 221

DELS-MVS		68.83 218	68.31 226	70.38 200	70.55 312	48.31 271	63.78 331	82.13 103	54.00 223	68.96 311	75.17 355	58.95 218	80.06 159	58.55 206	82.74 271	82.76 188
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+		68.81 219	68.30 227	70.35 202	74.66 239	48.61 270	66.06 294	78.32 187	50.62 269	71.48 281	75.54 350	68.75 98	79.59 165	50.55 288	78.73 333	82.86 186

mmtdpeth		68.76 220	70.55 194	63.40 307	67.06 368	56.26 198	68.73 255	71.22 280	55.47 193	70.09 297	88.64 115	65.29 143	56.89 393	58.94 203	89.50 147	77.04 306

OpenMVS	62.51 15	68.76 220	68.75 219	68.78 239	70.56 310	53.91 222	78.29 102	77.35 201	48.85 297	70.22 294	83.52 226	52.65 276	76.93 212	55.31 241	81.99 279	75.49 318

VPA-MVSNet		68.71 222	70.37 195	63.72 301	76.13 214	38.06 381	64.10 327	71.48 270	56.60 182	74.10 231	88.31 122	64.78 149	69.72 309	47.69 319	90.15 131	83.37 167

BH-RMVSNet		68.69 223	68.20 232	70.14 208	76.40 210	53.90 223	64.62 321	73.48 240	58.01 161	73.91 237	81.78 261	59.09 216	78.22 193	48.59 307	77.96 344	78.31 282

EIA-MVS		68.59 224	67.16 248	72.90 156	75.18 228	55.64 206	69.39 236	81.29 119	52.44 241	64.53 353	70.69 390	60.33 200	82.30 113	54.27 260	76.31 357	80.75 242

pm-mvs1		68.40 225	69.85 201	64.04 299	73.10 268	39.94 364	64.61 322	70.50 288	55.52 192	73.97 236	89.33 92	63.91 156	68.38 323	49.68 295	88.02 175	83.81 150

miper_ehance_all_eth		68.36 226	68.16 233	68.98 232	65.14 385	43.34 331	67.07 280	78.92 174	49.11 291	76.21 188	77.72 334	53.48 269	77.92 200	61.16 178	84.59 243	85.68 94

GBi-Net		68.30 227	68.79 217	66.81 273	73.14 265	40.68 356	71.96 194	73.03 244	54.81 199	74.72 215	90.36 74	48.63 309	75.20 236	47.12 321	85.37 220	84.54 128

test1		68.30 227	68.79 217	66.81 273	73.14 265	40.68 356	71.96 194	73.03 244	54.81 199	74.72 215	90.36 74	48.63 309	75.20 236	47.12 321	85.37 220	84.54 128

FE-MVS		68.29 229	66.96 253	72.26 175	74.16 248	54.24 219	77.55 111	73.42 242	57.65 168	72.66 258	84.91 195	32.02 400	81.49 128	48.43 310	81.85 282	81.04 231

diffmvs_AUTHOR		68.27 230	68.59 223	67.32 264	63.76 394	45.37 310	65.31 306	77.19 205	49.25 288	72.68 257	82.19 253	59.62 210	71.17 292	65.75 133	81.53 292	85.42 98

DIV-MVS_self_test		68.27 230	68.26 228	68.29 248	64.98 386	43.67 327	65.89 296	74.67 232	50.04 278	76.86 167	82.43 248	48.74 307	75.38 230	60.94 180	89.81 140	85.81 87

cl____		68.26 232	68.26 228	68.29 248	64.98 386	43.67 327	65.89 296	74.67 232	50.04 278	76.86 167	82.42 249	48.74 307	75.38 230	60.92 181	89.81 140	85.80 91

TinyColmap		67.98 233	69.28 208	64.08 297	67.98 352	46.82 296	70.04 226	75.26 227	53.05 234	77.36 157	86.79 149	59.39 212	72.59 271	45.64 335	88.01 176	72.83 348

xiu_mvs_v1_base_debu		67.87 234	67.07 250	70.26 203	79.13 160	61.90 137	67.34 274	71.25 277	47.98 306	67.70 332	74.19 367	61.31 183	72.62 268	56.51 226	78.26 340	76.27 314

xiu_mvs_v1_base		67.87 234	67.07 250	70.26 203	79.13 160	61.90 137	67.34 274	71.25 277	47.98 306	67.70 332	74.19 367	61.31 183	72.62 268	56.51 226	78.26 340	76.27 314

xiu_mvs_v1_base_debi		67.87 234	67.07 250	70.26 203	79.13 160	61.90 137	67.34 274	71.25 277	47.98 306	67.70 332	74.19 367	61.31 183	72.62 268	56.51 226	78.26 340	76.27 314

MAR-MVS		67.72 237	66.16 262	72.40 172	74.45 242	64.99 114	74.87 147	77.50 200	48.67 299	65.78 346	68.58 416	57.01 247	77.79 202	46.68 327	81.92 280	74.42 333
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		67.68 238	66.07 264	72.49 170	73.34 261	58.20 188	63.80 330	65.55 329	48.10 305	76.91 164	82.64 247	45.20 322	78.84 175	61.20 177	77.89 346	80.44 252

LF4IMVS		67.50 239	67.31 246	68.08 251	58.86 425	61.93 136	71.43 204	75.90 222	44.67 343	72.42 262	80.20 288	57.16 242	70.44 301	58.99 202	86.12 211	71.88 359

fmvsm_l_conf0.5_n		67.48 240	66.88 256	69.28 224	67.41 361	62.04 135	70.69 218	69.85 293	39.46 385	69.59 304	81.09 272	58.15 229	68.73 317	67.51 114	78.16 343	77.07 305

FMVSNet2		67.48 240	68.21 231	65.29 286	73.14 265	38.94 371	68.81 250	71.21 281	54.81 199	76.73 172	86.48 165	48.63 309	74.60 245	47.98 316	86.11 212	82.35 201

MSDG		67.47 242	67.48 243	67.46 261	70.70 306	54.69 216	66.90 284	78.17 190	60.88 136	70.41 291	74.76 357	61.22 188	73.18 262	47.38 320	76.87 353	74.49 331

diffmvs		67.42 243	67.50 242	67.20 266	62.26 402	45.21 313	64.87 314	77.04 208	48.21 302	71.74 270	79.70 298	58.40 226	71.17 292	64.99 137	80.27 313	85.22 101
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		67.37 244	66.36 260	70.37 201	70.86 302	61.17 146	74.00 167	57.18 374	40.77 377	68.83 321	80.88 275	63.11 160	67.61 332	66.94 124	74.72 370	82.33 204

fmvsm_s_conf0.5_n_7		67.30 245	66.92 254	68.43 245	72.78 277	58.22 187	60.90 351	72.51 259	49.62 284	63.66 367	80.65 280	58.56 224	68.63 320	62.83 162	80.76 304	78.45 280

IMVS_0407		67.26 246	67.35 244	66.97 272	72.47 279	48.64 266	69.03 245	72.98 247	45.33 333	68.91 316	79.37 308	61.91 175	75.77 225	55.06 244	81.11 295	76.49 307

SSM_04072		67.23 247	69.35 206	60.89 335	76.92 198	55.22 209	56.61 383	79.27 167	52.14 244	73.08 250	83.14 240	60.53 195	45.46 430	57.51 217	84.91 234	81.99 212

cl22		67.14 248	66.51 259	69.03 231	63.20 397	43.46 330	66.88 285	76.25 215	49.22 289	74.48 223	77.88 333	45.49 321	77.40 207	60.64 183	84.59 243	86.24 77

AstraMVS		67.11 249	66.84 257	67.92 252	70.75 305	51.36 236	64.77 317	67.06 318	49.03 294	75.40 201	82.05 255	51.26 286	70.65 297	58.89 204	82.32 275	81.77 220

ANet_high		67.08 250	69.94 199	58.51 355	57.55 431	27.09 439	58.43 372	76.80 210	63.56 111	82.40 90	91.93 26	59.82 208	64.98 360	50.10 291	88.86 165	83.46 163

IMVS_0403		67.07 251	67.08 249	67.03 270	72.47 279	48.64 266	68.44 262	72.98 247	45.33 333	68.63 324	79.37 308	60.38 199	75.97 221	55.06 244	81.11 295	76.49 307

LFMVS		67.06 252	67.89 236	64.56 293	78.02 178	38.25 378	70.81 217	59.60 362	65.18 93	71.06 286	86.56 163	43.85 331	75.22 234	46.35 329	89.63 143	80.21 257

thisisatest0530		67.05 253	65.16 276	72.73 165	73.10 268	50.55 243	71.26 210	63.91 343	50.22 275	74.46 224	80.75 278	26.81 427	80.25 154	59.43 199	86.50 207	87.37 58

fmvsm_s_conf0.5_n_a		67.00 254	65.95 268	70.17 206	69.72 331	61.16 147	73.34 173	56.83 377	40.96 374	68.36 326	80.08 292	62.84 161	67.57 333	66.90 126	74.50 374	81.78 219

guyue		66.95 255	66.74 258	67.56 259	70.12 324	51.14 238	65.05 312	68.68 308	49.98 280	74.64 219	80.83 276	50.77 288	70.34 304	57.72 216	82.89 269	81.21 226

fmvsm_l_conf0.5_n_a		66.66 256	65.97 267	68.72 241	67.09 364	61.38 143	70.03 227	69.15 301	38.59 393	68.41 325	80.36 285	56.56 251	68.32 324	66.10 128	77.45 349	76.46 311

fmvsm_s_conf0.1_n		66.60 257	65.54 270	69.77 214	68.99 338	59.15 171	72.12 188	56.74 379	40.72 379	68.25 329	80.14 291	61.18 189	66.92 339	67.34 121	74.40 375	83.23 172

MIMVSNet1		66.57 258	69.23 211	58.59 354	81.26 133	37.73 384	64.06 328	57.62 367	57.02 173	78.40 139	90.75 53	62.65 163	58.10 390	41.77 358	89.58 146	79.95 259

tfpnnormal		66.48 259	67.93 235	62.16 320	73.40 260	36.65 388	63.45 333	64.99 333	55.97 187	72.82 256	87.80 133	57.06 246	69.10 316	48.31 312	87.54 181	80.72 244

KD-MVS_self_test		66.38 260	67.51 241	62.97 312	61.76 404	34.39 406	58.11 375	75.30 226	50.84 267	77.12 160	85.42 189	56.84 248	69.44 312	51.07 283	91.16 103	85.08 107

SDMVSNet		66.36 261	67.85 238	61.88 322	73.04 271	46.14 305	58.54 370	71.36 273	51.42 256	68.93 314	82.72 244	65.62 137	62.22 372	54.41 257	84.67 238	77.28 297

mvs5depth		66.35 262	67.98 234	61.47 327	62.43 400	51.05 239	69.38 237	69.24 300	56.74 178	73.62 239	89.06 104	46.96 316	58.63 386	55.87 235	88.49 168	74.73 327

fmvsm_s_conf0.5_n		66.34 263	65.27 273	69.57 218	68.20 347	59.14 173	71.66 201	56.48 380	40.92 375	67.78 331	79.46 303	61.23 186	66.90 340	67.39 117	74.32 378	82.66 194

Anonymous202405211		66.02 264	66.89 255	63.43 306	74.22 246	38.14 379	59.00 365	66.13 323	63.33 117	69.76 303	85.95 185	51.88 279	70.50 300	44.23 343	87.52 182	81.64 223

VortexMVS		65.93 265	66.04 266	65.58 285	67.63 359	47.55 287	64.81 315	72.75 254	47.37 314	75.17 206	79.62 301	49.28 300	71.00 294	55.20 242	82.51 273	78.21 285

miper_enhance_ethall		65.86 266	65.05 284	68.28 250	61.62 406	42.62 339	64.74 318	77.97 194	42.52 361	73.42 246	72.79 377	49.66 295	77.68 204	58.12 212	84.59 243	84.54 128

RPMNet		65.77 267	65.08 283	67.84 255	66.37 370	48.24 273	70.93 214	86.27 21	54.66 205	61.35 381	86.77 152	33.29 387	85.67 49	55.93 233	70.17 408	69.62 383

viewmambaseed2359dif		65.63 268	65.13 279	67.11 269	64.57 389	44.73 318	64.12 326	72.48 260	43.08 360	71.59 273	81.17 270	58.90 219	72.46 272	52.94 272	77.33 350	84.13 144

VPNet		65.58 269	67.56 240	59.65 344	79.72 148	30.17 428	60.27 357	62.14 351	54.19 219	71.24 284	86.63 160	58.80 220	67.62 331	44.17 344	90.87 119	81.18 228

PVSNet_BlendedMVS		65.38 270	64.30 285	68.61 242	69.81 327	49.36 259	65.60 303	78.96 172	45.50 327	59.98 390	78.61 323	51.82 280	78.20 194	44.30 341	84.11 251	78.27 283

TAMVS		65.31 271	63.75 291	69.97 212	82.23 120	59.76 166	66.78 286	63.37 347	45.20 337	69.79 302	79.37 308	47.42 315	72.17 277	34.48 409	85.15 227	77.99 291

test_yl		65.11 272	65.09 281	65.18 287	70.59 308	40.86 351	63.22 338	72.79 251	57.91 162	68.88 318	79.07 319	42.85 338	74.89 241	45.50 337	84.97 228	79.81 260

DCV-MVSNet		65.11 272	65.09 281	65.18 287	70.59 308	40.86 351	63.22 338	72.79 251	57.91 162	68.88 318	79.07 319	42.85 338	74.89 241	45.50 337	84.97 228	79.81 260

mvs_anonymous		65.08 274	65.49 271	63.83 300	63.79 393	37.60 385	66.52 290	69.82 294	43.44 355	73.46 245	86.08 180	58.79 221	71.75 286	51.90 276	75.63 362	82.15 207

FMVSNet3		65.00 275	65.16 276	64.52 294	69.47 332	37.56 386	66.63 287	70.38 289	51.55 254	74.72 215	83.27 235	37.89 370	74.44 248	47.12 321	85.37 220	81.57 224

ECVR-MVS		64.82 276	65.22 274	63.60 302	78.80 168	31.14 423	66.97 282	56.47 381	54.23 216	69.94 300	88.68 113	37.23 373	74.81 243	45.28 340	89.41 150	84.86 113

BH-w/o		64.81 277	64.29 286	66.36 278	76.08 217	54.71 215	65.61 302	75.23 228	50.10 277	71.05 287	71.86 383	54.33 265	79.02 172	38.20 381	76.14 358	65.36 410

EGC-MVSNET		64.77 278	61.17 315	75.60 107	86.90 43	74.47 34	84.04 40	68.62 310	0.60 464	1.13 466	91.61 36	65.32 142	74.15 254	64.01 146	88.28 170	78.17 286

test1111		64.62 279	65.19 275	62.93 313	79.01 164	29.91 429	65.45 304	54.41 391	54.09 221	71.47 282	88.48 118	37.02 374	74.29 252	46.83 326	89.94 138	84.58 127

cascas		64.59 280	62.77 305	70.05 210	75.27 226	50.02 250	61.79 344	71.61 266	42.46 362	63.68 366	68.89 412	49.33 299	80.35 151	47.82 318	84.05 252	79.78 262

TR-MVS		64.59 280	63.54 294	67.73 258	75.75 223	50.83 242	63.39 334	70.29 290	49.33 287	71.55 279	74.55 360	50.94 287	78.46 184	40.43 366	75.69 361	73.89 337

PM-MVS		64.49 282	63.61 293	67.14 268	76.68 206	75.15 31	68.49 260	42.85 443	51.17 263	77.85 147	80.51 282	45.76 318	66.31 351	52.83 273	76.35 356	59.96 433

jason		64.47 283	62.84 303	69.34 223	76.91 201	59.20 167	67.15 279	65.67 326	35.29 413	65.16 350	76.74 343	44.67 326	70.68 296	54.74 252	79.28 327	78.14 287
jason: jason.
xiu_mvs_v2_base		64.43 284	63.96 289	65.85 284	77.72 184	51.32 237	63.63 332	72.31 262	45.06 341	61.70 378	69.66 403	62.56 164	73.93 257	49.06 303	73.91 380	72.31 355

pmmvs-eth3d		64.41 285	63.27 298	67.82 257	75.81 222	60.18 162	69.49 233	62.05 354	38.81 392	74.13 230	82.23 252	43.76 332	68.65 319	42.53 351	80.63 309	74.63 328

CDS-MVSNet		64.33 286	62.66 306	69.35 222	80.44 140	58.28 186	65.26 307	65.66 327	44.36 345	67.30 338	75.54 350	43.27 334	71.77 284	37.68 385	84.44 247	78.01 290
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
PS-MVSNAJ		64.27 287	63.73 292	65.90 283	77.82 182	51.42 235	63.33 335	72.33 261	45.09 340	61.60 379	68.04 418	62.39 168	73.95 256	49.07 302	73.87 381	72.34 354

ab-mvs		64.11 288	65.13 279	61.05 332	71.99 289	38.03 382	67.59 269	68.79 307	49.08 292	65.32 349	86.26 171	58.02 236	66.85 345	39.33 370	79.79 323	78.27 283

CANet_DTU		64.04 289	63.83 290	64.66 292	68.39 342	42.97 336	73.45 172	74.50 235	52.05 248	54.78 422	75.44 353	43.99 330	70.42 302	53.49 268	78.41 338	80.59 248

VNet		64.01 290	65.15 278	60.57 338	73.28 262	35.61 398	57.60 377	67.08 317	54.61 206	66.76 341	83.37 230	56.28 253	66.87 343	42.19 354	85.20 226	79.23 271

icg_test_0407_2		63.88 291	65.59 269	58.75 352	72.47 279	48.64 266	53.19 407	72.98 247	45.33 333	68.91 316	79.37 308	61.91 175	51.11 408	55.06 244	81.11 295	76.49 307

sd_testset		63.55 292	65.38 272	58.07 357	73.04 271	38.83 373	57.41 378	65.44 330	51.42 256	68.93 314	82.72 244	63.76 157	58.11 389	41.05 362	84.67 238	77.28 297

Anonymous20240521		63.55 292	66.07 264	55.99 369	66.18 375	44.04 324	68.77 253	68.80 306	46.99 316	72.57 259	85.84 186	39.87 356	50.22 412	53.40 271	92.23 85	73.71 339

lupinMVS		63.36 294	61.49 313	68.97 233	74.93 230	59.19 168	65.80 299	64.52 339	34.68 419	63.53 370	74.25 365	43.19 335	70.62 298	53.88 264	78.67 334	77.10 302

ET-MVSNet_ETH3D		63.32 295	60.69 321	71.20 190	70.15 322	55.66 204	65.02 313	64.32 340	43.28 359	68.99 310	72.05 382	25.46 434	78.19 196	54.16 262	82.80 270	79.74 263

MVSTER		63.29 296	61.60 312	68.36 246	59.77 420	46.21 304	60.62 354	71.32 274	41.83 365	75.40 201	79.12 317	30.25 416	75.85 222	56.30 230	79.81 321	83.03 179

OpenMVS_ROB	54.93 17	63.23 297	63.28 297	63.07 310	69.81 327	45.34 311	68.52 259	67.14 316	43.74 351	70.61 290	79.22 314	47.90 313	72.66 267	48.75 305	73.84 382	71.21 368

IterMVS		63.12 298	62.48 307	65.02 290	66.34 372	52.86 228	63.81 329	62.25 350	46.57 319	71.51 280	80.40 284	44.60 327	66.82 346	51.38 281	75.47 364	75.38 321
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
HyFIR lowres test		63.01 299	60.47 322	70.61 195	83.04 107	54.10 220	59.93 360	72.24 263	33.67 424	69.00 309	75.63 349	38.69 364	76.93 212	36.60 395	75.45 365	80.81 241

GA-MVS		62.91 300	61.66 309	66.66 277	67.09 364	44.49 321	61.18 349	69.36 299	51.33 260	69.33 307	74.47 361	36.83 375	74.94 240	50.60 287	74.72 370	80.57 249

PVSNet_Blended		62.90 301	61.64 310	66.69 276	69.81 327	49.36 259	61.23 348	78.96 172	42.04 363	59.98 390	68.86 413	51.82 280	78.20 194	44.30 341	77.77 347	72.52 351

USDC		62.80 302	63.10 300	61.89 321	65.19 382	43.30 332	67.42 273	74.20 237	35.80 412	72.25 265	84.48 205	45.67 319	71.95 283	37.95 383	84.97 228	70.42 376

MonoMVSNet		62.75 303	63.42 295	60.73 337	65.60 379	40.77 354	72.49 182	70.56 287	52.49 240	75.07 207	79.42 305	39.52 360	69.97 307	46.59 328	69.06 414	71.44 363

Vis-MVSNet (Re-imp)		62.74 304	63.21 299	61.34 330	72.19 287	31.56 420	67.31 278	53.87 393	53.60 231	69.88 301	83.37 230	40.52 352	70.98 295	41.40 360	86.78 203	81.48 225

patch_mono-2		62.73 305	64.08 288	58.68 353	70.36 317	55.87 201	60.84 352	64.11 342	41.23 370	64.04 358	78.22 328	60.00 203	48.80 416	54.17 261	83.71 258	71.37 364

D2MVS		62.58 306	61.05 317	67.20 266	63.85 392	47.92 279	56.29 386	69.58 295	39.32 386	70.07 298	78.19 329	34.93 382	72.68 266	53.44 269	83.74 256	81.00 234

CL-MVSNet_self_test		62.44 307	63.40 296	59.55 346	72.34 284	32.38 415	56.39 385	64.84 335	51.21 262	67.46 336	81.01 274	50.75 289	63.51 367	38.47 379	88.12 173	82.75 189

MDA-MVSNet-bldmvs		62.34 308	61.73 308	64.16 295	61.64 405	49.90 253	48.11 428	57.24 373	53.31 233	80.95 108	79.39 307	49.00 305	61.55 374	45.92 333	80.05 316	81.03 232

IMVS_0404		62.18 309	63.05 301	59.58 345	72.47 279	48.64 266	55.47 393	72.98 247	45.33 333	55.80 417	79.37 308	49.84 294	53.60 403	55.06 244	81.11 295	76.49 307

miper_lstm_enhance		61.97 310	61.63 311	62.98 311	60.04 414	45.74 308	47.53 430	70.95 283	44.04 346	73.06 253	78.84 322	39.72 357	60.33 377	55.82 236	84.64 241	82.88 184

wuyk23d		61.97 310	66.25 261	49.12 408	58.19 430	60.77 156	66.32 292	52.97 401	55.93 189	90.62 6	86.91 146	73.07 61	35.98 456	20.63 458	91.63 92	50.62 445

thres600view7		61.82 312	61.38 314	63.12 309	71.81 291	34.93 402	64.64 320	56.99 375	54.78 203	70.33 293	79.74 296	32.07 398	72.42 274	38.61 377	83.46 261	82.02 210

SSC-MVS		61.79 313	66.08 263	48.89 410	76.91 201	10.00 468	53.56 406	47.37 428	68.20 64	76.56 178	89.21 96	54.13 266	57.59 391	54.75 251	74.07 379	79.08 273

PAPM		61.79 313	60.37 323	66.05 281	76.09 215	41.87 343	69.30 239	76.79 211	40.64 380	53.80 427	79.62 301	44.38 328	82.92 100	29.64 431	73.11 386	73.36 341

SD_0403		61.63 315	62.83 304	58.03 358	72.21 286	32.43 414	69.33 238	69.00 303	44.54 344	62.01 377	79.42 305	55.27 259	66.88 342	36.07 402	77.63 348	74.78 326

MVP-Stereo		61.56 316	59.22 330	68.58 243	79.28 154	60.44 158	69.20 242	71.57 267	43.58 353	56.42 412	78.37 326	39.57 359	76.46 219	34.86 408	60.16 441	68.86 390
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
CMPMVS	48.73 20	61.54 317	60.89 318	63.52 304	61.08 408	51.55 234	68.07 266	68.00 314	33.88 421	65.87 344	81.25 269	37.91 369	67.71 329	49.32 300	82.60 272	71.31 366
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
test2506		61.23 318	60.85 319	62.38 318	78.80 168	27.88 437	67.33 277	37.42 456	54.23 216	67.55 335	88.68 113	17.87 460	74.39 249	46.33 330	89.41 150	84.86 113

thres100view900		61.17 319	61.09 316	61.39 328	72.14 288	35.01 401	65.42 305	56.99 375	55.23 195	70.71 289	79.90 294	32.07 398	72.09 278	35.61 404	81.73 285	77.08 303

Patchmtry		60.91 320	63.01 302	54.62 376	66.10 376	26.27 445	67.47 272	56.40 382	54.05 222	72.04 269	86.66 157	33.19 388	60.17 378	43.69 345	87.45 185	77.42 295

EU-MVSNet		60.82 321	60.80 320	60.86 336	68.37 343	41.16 347	72.27 184	68.27 313	26.96 444	69.08 308	75.71 348	32.09 397	67.44 334	55.59 239	78.90 331	73.97 335

pmmvs4		60.78 322	59.04 332	66.00 282	73.06 270	57.67 190	64.53 323	60.22 360	36.91 405	65.96 343	77.27 338	39.66 358	68.54 322	38.87 374	74.89 369	71.80 360

thres400		60.77 323	59.97 325	63.15 308	70.78 303	35.35 399	63.27 336	57.47 368	53.00 235	68.31 327	77.09 340	32.45 395	72.09 278	35.61 404	81.73 285	82.02 210

MVS		60.62 324	59.97 325	62.58 316	68.13 350	47.28 292	68.59 256	73.96 238	32.19 428	59.94 392	68.86 413	50.48 290	77.64 205	41.85 357	75.74 360	62.83 422

thisisatest0515		60.48 325	57.86 343	68.34 247	67.25 362	46.42 301	60.58 355	62.14 351	40.82 376	63.58 369	69.12 407	26.28 430	78.34 190	48.83 304	82.13 277	80.26 255

tfpn200view9		60.35 326	59.97 325	61.51 325	70.78 303	35.35 399	63.27 336	57.47 368	53.00 235	68.31 327	77.09 340	32.45 395	72.09 278	35.61 404	81.73 285	77.08 303

ppachtmachnet_test		60.26 327	59.61 328	62.20 319	67.70 357	44.33 322	58.18 374	60.96 358	40.75 378	65.80 345	72.57 378	41.23 345	63.92 364	46.87 325	82.42 274	78.33 281

WB-MVS		60.04 328	64.19 287	47.59 413	76.09 215	10.22 467	52.44 413	46.74 430	65.17 94	74.07 232	87.48 135	53.48 269	55.28 397	49.36 299	72.84 387	77.28 297

Patchmatch-RL test		59.95 329	59.12 331	62.44 317	72.46 283	54.61 217	59.63 361	47.51 427	41.05 373	74.58 221	74.30 364	31.06 410	65.31 357	51.61 277	79.85 320	67.39 397

1314		59.83 330	58.86 334	62.74 315	65.71 378	44.78 317	68.59 256	72.63 256	33.54 426	61.05 385	67.29 424	43.62 333	71.26 291	49.49 298	67.84 422	72.19 357

IB-MVS	49.67 18	59.69 331	56.96 350	67.90 253	68.19 348	50.30 247	61.42 346	65.18 332	47.57 312	55.83 415	67.15 425	23.77 440	79.60 164	43.56 347	79.97 317	73.79 338
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		59.48 332	58.99 333	60.96 334	77.84 181	42.39 341	61.42 346	68.45 312	37.96 397	59.93 393	67.46 421	45.11 324	65.07 359	40.89 364	71.81 396	75.41 320

FPMVS		59.43 333	60.07 324	57.51 361	77.62 187	71.52 53	62.33 342	50.92 410	57.40 170	69.40 306	80.00 293	39.14 362	61.92 373	37.47 388	66.36 425	39.09 456

CVMVSNet		59.21 334	58.44 338	61.51 325	73.94 252	47.76 283	71.31 208	64.56 338	26.91 446	60.34 389	70.44 391	36.24 378	67.65 330	53.57 267	68.66 417	69.12 388

CR-MVSNet		58.96 335	58.49 337	60.36 340	66.37 370	48.24 273	70.93 214	56.40 382	32.87 427	61.35 381	86.66 157	33.19 388	63.22 368	48.50 309	70.17 408	69.62 383

reproduce_monomvs		58.94 336	58.14 341	61.35 329	59.70 421	40.98 350	60.24 358	63.51 346	45.85 324	68.95 312	75.31 354	18.27 458	65.82 353	51.47 279	79.97 317	77.26 300

EPNet_dtu		58.93 337	58.52 336	60.16 342	67.91 353	47.70 285	69.97 228	58.02 366	49.73 281	47.28 447	73.02 376	38.14 366	62.34 370	36.57 396	85.99 213	70.43 375
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
Test_1112_low_res		58.78 338	58.69 335	59.04 351	79.41 152	38.13 380	57.62 376	66.98 319	34.74 417	59.62 396	77.56 336	42.92 337	63.65 366	38.66 376	70.73 404	75.35 322

PatchMatch-RL		58.68 339	57.72 344	61.57 324	76.21 213	73.59 43	61.83 343	49.00 422	47.30 315	61.08 383	68.97 409	50.16 292	59.01 383	36.06 403	68.84 416	52.10 443

SCA		58.57 340	58.04 342	60.17 341	70.17 320	41.07 349	65.19 309	53.38 399	43.34 358	61.00 386	73.48 371	45.20 322	69.38 313	40.34 367	70.31 407	70.05 377

testing3		58.28 341	58.38 339	58.00 359	77.45 189	26.12 446	60.78 353	43.00 442	56.02 186	70.18 295	75.76 347	13.27 468	67.24 337	48.02 315	80.89 300	80.65 246

CHOSEN 1792x2688		58.09 342	56.30 355	63.45 305	79.95 144	50.93 241	54.07 404	65.59 328	28.56 440	61.53 380	74.33 363	41.09 348	66.52 350	33.91 412	67.69 423	72.92 345

HY-MVS	49.31 19	57.96 343	57.59 346	59.10 350	66.85 369	36.17 392	65.13 310	65.39 331	39.24 389	54.69 424	78.14 330	44.28 329	67.18 338	33.75 414	70.79 403	73.95 336

baseline1		57.82 344	58.36 340	56.19 368	69.17 335	30.76 426	62.94 340	55.21 386	46.04 322	63.83 363	78.47 324	41.20 346	63.68 365	39.44 369	68.99 415	74.13 334

thres200		57.55 345	57.02 349	59.17 348	67.89 354	34.93 402	58.91 368	57.25 372	50.24 274	64.01 359	71.46 386	32.49 394	71.39 290	31.31 422	79.57 325	71.19 369

CostFormer		57.35 346	56.14 356	60.97 333	63.76 394	38.43 375	67.50 271	60.22 360	37.14 404	59.12 398	76.34 345	32.78 391	71.99 281	39.12 373	69.27 413	72.47 352

SSC-MVS3.2		57.01 347	59.50 329	49.57 404	67.73 356	25.95 447	46.68 433	51.75 408	51.41 258	63.84 362	79.66 299	53.28 271	50.34 411	37.85 384	83.28 264	72.41 353

testing3-2		56.85 348	57.62 345	54.53 377	75.84 220	22.23 457	51.26 418	49.10 420	61.04 134	63.74 365	79.73 297	22.29 447	59.44 381	31.16 424	84.43 248	81.92 216

test_fmvs3		56.78 349	55.99 358	59.12 349	53.96 450	48.09 276	58.76 369	66.22 322	27.54 442	76.66 173	68.69 415	25.32 436	51.31 407	53.42 270	73.38 384	77.97 292

our_test_3		56.46 350	56.51 353	56.30 367	67.70 357	39.66 366	55.36 395	52.34 405	40.57 381	63.85 361	69.91 402	40.04 355	58.22 388	43.49 348	75.29 368	71.03 372

ttmdpeth		56.40 351	55.45 362	59.25 347	55.63 441	40.69 355	58.94 367	49.72 416	36.22 408	65.39 347	86.97 144	23.16 443	56.69 394	42.30 352	80.74 305	80.36 253

tpm2		56.12 352	54.64 369	60.55 339	66.24 373	36.01 393	68.14 264	56.77 378	33.60 425	58.25 401	75.52 352	30.25 416	74.33 250	33.27 415	69.76 412	71.32 365

tpmvs		55.84 353	55.45 362	57.01 363	60.33 412	33.20 412	65.89 296	59.29 364	47.52 313	56.04 413	73.60 370	31.05 411	68.06 327	40.64 365	64.64 429	69.77 381

gg-mvs-nofinetune		55.75 354	56.75 352	52.72 386	62.87 398	28.04 436	68.92 246	41.36 451	71.09 47	50.80 437	92.63 15	20.74 450	66.86 344	29.97 429	72.41 390	63.25 421

testing91		55.74 355	55.29 365	57.08 362	70.63 307	30.85 425	54.94 399	56.31 384	50.34 272	57.08 405	70.10 399	24.50 438	65.86 352	36.98 393	76.75 354	74.53 330

test20.03		55.74 355	57.51 347	50.42 397	59.89 419	32.09 417	50.63 419	49.01 421	50.11 276	65.07 351	83.23 237	45.61 320	48.11 421	30.22 427	83.82 254	71.07 371

MS-PatchMatch		55.59 357	54.89 367	57.68 360	69.18 334	49.05 262	61.00 350	62.93 349	35.98 410	58.36 400	68.93 411	36.71 376	66.59 349	37.62 387	63.30 433	57.39 439

baseline2		55.57 358	52.74 379	64.05 298	65.26 381	44.11 323	62.38 341	54.43 390	39.03 390	51.21 435	67.35 423	33.66 386	72.45 273	37.14 390	64.22 431	75.60 317

MVStest1		55.38 359	54.97 366	56.58 366	43.72 463	40.07 363	59.13 363	47.09 429	34.83 415	76.53 181	84.65 199	13.55 467	53.30 404	55.04 248	80.23 314	76.38 312

XXY-MVS		55.19 360	57.40 348	48.56 412	64.45 390	34.84 404	51.54 416	53.59 395	38.99 391	63.79 364	79.43 304	56.59 249	45.57 428	36.92 394	71.29 400	65.25 411

testing99		55.16 361	54.56 370	56.98 364	70.13 323	30.58 427	54.55 402	54.11 392	49.53 286	56.76 409	70.14 398	22.76 445	65.79 354	36.99 392	76.04 359	74.57 329

FMVSNet5		55.08 362	55.54 361	53.71 379	65.80 377	33.50 411	56.22 387	52.50 403	43.72 352	61.06 384	83.38 229	25.46 434	54.87 398	30.11 428	81.64 290	72.75 349

test_fmvs2		54.80 363	54.11 373	56.88 365	51.76 454	49.95 252	56.70 382	65.80 325	26.22 447	69.42 305	65.25 429	31.82 402	49.98 413	49.63 296	70.36 406	70.71 373

PatchmatchNet		54.60 364	54.27 371	55.59 372	65.17 384	39.08 368	66.92 283	51.80 407	39.89 383	58.39 399	73.12 375	31.69 404	58.33 387	43.01 350	58.38 447	69.38 386
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
MIMVSNet		54.39 365	56.12 357	49.20 406	72.57 278	30.91 424	59.98 359	48.43 424	41.66 366	55.94 414	83.86 222	41.19 347	50.42 410	26.05 442	75.38 366	66.27 405

Syy-MVS		54.13 366	55.45 362	50.18 398	68.77 339	23.59 451	55.02 396	44.55 436	43.80 348	58.05 402	64.07 431	46.22 317	58.83 384	46.16 331	72.36 391	68.12 393

Anonymous20231206		54.13 366	55.82 359	49.04 409	70.89 301	35.96 394	51.73 415	50.87 411	34.86 414	62.49 375	79.22 314	42.52 341	44.29 439	27.95 438	81.88 281	66.88 401

JIA-IIPM		54.03 368	51.62 388	61.25 331	59.14 424	55.21 213	59.10 364	47.72 425	50.85 266	50.31 441	85.81 187	20.10 452	63.97 363	36.16 400	55.41 452	64.55 418

tpm cat1		54.02 369	52.63 381	58.19 356	64.85 388	39.86 365	66.26 293	57.28 371	32.16 429	56.90 407	70.39 393	32.75 392	65.30 358	34.29 410	58.79 444	69.41 385

testgi		54.00 370	56.86 351	45.45 422	58.20 429	25.81 448	49.05 424	49.50 418	45.43 330	67.84 330	81.17 270	51.81 282	43.20 443	29.30 432	79.41 326	67.34 399

WB-MVSnew		53.94 371	54.76 368	51.49 392	71.53 294	28.05 435	58.22 373	50.36 413	37.94 398	59.16 397	70.17 397	49.21 301	51.94 406	24.49 449	71.80 397	74.47 332

WBMVS		53.38 372	54.14 372	51.11 394	70.16 321	26.66 441	50.52 421	51.64 409	39.32 386	63.08 373	77.16 339	23.53 441	55.56 395	31.99 419	79.88 319	71.11 370

testing222		53.37 373	52.50 383	55.98 370	70.51 313	29.68 430	56.20 388	51.85 406	46.19 321	56.76 409	68.94 410	19.18 456	65.39 356	25.87 445	76.98 352	72.87 347

PatchT		53.35 374	56.47 354	43.99 429	64.19 391	17.46 460	59.15 362	43.10 441	52.11 247	54.74 423	86.95 145	29.97 419	49.98 413	43.62 346	74.40 375	64.53 419

testing11		53.13 375	52.26 385	55.75 371	70.44 314	31.73 419	54.75 400	52.40 404	44.81 342	52.36 432	68.40 417	21.83 448	65.74 355	32.64 418	72.73 388	69.78 380

test_vis1_n_1920		52.96 376	53.50 375	51.32 393	59.15 423	44.90 315	56.13 389	64.29 341	30.56 438	59.87 394	60.68 442	40.16 354	47.47 422	48.25 313	62.46 435	61.58 430

UWE-MVS		52.94 377	52.70 380	53.65 380	73.56 256	27.49 438	57.30 379	49.57 417	38.56 394	62.79 374	71.42 387	19.49 455	60.41 376	24.33 451	77.33 350	73.06 343

new-patchmatchnet		52.89 378	55.76 360	44.26 428	59.94 418	6.31 469	37.36 453	50.76 412	41.10 371	64.28 356	79.82 295	44.77 325	48.43 420	36.24 399	87.61 180	78.03 289

test_fmvs1_n		52.70 379	52.01 386	54.76 374	53.83 451	50.36 245	55.80 391	65.90 324	24.96 451	65.39 347	60.64 443	27.69 425	48.46 418	45.88 334	67.99 420	65.46 409

YYNet1		52.58 380	53.50 375	49.85 400	54.15 447	36.45 391	40.53 446	46.55 432	38.09 396	75.52 198	73.31 374	41.08 349	43.88 440	41.10 361	71.14 402	69.21 387

MDA-MVSNet_test_wron		52.57 381	53.49 377	49.81 401	54.24 446	36.47 390	40.48 447	46.58 431	38.13 395	75.47 200	73.32 373	41.05 350	43.85 441	40.98 363	71.20 401	69.10 389

pmmvs5		52.49 382	52.58 382	52.21 388	54.99 444	32.38 415	55.45 394	53.84 394	32.15 430	55.49 418	74.81 356	38.08 367	57.37 392	34.02 411	74.40 375	66.88 401

UnsupCasMVSNet_eth		52.26 383	53.29 378	49.16 407	55.08 443	33.67 410	50.03 422	58.79 365	37.67 400	63.43 372	74.75 358	41.82 343	45.83 426	38.59 378	59.42 443	67.98 396

N_pmnet		52.06 384	51.11 393	54.92 373	59.64 422	71.03 57	37.42 452	61.62 357	33.68 423	57.12 404	72.10 379	37.94 368	31.03 458	29.13 437	71.35 399	62.70 423

KD-MVS_2432*1600		52.05 385	51.58 389	53.44 382	52.11 452	31.20 421	44.88 439	64.83 336	41.53 367	64.37 354	70.03 400	15.61 464	64.20 361	36.25 397	74.61 372	64.93 415

miper_refine_blended		52.05 385	51.58 389	53.44 382	52.11 452	31.20 421	44.88 439	64.83 336	41.53 367	64.37 354	70.03 400	15.61 464	64.20 361	36.25 397	74.61 372	64.93 415

test_vis3_rt		51.94 387	51.04 394	54.65 375	46.32 461	50.13 249	44.34 441	78.17 190	23.62 455	68.95 312	62.81 435	21.41 449	38.52 454	41.49 359	72.22 393	75.30 323

PVSNet	43.83 21	51.56 388	51.17 392	52.73 385	68.34 344	38.27 377	48.22 427	53.56 397	36.41 407	54.29 425	64.94 430	34.60 383	54.20 401	30.34 426	69.87 410	65.71 408

test_fmvs1		51.51 389	50.86 397	53.48 381	49.72 457	49.35 261	54.11 403	64.96 334	24.64 453	63.66 367	59.61 446	28.33 424	48.45 419	45.38 339	67.30 424	62.66 425

myMVS_eth3d28		51.35 390	51.99 387	49.44 405	69.21 333	22.51 455	49.82 423	49.11 419	49.00 295	55.03 420	70.31 394	22.73 446	52.88 405	24.33 451	78.39 339	72.92 345

test_vis1_n		51.27 391	50.41 401	53.83 378	56.99 433	50.01 251	56.75 381	60.53 359	25.68 449	59.74 395	57.86 447	29.40 421	47.41 423	43.10 349	63.66 432	64.08 420

test_cas_vis1_n_1920		50.90 392	50.92 396	50.83 396	54.12 449	47.80 281	51.44 417	54.61 389	26.95 445	63.95 360	60.85 441	37.86 371	44.97 434	45.53 336	62.97 434	59.72 434

tpm		50.60 393	52.42 384	45.14 424	65.18 383	26.29 444	60.30 356	43.50 439	37.41 402	57.01 406	79.09 318	30.20 418	42.32 444	32.77 417	66.36 425	66.81 403

test-LLR		50.43 394	50.69 399	49.64 402	60.76 409	41.87 343	53.18 408	45.48 434	43.41 356	49.41 442	60.47 444	29.22 422	44.73 436	42.09 355	72.14 394	62.33 428

myMVS_eth3d		50.36 395	50.52 400	49.88 399	68.77 339	22.69 453	55.02 396	44.55 436	43.80 348	58.05 402	64.07 431	14.16 466	58.83 384	33.90 413	72.36 391	68.12 393

ETVMVS		50.32 396	49.87 404	51.68 390	70.30 319	26.66 441	52.33 414	43.93 438	43.54 354	54.91 421	67.95 419	20.01 453	60.17 378	22.47 454	73.40 383	68.22 392

tpmrst		50.15 397	51.38 391	46.45 419	56.05 437	24.77 449	64.40 325	49.98 414	36.14 409	53.32 429	69.59 404	35.16 381	48.69 417	39.24 371	58.51 446	65.89 406

UnsupCasMVSNet_bld		50.01 398	51.03 395	46.95 415	58.61 426	32.64 413	48.31 426	53.27 400	34.27 420	60.47 388	71.53 385	41.40 344	47.07 424	30.68 425	60.78 440	61.13 431

dmvs_re		49.91 399	50.77 398	47.34 414	59.98 415	38.86 372	53.18 408	53.58 396	39.75 384	55.06 419	61.58 440	36.42 377	44.40 438	29.15 436	68.23 418	58.75 436

WTY-MVS		49.39 400	50.31 402	46.62 418	61.22 407	32.00 418	46.61 434	49.77 415	33.87 422	54.12 426	69.55 405	41.96 342	45.40 431	31.28 423	64.42 430	62.47 426

UBG		49.18 401	49.35 405	48.66 411	70.36 317	26.56 443	50.53 420	45.61 433	37.43 401	53.37 428	65.97 426	23.03 444	54.20 401	26.29 440	71.54 398	65.20 412

ADS-MVSNet2		48.76 402	47.25 411	53.29 384	55.90 439	40.54 359	47.34 431	54.99 388	31.41 435	50.48 438	72.06 380	31.23 407	54.26 400	25.93 443	55.93 449	65.07 413

test-mter		48.56 403	48.20 408	49.64 402	60.76 409	41.87 343	53.18 408	45.48 434	31.91 433	49.41 442	60.47 444	18.34 457	44.73 436	42.09 355	72.14 394	62.33 428

Patchmatch-test		47.93 404	49.96 403	41.84 433	57.42 432	24.26 450	48.75 425	41.49 450	39.30 388	56.79 408	73.48 371	30.48 415	33.87 457	29.29 433	72.61 389	67.39 397

test0.0.03 1		47.72 405	48.31 407	45.93 420	55.53 442	29.39 431	46.40 435	41.21 452	43.41 356	55.81 416	67.65 420	29.22 422	43.77 442	25.73 446	69.87 410	64.62 417

sss		47.59 406	48.32 406	45.40 423	56.73 436	33.96 408	45.17 437	48.51 423	32.11 432	52.37 431	65.79 427	40.39 353	41.91 447	31.85 420	61.97 437	60.35 432

pmmvs3		46.71 407	45.09 417	51.55 391	56.76 435	48.25 272	55.78 392	39.53 455	24.13 454	50.35 440	63.40 433	15.90 463	51.08 409	29.29 433	70.69 405	55.33 442

test_vis1_rt		46.70 408	45.24 416	51.06 395	44.58 462	51.04 240	39.91 448	67.56 315	21.84 459	51.94 433	50.79 455	33.83 385	39.77 451	35.25 407	61.50 438	62.38 427

EPMVS		45.74 409	46.53 412	43.39 431	54.14 448	22.33 456	55.02 396	35.00 459	34.69 418	51.09 436	70.20 396	25.92 432	42.04 446	37.19 389	55.50 451	65.78 407

MVS-HIRNet		45.53 410	47.29 410	40.24 436	62.29 401	26.82 440	56.02 390	37.41 457	29.74 439	43.69 457	81.27 268	33.96 384	55.48 396	24.46 450	56.79 448	38.43 457

dmvs_testset		45.26 411	47.51 409	38.49 439	59.96 417	14.71 463	58.50 371	43.39 440	41.30 369	51.79 434	56.48 448	39.44 361	49.91 415	21.42 456	55.35 453	50.85 444

TESTMET0.1,1		45.17 412	44.93 418	45.89 421	56.02 438	38.31 376	53.18 408	41.94 449	27.85 441	44.86 453	56.47 449	17.93 459	41.50 449	38.08 382	68.06 419	57.85 437

E-PMN		45.17 412	45.36 415	44.60 426	50.07 455	42.75 337	38.66 450	42.29 447	46.39 320	39.55 458	51.15 454	26.00 431	45.37 432	37.68 385	76.41 355	45.69 451

PMMVS		44.69 414	43.95 423	46.92 416	50.05 456	53.47 226	48.08 429	42.40 445	22.36 457	44.01 456	53.05 452	42.60 340	45.49 429	31.69 421	61.36 439	41.79 454

ADS-MVSNet		44.62 415	45.58 414	41.73 434	55.90 439	20.83 458	47.34 431	39.94 454	31.41 435	50.48 438	72.06 380	31.23 407	39.31 452	25.93 443	55.93 449	65.07 413

EMVS		44.61 416	44.45 421	45.10 425	48.91 458	43.00 335	37.92 451	41.10 453	46.75 318	38.00 460	48.43 457	26.42 429	46.27 425	37.11 391	75.38 366	46.03 450

UWE-MVS-28		44.18 417	44.37 422	43.61 430	60.10 413	16.96 461	52.62 412	33.27 460	36.79 406	48.86 444	69.47 406	19.96 454	45.65 427	13.40 461	64.83 428	68.23 391

dp		44.09 418	44.88 419	41.72 435	58.53 428	23.18 452	54.70 401	42.38 446	34.80 416	44.25 455	65.61 428	24.48 439	44.80 435	29.77 430	49.42 455	57.18 440

test_f		43.79 419	45.63 413	38.24 440	42.29 466	38.58 374	34.76 455	47.68 426	22.22 458	67.34 337	63.15 434	31.82 402	30.60 459	39.19 372	62.28 436	45.53 452

mvsany_test3		43.76 420	41.01 424	52.01 389	48.09 459	57.74 189	42.47 443	23.85 466	23.30 456	64.80 352	62.17 438	27.12 426	40.59 450	29.17 435	48.11 456	57.69 438

DSMNet-mixed		43.18 421	44.66 420	38.75 438	54.75 445	28.88 434	57.06 380	27.42 463	13.47 461	47.27 448	77.67 335	38.83 363	39.29 453	25.32 448	60.12 442	48.08 447

CHOSEN 280x420		41.62 422	39.89 427	46.80 417	61.81 403	51.59 233	33.56 456	35.74 458	27.48 443	37.64 461	53.53 450	23.24 442	42.09 445	27.39 439	58.64 445	46.72 449

PVSNet_0	36.71 22	41.12 423	40.78 426	42.14 432	59.97 416	40.13 362	40.97 445	42.24 448	30.81 437	44.86 453	49.41 456	40.70 351	45.12 433	23.15 453	34.96 459	41.16 455

mvsany_test1		37.88 424	35.74 429	44.28 427	47.28 460	49.90 253	36.54 454	24.37 465	19.56 460	45.76 449	53.46 451	32.99 390	37.97 455	26.17 441	35.52 458	44.99 453

PMMVS2		37.74 425	40.87 425	28.36 442	42.41 465	5.35 470	24.61 457	27.75 462	32.15 430	47.85 446	70.27 395	35.85 379	29.51 460	19.08 459	67.85 421	50.22 446

new_pmnet		37.55 426	39.80 428	30.79 441	56.83 434	16.46 462	39.35 449	30.65 461	25.59 450	45.26 451	61.60 439	24.54 437	28.02 461	21.60 455	52.80 454	47.90 448

MVE	27.91 23	36.69 427	35.64 430	39.84 437	43.37 464	35.85 396	19.49 458	24.61 464	24.68 452	39.05 459	62.63 437	38.67 365	27.10 462	21.04 457	47.25 457	56.56 441
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
dongtai		31.66 428	32.98 431	27.71 443	58.58 427	12.61 465	45.02 438	14.24 469	41.90 364	47.93 445	43.91 458	10.65 469	41.81 448	14.06 460	20.53 462	28.72 459

kuosan		22.02 429	23.52 433	17.54 445	41.56 467	11.24 466	41.99 444	13.39 470	26.13 448	28.87 462	30.75 460	9.72 470	21.94 464	4.77 465	14.49 463	19.43 460

test_method		19.26 430	19.12 434	19.71 444	9.09 469	1.91 472	7.79 460	53.44 398	1.42 463	10.27 465	35.80 459	17.42 461	25.11 463	12.44 462	24.38 461	32.10 458

cdsmvs_eth3d_5k		17.71 431	23.62 432	0.00 450	0.00 473	0.00 475	0.00 461	70.17 291	0.00 468	0.00 469	74.25 365	68.16 104	0.00 469	0.00 468	0.00 467	0.00 465

tmp_tt		11.98 432	14.73 435	3.72 447	2.28 470	4.62 471	19.44 459	14.50 468	0.47 465	21.55 463	9.58 463	25.78 433	4.57 466	11.61 463	27.37 460	1.96 462

ab-mvs-re		5.62 433	7.50 436	0.00 450	0.00 473	0.00 475	0.00 461	0.00 474	0.00 468	0.00 469	67.46 421	0.00 473	0.00 469	0.00 468	0.00 467	0.00 465

pcd_1.5k_mvsjas		5.20 434	6.93 437	0.00 450	0.00 473	0.00 475	0.00 461	0.00 474	0.00 468	0.00 469	0.00 468	62.39 168	0.00 469	0.00 468	0.00 467	0.00 465

test123		4.43 435	5.78 438	0.39 449	0.97 471	0.28 473	46.33 436	0.45 472	0.31 466	0.62 467	1.50 466	0.61 472	0.11 468	0.56 466	0.63 465	0.77 464

testmvs		4.06 436	5.28 439	0.41 448	0.64 472	0.16 474	42.54 442	0.31 473	0.26 467	0.50 468	1.40 467	0.77 471	0.17 467	0.56 466	0.55 466	0.90 463

mmdepth		0.00 437	0.00 440	0.00 450	0.00 473	0.00 475	0.00 461	0.00 474	0.00 468	0.00 469	0.00 468	0.00 473	0.00 469	0.00 468	0.00 467	0.00 465

monomultidepth		0.00 437	0.00 440	0.00 450	0.00 473	0.00 475	0.00 461	0.00 474	0.00 468	0.00 469	0.00 468	0.00 473	0.00 469	0.00 468	0.00 467	0.00 465

test_blank		0.00 437	0.00 440	0.00 450	0.00 473	0.00 475	0.00 461	0.00 474	0.00 468	0.00 469	0.00 468	0.00 473	0.00 469	0.00 468	0.00 467	0.00 465

uanet_test		0.00 437	0.00 440	0.00 450	0.00 473	0.00 475	0.00 461	0.00 474	0.00 468	0.00 469	0.00 468	0.00 473	0.00 469	0.00 468	0.00 467	0.00 465

DCPMVS		0.00 437	0.00 440	0.00 450	0.00 473	0.00 475	0.00 461	0.00 474	0.00 468	0.00 469	0.00 468	0.00 473	0.00 469	0.00 468	0.00 467	0.00 465

sosnet-low-res		0.00 437	0.00 440	0.00 450	0.00 473	0.00 475	0.00 461	0.00 474	0.00 468	0.00 469	0.00 468	0.00 473	0.00 469	0.00 468	0.00 467	0.00 465

sosnet		0.00 437	0.00 440	0.00 450	0.00 473	0.00 475	0.00 461	0.00 474	0.00 468	0.00 469	0.00 468	0.00 473	0.00 469	0.00 468	0.00 467	0.00 465

uncertanet		0.00 437	0.00 440	0.00 450	0.00 473	0.00 475	0.00 461	0.00 474	0.00 468	0.00 469	0.00 468	0.00 473	0.00 469	0.00 468	0.00 467	0.00 465

Regformer		0.00 437	0.00 440	0.00 450	0.00 473	0.00 475	0.00 461	0.00 474	0.00 468	0.00 469	0.00 468	0.00 473	0.00 469	0.00 468	0.00 467	0.00 465

uanet		0.00 437	0.00 440	0.00 450	0.00 473	0.00 475	0.00 461	0.00 474	0.00 468	0.00 469	0.00 468	0.00 473	0.00 469	0.00 468	0.00 467	0.00 465

WAC-MVS						22.69 453								36.10 401

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

MSC_two_6792asdad				79.02 58	83.14 102	67.03 94		80.75 132					86.24 24	77.27 38	94.85 31	83.78 151

PC_three_1452									46.98 317	81.83 95	86.28 169	66.55 128	84.47 74	63.31 159	90.78 120	83.49 159

No_MVS				79.02 58	83.14 102	67.03 94		80.75 132					86.24 24	77.27 38	94.85 31	83.78 151

test_one_0601					85.84 64	61.45 142		85.63 31	75.27 21	85.62 52	90.38 71	76.72 31

eth-test2					0.00 473

eth-test					0.00 473

ZD-MVS					83.91 91	69.36 75		81.09 126	58.91 154	82.73 88	89.11 101	75.77 39	86.63 14	72.73 71	92.93 74

RE-MVS-def			85.50 7		86.19 50	79.18 7	87.23 9	86.27 21	77.51 14	87.65 22	90.73 54	81.38 7		78.11 28	94.46 41	84.89 110

IU-MVS					86.12 54	60.90 152		80.38 144	45.49 329	81.31 103				75.64 46	94.39 46	84.65 120

OPU-MVS				78.65 65	83.44 100	66.85 96	83.62 47				86.12 178	66.82 120	86.01 34	61.72 171	89.79 142	83.08 177

test_241102_TWO								84.80 49	72.61 36	84.93 60	89.70 87	77.73 25	85.89 42	75.29 47	94.22 57	83.25 170

test_241102_ONE					86.12 54	61.06 148		84.72 53	72.64 35	87.38 28	89.47 90	77.48 27	85.74 46

9.14			80.22 58		80.68 137		80.35 78	87.69 12	59.90 143	83.00 81	88.20 124	74.57 51	81.75 125	73.75 63	93.78 62

save fliter					87.00 40	67.23 93	79.24 92	77.94 195	56.65 181

test_0728_THIRD									74.03 25	85.83 47	90.41 66	75.58 41	85.69 47	77.43 35	94.74 35	84.31 138

test_0728_SECOND				76.57 92	86.20 49	60.57 157	83.77 45	85.49 33					85.90 40	75.86 43	94.39 46	83.25 170

test0726					86.16 52	60.78 154	83.81 44	85.10 44	72.48 38	85.27 57	89.96 83	78.57 19

GSMVS																70.05 377

test_part2					85.90 60	66.44 98				84.61 66

sam_mvs1												31.41 405				70.05 377

sam_mvs												31.21 409

ambc				70.10 209	77.74 183	50.21 248	74.28 164	77.93 196		79.26 125	88.29 123	54.11 267	79.77 161	64.43 142	91.10 108	80.30 254

MTGPA								80.63 138

test_post1							66.63 287				2.08 464	30.66 414	59.33 382	40.34 367

test_post											1.99 465	30.91 412	54.76 399

patchmatchnet-post											68.99 408	31.32 406	69.38 313

GG-mvs-BLEND				52.24 387	60.64 411	29.21 433	69.73 232	42.41 444		45.47 450	52.33 453	20.43 451	68.16 325	25.52 447	65.42 427	59.36 435

MTMP							84.83 34	19.26 467

gm-plane-assit					62.51 399	33.91 409			37.25 403		62.71 436		72.74 265	38.70 375

test9_res														72.12 79	91.37 98	77.40 296

TEST9					85.47 67	69.32 76	76.42 128	78.69 180	53.73 228	76.97 161	86.74 153	66.84 119	81.10 135

test_8					85.09 74	67.89 85	76.26 133	78.66 182	54.00 223	76.89 165	86.72 155	66.60 125	80.89 145

agg_prior2														70.70 87	90.93 114	78.55 279

agg_prior					84.44 86	66.02 104		78.62 183		76.95 163			80.34 152

TestCases				78.35 70	79.19 158	70.81 59		88.64 4	65.37 89	80.09 118	88.17 125	70.33 84	78.43 186	55.60 237	90.90 116	85.81 87

test_prior4						70.14 67	77.57 109

test_prior2							75.57 141		58.92 153	76.53 181	86.78 151	67.83 112		69.81 94	92.76 77

test_prior				75.27 112	82.15 121	59.85 165		84.33 67					83.39 92			82.58 196

旧先验2							71.17 211		45.11 339	78.54 138			61.28 375	59.19 201

新几何2							71.33 207

新几何1				69.99 211	88.37 35	71.34 55		62.08 353	43.85 347	74.99 209	86.11 179	52.85 273	70.57 299	50.99 284	83.23 265	68.05 395

旧先验1					84.55 83	60.36 159		63.69 344			87.05 143	54.65 262			83.34 263	69.66 382

无先验							74.82 148	70.94 284	47.75 311				76.85 215	54.47 255		72.09 358

原ACMM2							74.78 152

原ACMM1				73.90 128	85.90 60	65.15 113		81.67 111	50.97 264	74.25 228	86.16 175	61.60 180	83.54 87	56.75 224	91.08 110	73.00 344

test222					87.30 38	69.15 79	67.85 267	59.59 363	41.06 372	73.05 254	85.72 188	48.03 312			80.65 307	66.92 400

testdata2													67.30 335	48.34 311

segment_acmp												68.30 103

testdata				64.13 296	85.87 62	63.34 127		61.80 356	47.83 309	76.42 186	86.60 162	48.83 306	62.31 371	54.46 256	81.26 294	66.74 404

testdata1							68.34 263		57.24 172

test12				76.51 93	82.28 119	60.94 151		81.64 112		73.60 241		64.88 147	85.19 62		90.42 127	83.38 166

plane_prior7					85.18 70	66.21 101

plane_prior6					84.18 89	65.31 110						60.83 193

plane_prior5								85.49 33					86.15 29	71.09 82	90.94 112	84.82 115

plane_prior4											89.11 101

plane_prior3						65.67 106			63.82 108	78.23 141

plane_prior2							82.74 56		65.45 86

plane_prior1					84.46 85

plane_prior						65.18 111	80.06 84		61.88 128						89.91 139

n2								0.00 474

nn								0.00 474

door-mid								55.02 387

lessismore_v0				72.75 163	79.60 150	56.83 196		57.37 370		83.80 75	89.01 105	47.45 314	78.74 178	64.39 143	86.49 208	82.69 193

LGP-MVS_train				80.90 36	87.00 40	70.41 64		86.35 18	69.77 56	87.75 19	91.13 42	81.83 3	86.20 26	77.13 40	95.96 6	86.08 81

test11								82.71 95

door								52.91 402

HQP5-MVS						58.80 178

HQP-NCC					82.37 116		77.32 114		59.08 148	71.58 275

ACMP_Plane					82.37 116		77.32 114		59.08 148	71.58 275

BP-MVS														67.38 119

HQP4-MVS										71.59 273			85.31 54			83.74 153

HQP3-MVS								84.12 73							89.16 154

HQP2-MVS												58.09 231

NP-MVS					83.34 101	63.07 130					85.97 183

MDTV_nov1_ep13_2view						18.41 459	53.74 405		31.57 434	44.89 452		29.90 420		32.93 416		71.48 362

MDTV_nov1_ep13			54.05 374		65.54 380	29.30 432	59.00 365	55.22 385	35.96 411	52.44 430	75.98 346	30.77 413	59.62 380	38.21 380	73.33 385

ACMMP++_ref															89.47 149

ACMMP++															91.96 88

Test By Simon												62.56 164

ITE_SJBPF				80.35 42	76.94 197	73.60 42		80.48 141	66.87 72	83.64 77	86.18 173	70.25 87	79.90 160	61.12 179	88.95 164	87.56 57

DeepMVS_CX				11.83 446	15.51 468	13.86 464		11.25 471	5.76 462	20.85 464	26.46 461	17.06 462	9.22 465	9.69 464	13.82 464	12.42 461

High-resolution multi-view benchmark