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.

DVP-MVS++		81.24 39	82.74 40	76.76 93	83.14 103	60.90 147	91.64 1	85.49 34	74.03 23	84.93 58	90.38 68	66.82 114	85.90 39	77.43 33	90.78 123	83.49 142

FOURS1					89.19 25	77.84 16	91.64 1	89.11 2	84.05 2	91.57 2

LTVRE_ROB	75.46 1	84.22 8	84.98 9	81.94 23	84.82 78	75.40 30	91.60 3	87.80 8	73.52 26	88.90 11	93.06 6	71.39 75	81.53 125	81.53 3	92.15 93	88.91 41
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
TDRefinement		86.32 2	86.33 2	86.29 1	88.64 33	81.19 5	88.84 4	90.72 1	78.27 9	87.95 15	92.53 13	79.37 13	84.79 68	74.51 51	96.15 2	92.88 7

CP-MVS		84.12 10	84.55 12	82.80 12	89.42 18	79.74 7	88.19 5	84.43 64	71.96 42	84.70 64	90.56 55	77.12 26	86.18 26	79.24 18	95.36 13	82.49 175

ACMMP		84.22 8	84.84 10	82.35 20	89.23 23	76.66 26	87.65 6	85.89 30	71.03 45	85.85 42	90.58 54	78.77 17	85.78 43	79.37 16	95.17 17	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
abl_6		84.92 3	85.70 3	82.57 17	86.72 49	79.27 8	87.56 7	86.08 27	77.48 13	88.12 14	91.53 30	81.18 8	84.31 77	78.12 24	94.47 38	84.15 128

LS3D		80.99 46	80.85 55	81.41 29	78.37 173	71.37 56	87.45 8	85.87 31	77.48 13	81.98 96	89.95 82	69.14 91	85.26 56	66.15 113	91.24 107	87.61 55

SR-MVS-dyc-post		84.75 5	85.26 7	83.21 3	86.19 55	79.18 9	87.23 9	86.27 22	77.51 11	87.65 19	90.73 49	79.20 14	85.58 50	78.11 25	94.46 39	84.89 97

RE-MVS-def			85.50 4		86.19 55	79.18 9	87.23 9	86.27 22	77.51 11	87.65 19	90.73 49	81.38 7		78.11 25	94.46 39	84.89 97

COLMAP_ROB	72.78 3	83.75 13	84.11 17	82.68 14	82.97 111	74.39 37	87.18 11	88.18 7	78.98 7	86.11 40	91.47 32	79.70 12	85.76 44	66.91 112	95.46 11	87.89 51
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
MSP-MVS		80.49 50	79.67 65	82.96 7	89.70 12	77.46 23	87.16 12	85.10 45	64.94 90	81.05 109	88.38 114	57.10 207	87.10 7	79.75 8	83.87 230	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
mPP-MVS		84.01 12	84.39 13	82.88 8	90.65 4	81.38 4	87.08 13	82.79 92	72.41 36	85.11 57	90.85 45	76.65 30	84.89 65	79.30 17	94.63 35	82.35 178

region2R		83.54 16	83.86 21	82.58 16	89.82 10	77.53 20	87.06 14	84.23 72	70.19 51	83.86 77	90.72 51	75.20 42	86.27 21	79.41 15	94.25 53	83.95 131

HFP-MVS		83.39 19	84.03 18	81.48 26	89.25 21	75.69 28	87.01 15	84.27 68	70.23 49	84.47 68	90.43 60	76.79 27	85.94 35	79.58 11	94.23 54	82.82 165

ACMMPR		83.62 14	83.93 19	82.69 13	89.78 11	77.51 22	87.01 15	84.19 73	70.23 49	84.49 67	90.67 52	75.15 43	86.37 18	79.58 11	94.26 52	84.18 127

SR-MVS		84.51 7	85.27 6	82.25 21	88.52 35	77.71 17	86.81 17	85.25 41	77.42 15	86.15 38	90.24 75	81.69 5	85.94 35	77.77 29	93.58 68	83.09 156

XVS		83.51 17	83.73 22	82.85 10	89.43 16	77.61 18	86.80 18	84.66 57	72.71 29	82.87 86	90.39 66	73.86 56	86.31 19	78.84 20	94.03 58	84.64 107

X-MVStestdata		76.81 87	74.79 108	82.85 10	89.43 16	77.61 18	86.80 18	84.66 57	72.71 29	82.87 86	9.95 374	73.86 56	86.31 19	78.84 20	94.03 58	84.64 107

TSAR-MVS + MP.		79.05 64	78.81 69	79.74 48	88.94 29	67.52 87	86.61 20	81.38 114	51.71 228	77.15 155	91.42 35	65.49 129	87.20 5	79.44 14	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
APDe-MVS		82.88 26	84.14 16	79.08 59	84.80 80	66.72 95	86.54 21	85.11 44	72.00 41	86.65 33	91.75 25	78.20 21	87.04 8	77.93 28	94.32 51	83.47 145

CPTT-MVS		81.51 38	81.76 47	80.76 39	89.20 24	78.75 12	86.48 22	82.03 103	68.80 56	80.92 112	88.52 110	72.00 68	82.39 110	74.80 47	93.04 77	81.14 194

MP-MVS		83.19 20	83.54 26	82.14 22	90.54 5	79.00 11	86.42 23	83.59 83	71.31 43	81.26 107	90.96 42	74.57 51	84.69 69	78.41 22	94.78 28	82.74 169
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
ZNCC-MVS		83.12 22	83.68 23	81.45 28	89.14 26	73.28 47	86.32 24	85.97 29	67.39 64	84.02 74	90.39 66	74.73 48	86.46 15	80.73 7	94.43 43	84.60 112

HPM-MVS_fast		84.59 6	85.10 8	83.06 6	88.60 34	75.83 27	86.27 25	86.89 18	73.69 25	86.17 37	91.70 26	78.23 20	85.20 60	79.45 13	94.91 25	88.15 49

GST-MVS		82.79 27	83.27 32	81.34 31	88.99 28	73.29 46	85.94 26	85.13 43	68.58 60	84.14 73	90.21 77	73.37 61	86.41 16	79.09 19	93.98 61	84.30 126

SteuartSystems-ACMMP		83.07 23	83.64 24	81.35 30	85.14 74	71.00 60	85.53 27	84.78 51	70.91 46	85.64 45	90.41 63	75.55 40	87.69 3	79.75 8	95.08 20	85.36 88
Skip Steuart: Steuart Systems R&D Blog.
APD-MVS_3200maxsize		83.57 15	84.33 14	81.31 32	82.83 114	73.53 45	85.50 28	87.45 14	74.11 21	86.45 35	90.52 58	80.02 11	84.48 72	77.73 30	94.34 50	85.93 78

HPM-MVS		84.12 10	84.63 11	82.60 15	88.21 39	74.40 36	85.24 29	87.21 16	70.69 48	85.14 56	90.42 62	78.99 16	86.62 13	80.83 6	94.93 24	86.79 66
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
test1172		84.85 4	85.39 5	83.21 3	88.34 38	80.50 6	85.12 30	85.22 42	81.06 3	87.20 28	90.28 74	79.20 14	85.58 50	78.04 27	94.08 57	83.55 140

SMA-MVS		82.12 32	82.68 42	80.43 41	88.90 31	69.52 71	85.12 30	84.76 52	63.53 104	84.23 72	91.47 32	72.02 67	87.16 6	79.74 10	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
MTAPA		83.19 20	83.87 20	81.13 34	91.16 2	78.16 14	84.87 32	80.63 130	72.08 39	84.93 58	90.79 46	74.65 49	84.42 74	80.98 4	94.75 29	80.82 203

MTMP							84.83 33	19.26 381

LCM-MVSNet		86.90 1	88.67 1	81.57 24	91.50 1	63.30 124	84.80 34	87.77 10	86.18 1	96.26 1	96.06 1	90.32 1	84.49 71	68.08 97	97.05 1	96.93 1

UA-Net		81.56 37	82.28 44	79.40 56	88.91 30	69.16 78	84.67 35	80.01 145	75.34 17	79.80 124	94.91 2	69.79 87	80.25 153	72.63 66	94.46 39	88.78 45

#test#		82.40 30	82.71 41	81.48 26	89.25 21	75.69 28	84.47 36	84.27 68	64.45 94	84.47 68	90.43 60	76.79 27	85.94 35	76.01 39	94.23 54	82.82 165

3Dnovator+	73.19 2	81.08 44	80.48 57	82.87 9	81.41 134	72.03 50	84.38 37	86.23 25	77.28 16	80.65 115	90.18 78	59.80 180	87.58 4	73.06 63	91.34 105	89.01 37

EGC-MVSNET		64.77 231	61.17 262	75.60 110	86.90 47	74.47 35	84.04 38	68.62 263	0.60 376	1.13 378	91.61 29	65.32 132	74.15 243	64.01 129	88.28 166	78.17 241

MVSFormer		69.93 174	69.03 186	72.63 160	74.93 219	59.19 162	83.98 39	75.72 201	52.27 221	63.53 304	76.74 280	43.19 283	80.56 145	72.28 71	78.67 287	78.14 242

test_djsdf		78.88 66	78.27 76	80.70 40	81.42 133	71.24 58	83.98 39	75.72 201	52.27 221	87.37 27	92.25 16	68.04 104	80.56 145	72.28 71	91.15 110	90.32 23

APD-MVS		81.13 43	81.73 48	79.36 57	84.47 85	70.53 65	83.85 41	83.70 81	69.43 55	83.67 79	88.96 104	75.89 36	86.41 16	72.62 67	92.95 78	81.14 194
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
test0726					86.16 57	60.78 149	83.81 42	85.10 45	72.48 34	85.27 55	89.96 81	78.57 18

DVP-MVS		81.15 42	83.12 35	75.24 116	86.16 57	60.78 149	83.77 43	80.58 133	72.48 34	85.83 43	90.41 63	78.57 18	85.69 46	75.86 42	94.39 44	79.24 228
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
test_0728_SECOND				76.57 96	86.20 54	60.57 152	83.77 43	85.49 34					85.90 39	75.86 42	94.39 44	83.25 152

SED-MVS		81.78 35	83.48 27	76.67 94	86.12 59	61.06 143	83.62 45	84.72 54	72.61 32	87.38 25	89.70 85	77.48 24	85.89 41	75.29 45	94.39 44	83.08 157

OPU-MVS				78.65 68	83.44 101	66.85 94	83.62 45				86.12 166	66.82 114	86.01 31	61.72 150	89.79 145	83.08 157

ACMMP_NAP		82.33 31	83.28 31	79.46 55	89.28 19	69.09 80	83.62 45	84.98 47	64.77 91	83.97 75	91.02 41	75.53 41	85.93 38	82.00 2	94.36 48	83.35 150

testtj		81.19 41	81.70 49	79.67 52	83.95 93	69.77 70	83.58 48	84.63 59	72.13 38	82.85 88	88.36 115	75.00 46	86.79 11	71.99 75	92.84 80	82.44 176

HPM-MVS++		79.89 57	79.80 63	80.18 44	89.02 27	78.44 13	83.49 49	80.18 142	64.71 93	78.11 144	88.39 113	65.46 130	83.14 97	77.64 32	91.20 108	78.94 231

SF-MVS		80.72 48	81.80 46	77.48 84	82.03 125	64.40 116	83.41 50	88.46 6	65.28 85	84.29 70	89.18 95	73.73 59	83.22 95	76.01 39	93.77 63	84.81 103

SD-MVS		80.28 55	81.55 52	76.47 99	83.57 97	67.83 86	83.39 51	85.35 40	64.42 95	86.14 39	87.07 131	74.02 55	80.97 138	77.70 31	92.32 91	80.62 211
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
RRT_MVS		78.18 77	77.69 82	79.66 53	83.14 103	61.34 140	83.29 52	80.34 140	57.43 158	86.65 33	91.79 24	50.52 241	86.01 31	71.36 76	94.65 34	91.62 12

ACMM	69.25 9	82.11 33	83.31 30	78.49 70	88.17 40	73.96 39	83.11 53	84.52 63	66.40 74	87.45 23	89.16 98	81.02 9	80.52 148	74.27 53	95.73 7	80.98 199
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
DPE-MVS		82.00 34	83.02 36	78.95 64	85.36 71	67.25 89	82.91 54	84.98 47	73.52 26	85.43 51	90.03 79	76.37 31	86.97 10	74.56 50	94.02 60	82.62 171
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
HQP_MVS		78.77 67	78.78 71	78.72 66	85.18 72	65.18 107	82.74 55	85.49 34	65.45 80	78.23 141	89.11 99	60.83 170	86.15 27	71.09 77	90.94 115	84.82 101

plane_prior2							82.74 55		65.45 80

zzz-MVS		83.01 25	83.63 25	81.13 34	91.16 2	78.16 14	82.72 57	80.63 130	72.08 39	84.93 58	90.79 46	74.65 49	84.42 74	80.98 4	94.75 29	80.82 203

ACMP	69.50 8	82.64 28	83.38 29	80.40 42	86.50 51	69.44 73	82.30 58	86.08 27	66.80 69	86.70 32	89.99 80	81.64 6	85.95 34	74.35 52	96.11 3	85.81 80
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
PMVS	70.70 6	81.70 36	83.15 34	77.36 87	90.35 6	82.82 2	82.15 59	79.22 156	74.08 22	87.16 30	91.97 20	84.80 2	76.97 207	64.98 123	93.61 66	72.28 289
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
DeepC-MVS	72.44 4	81.00 45	80.83 56	81.50 25	86.70 50	70.03 69	82.06 60	87.00 17	59.89 133	80.91 113	90.53 56	72.19 65	88.56 1	73.67 58	94.52 37	85.92 79
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
PGM-MVS		83.07 23	83.25 33	82.54 18	89.57 14	77.21 24	82.04 61	85.40 38	67.96 62	84.91 62	90.88 43	75.59 38	86.57 14	78.16 23	94.71 32	83.82 132

LPG-MVS_test		83.47 18	84.33 14	80.90 37	87.00 43	70.41 66	82.04 61	86.35 19	69.77 53	87.75 16	91.13 37	81.83 3	86.20 24	77.13 37	95.96 5	86.08 74

F-COLMAP		75.29 102	73.99 120	79.18 58	81.73 130	71.90 51	81.86 63	82.98 89	59.86 134	72.27 228	84.00 192	64.56 139	83.07 100	51.48 230	87.19 188	82.56 174

MP-MVS-pluss		82.54 29	83.46 28	79.76 47	88.88 32	68.44 82	81.57 64	86.33 21	63.17 110	85.38 52	91.26 36	76.33 32	84.67 70	83.30 1	94.96 23	86.17 73
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
PAPM_NR		73.91 119	74.16 118	73.16 143	81.90 127	53.50 198	81.28 65	81.40 113	66.17 75	73.30 217	83.31 204	59.96 176	83.10 99	58.45 177	81.66 256	82.87 163

API-MVS		70.97 163	71.51 164	69.37 197	75.20 216	55.94 182	80.99 66	76.84 192	62.48 115	71.24 244	77.51 275	61.51 162	80.96 142	52.04 226	85.76 203	71.22 299

OMC-MVS		79.41 61	78.79 70	81.28 33	80.62 142	70.71 64	80.91 67	84.76 52	62.54 114	81.77 99	86.65 148	71.46 73	83.53 89	67.95 102	92.44 88	89.60 26

bld_raw_conf005		78.24 76	77.73 81	79.77 46	80.62 142	61.50 138	80.87 68	84.09 76	55.76 176	85.28 54	92.08 19	53.44 226	86.02 30	74.22 54	93.21 74	91.79 10

CS-MVS		76.51 90	76.00 97	78.06 79	77.02 192	64.77 111	80.78 69	82.66 95	60.39 129	74.15 205	83.30 205	69.65 88	82.07 117	69.27 89	86.75 194	87.36 59

mvs_tets		78.93 65	78.67 73	79.72 49	84.81 79	73.93 40	80.65 70	76.50 195	51.98 226	87.40 24	91.86 22	76.09 35	78.53 178	68.58 92	90.20 132	86.69 69

mvsmamba		77.20 83	76.37 93	79.69 51	80.34 146	61.52 137	80.58 71	82.12 101	53.54 211	83.93 76	91.03 40	49.49 248	85.97 33	73.26 61	93.08 76	91.59 13

ACMH+	66.64 10	81.20 40	82.48 43	77.35 88	81.16 137	62.39 130	80.51 72	87.80 8	73.02 28	87.57 21	91.08 39	80.28 10	82.44 108	64.82 124	96.10 4	87.21 61

EPP-MVSNet		73.86 120	73.38 132	75.31 113	78.19 175	53.35 200	80.45 73	77.32 187	65.11 88	76.47 176	86.80 137	49.47 249	83.77 83	53.89 218	92.72 86	88.81 44

jajsoiax		78.51 70	78.16 78	79.59 54	84.65 82	73.83 42	80.42 74	76.12 197	51.33 234	87.19 29	91.51 31	73.79 58	78.44 182	68.27 95	90.13 137	86.49 71

PHI-MVS		74.92 108	74.36 115	76.61 95	76.40 202	62.32 131	80.38 75	83.15 87	54.16 201	73.23 218	80.75 231	62.19 155	83.86 82	68.02 98	90.92 118	83.65 139

QAPM		69.18 186	69.26 182	68.94 207	71.61 265	52.58 204	80.37 76	78.79 164	49.63 252	73.51 212	85.14 180	53.66 224	79.12 168	55.11 204	75.54 305	75.11 265

9.14			80.22 59		80.68 140		80.35 77	87.69 11	59.90 132	83.00 84	88.20 118	74.57 51	81.75 123	73.75 57	93.78 62

DROMVSNet		77.08 85	77.39 85	76.14 104	76.86 199	56.87 178	80.32 78	87.52 13	63.45 106	74.66 199	84.52 185	69.87 86	84.94 63	69.76 87	89.59 148	86.60 70

ETH3D-3000-0.1		79.14 63	79.80 63	77.16 91	80.67 141	64.57 113	80.26 79	87.60 12	60.74 126	82.47 93	88.03 123	71.73 70	81.81 121	73.12 62	93.61 66	85.09 92

OurMVSNet-221017-0		78.57 69	78.53 75	78.67 67	80.48 144	64.16 117	80.24 80	82.06 102	61.89 118	88.77 12	93.32 4	57.15 205	82.60 107	70.08 83	92.80 82	89.25 31

XVG-ACMP-BASELINE		80.54 49	81.06 53	78.98 63	87.01 42	72.91 48	80.23 81	85.56 33	66.56 73	85.64 45	89.57 87	69.12 92	80.55 147	72.51 68	93.37 70	83.48 144

test_low_dy_conf_001		76.29 92	75.63 103	78.24 75	81.15 138	62.81 128	80.22 82	79.33 154	48.16 263	84.62 65	90.62 53	49.85 246	82.43 109	73.56 59	93.19 75	89.48 28

anonymousdsp		78.60 68	77.80 80	81.00 36	78.01 179	74.34 38	80.09 83	76.12 197	50.51 243	89.19 10	90.88 43	71.45 74	77.78 200	73.38 60	90.60 128	90.90 19

Gipuma		69.55 179	72.83 144	59.70 295	63.63 329	53.97 195	80.08 84	75.93 199	64.24 97	73.49 213	88.93 105	57.89 201	62.46 319	59.75 170	91.55 101	62.67 347
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
plane_prior						65.18 107	80.06 85		61.88 119						89.91 142

DeepC-MVS_fast	69.89 7	77.17 84	76.33 95	79.70 50	83.90 95	67.94 84	80.06 85	83.75 80	56.73 165	74.88 193	85.32 177	65.54 128	87.79 2	65.61 119	91.14 111	83.35 150
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
NCCC		78.25 75	78.04 79	78.89 65	85.61 68	69.45 72	79.80 87	80.99 125	65.77 77	75.55 185	86.25 161	67.42 108	85.42 52	70.10 82	90.88 121	81.81 187

IS-MVSNet		75.10 105	75.42 106	74.15 128	79.23 159	48.05 233	79.43 88	78.04 177	70.09 52	79.17 131	88.02 124	53.04 227	83.60 87	58.05 180	93.76 65	90.79 20

AdaColmap		74.22 117	74.56 110	73.20 142	81.95 126	60.97 145	79.43 88	80.90 126	65.57 79	72.54 226	81.76 222	70.98 78	85.26 56	47.88 260	90.00 138	73.37 277

OPM-MVS		80.99 46	81.63 51	79.07 60	86.86 48	69.39 74	79.41 90	84.00 79	65.64 78	85.54 49	89.28 91	76.32 33	83.47 90	74.03 55	93.57 69	84.35 123
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
xxxxxxxxxxxxxcwj		80.31 54	80.94 54	78.42 72	87.00 43	67.23 90	79.24 91	88.61 5	56.65 167	84.29 70	89.18 95	73.73 59	83.22 95	76.01 39	93.77 63	84.81 103

save fliter					87.00 43	67.23 90	79.24 91	77.94 179	56.65 167

v7n		79.37 62	80.41 58	76.28 101	78.67 172	55.81 184	79.22 93	82.51 98	70.72 47	87.54 22	92.44 14	68.00 105	81.34 126	72.84 64	91.72 95	91.69 11

ETH3D cwj APD-0.16		78.38 74	78.72 72	77.38 86	80.09 148	66.16 100	79.08 94	86.13 26	57.55 157	80.93 111	87.76 126	71.98 69	82.73 105	72.11 74	92.83 81	83.25 152

DP-MVS		78.44 73	79.29 67	75.90 106	81.86 128	65.33 105	79.05 95	84.63 59	74.83 20	80.41 118	86.27 159	71.68 71	83.45 91	62.45 146	92.40 89	78.92 232

CS-MVS-test		74.89 111	74.23 117	76.86 92	77.01 193	62.94 127	78.98 96	84.61 61	58.62 144	70.17 256	80.80 230	66.74 117	81.96 118	61.74 149	89.40 154	85.69 86

ACMH	63.62 14	77.50 81	80.11 60	69.68 195	79.61 152	56.28 180	78.81 97	83.62 82	63.41 108	87.14 31	90.23 76	76.11 34	73.32 246	67.58 104	94.44 42	79.44 226
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
MSLP-MVS++		74.48 115	75.78 100	70.59 180	84.66 81	62.40 129	78.65 98	84.24 71	60.55 128	77.71 150	81.98 218	63.12 145	77.64 202	62.95 143	88.14 168	71.73 294

AllTest		77.66 79	77.43 84	78.35 73	79.19 161	70.81 61	78.60 99	88.64 3	65.37 83	80.09 122	88.17 119	70.33 81	78.43 183	55.60 199	90.90 119	85.81 80

PS-MVSNAJss		77.54 80	77.35 86	78.13 78	84.88 77	66.37 98	78.55 100	79.59 150	53.48 212	86.29 36	92.43 15	62.39 152	80.25 153	67.90 103	90.61 127	87.77 52

Effi-MVS+-dtu		75.43 100	72.28 151	84.91 2	77.05 189	83.58 1	78.47 101	77.70 181	57.68 152	74.89 192	78.13 269	64.80 136	84.26 78	56.46 191	85.32 209	86.88 65

3Dnovator	65.95 11	71.50 158	71.22 167	72.34 165	73.16 250	63.09 125	78.37 102	78.32 172	57.67 154	72.22 230	84.61 183	54.77 218	78.47 180	60.82 160	81.07 261	75.45 261

ETH3 D test6400		75.73 97	76.00 97	74.92 117	81.75 129	56.93 176	78.31 103	84.60 62	52.83 217	77.15 155	85.14 180	68.59 96	84.03 80	65.44 120	90.20 132	83.82 132

OpenMVS	62.51 15	68.76 191	68.75 191	68.78 212	70.56 274	53.91 196	78.29 104	77.35 186	48.85 259	70.22 255	83.52 197	52.65 230	76.93 208	55.31 203	81.99 248	75.49 260

test_part1		76.97 86	78.21 77	73.25 141	77.87 181	45.76 258	78.27 105	87.26 15	66.69 71	85.31 53	91.43 34	55.95 216	84.24 79	65.71 117	95.43 12	89.75 25

WR-MVS_H		80.22 56	82.17 45	74.39 123	89.46 15	42.69 282	78.24 106	82.24 99	78.21 10	89.57 9	92.10 18	68.05 103	85.59 49	66.04 115	95.62 9	94.88 5

114514_t		73.40 127	73.33 135	73.64 134	84.15 92	57.11 175	78.20 107	80.02 144	43.76 295	72.55 225	86.07 169	64.00 142	83.35 94	60.14 165	91.03 114	80.45 214

PLC	62.01 16	71.79 156	70.28 175	76.33 100	80.31 147	68.63 81	78.18 108	81.24 117	54.57 191	67.09 282	80.63 233	59.44 181	81.74 124	46.91 267	84.17 225	78.63 233
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
CNVR-MVS		78.49 71	78.59 74	78.16 76	85.86 66	67.40 88	78.12 109	81.50 110	63.92 99	77.51 152	86.56 152	68.43 100	84.82 67	73.83 56	91.61 99	82.26 181

TAPA-MVS	65.27 12	75.16 104	74.29 116	77.77 81	74.86 222	68.08 83	77.89 110	84.04 78	55.15 181	76.19 181	83.39 199	66.91 112	80.11 158	60.04 167	90.14 136	85.13 91
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
test_prior4						70.14 68	77.57 111

EPNet		69.10 187	67.32 211	74.46 120	68.33 292	61.27 142	77.56 112	63.57 289	60.95 124	56.62 334	82.75 211	51.53 236	81.24 129	54.36 214	90.20 132	80.88 202
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
RPSCF		75.76 96	74.37 114	79.93 45	74.81 223	77.53 20	77.53 113	79.30 155	59.44 136	78.88 133	89.80 84	71.26 76	73.09 248	57.45 182	80.89 264	89.17 34

CSCG		74.12 118	74.39 113	73.33 139	79.35 156	61.66 136	77.45 114	81.98 104	62.47 116	79.06 132	80.19 240	61.83 157	78.79 174	59.83 169	87.35 182	79.54 225

HQP-NCC					82.37 118		77.32 115		59.08 137	71.58 236

ACMP_Plane					82.37 118		77.32 115		59.08 137	71.58 236

HQP-MVS		75.24 103	75.01 107	75.94 105	82.37 118	58.80 168	77.32 115	84.12 74	59.08 137	71.58 236	85.96 171	58.09 195	85.30 55	67.38 108	89.16 156	83.73 138

DTE-MVSNet		80.35 53	82.89 38	72.74 156	89.84 8	37.34 321	77.16 118	81.81 106	80.45 4	90.92 3	92.95 7	74.57 51	86.12 29	63.65 135	94.68 33	94.76 6

PS-CasMVS		80.41 52	82.86 39	73.07 145	89.93 7	39.21 304	77.15 119	81.28 116	79.74 6	90.87 4	92.73 11	75.03 45	84.93 64	63.83 134	95.19 16	95.07 3

XVG-OURS-SEG-HR		79.62 58	79.99 61	78.49 70	86.46 52	74.79 34	77.15 119	85.39 39	66.73 70	80.39 119	88.85 106	74.43 54	78.33 188	74.73 49	85.79 202	82.35 178

PEN-MVS		80.46 51	82.91 37	73.11 144	89.83 9	39.02 307	77.06 121	82.61 96	80.04 5	90.60 6	92.85 9	74.93 47	85.21 59	63.15 142	95.15 18	95.09 2

CP-MVSNet		79.48 60	81.65 50	72.98 148	89.66 13	39.06 306	76.76 122	80.46 135	78.91 8	90.32 7	91.70 26	68.49 98	84.89 65	63.40 139	95.12 19	95.01 4

SixPastTwentyTwo		75.77 95	76.34 94	74.06 129	81.69 131	54.84 189	76.47 123	75.49 203	64.10 98	87.73 18	92.24 17	50.45 243	81.30 128	67.41 106	91.46 102	86.04 76

TEST9					85.47 69	69.32 76	76.42 124	78.69 165	53.73 209	76.97 158	86.74 142	66.84 113	81.10 132

train_agg		76.38 91	76.55 91	75.86 107	85.47 69	69.32 76	76.42 124	78.69 165	54.00 204	76.97 158	86.74 142	66.60 118	81.10 132	72.50 69	91.56 100	77.15 250

Vis-MVSNet		74.85 113	74.56 110	75.72 108	81.63 132	64.64 112	76.35 126	79.06 158	62.85 112	73.33 216	88.41 112	62.54 150	79.59 164	63.94 133	82.92 240	82.94 161
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
DeepPCF-MVS	71.07 5	78.48 72	77.14 89	82.52 19	84.39 89	77.04 25	76.35 126	84.05 77	56.66 166	80.27 120	85.31 178	68.56 97	87.03 9	67.39 107	91.26 106	83.50 141

XVG-OURS		79.51 59	79.82 62	78.58 69	86.11 62	74.96 33	76.33 128	84.95 49	66.89 66	82.75 90	88.99 103	66.82 114	78.37 186	74.80 47	90.76 126	82.40 177

test_8					85.09 75	67.89 85	76.26 129	78.66 167	54.00 204	76.89 163	86.72 144	66.60 118	80.89 143

agg_prior1		75.89 94	76.41 92	74.31 125	84.44 87	66.02 101	76.12 130	78.62 168	54.40 193	76.95 160	86.85 136	66.44 121	80.34 150	72.45 70	91.42 103	76.57 254

CDPH-MVS		77.33 82	77.06 90	78.14 77	84.21 90	63.98 119	76.07 131	83.45 84	54.20 199	77.68 151	87.18 127	69.98 84	85.37 53	68.01 99	92.72 86	85.08 94

CNLPA		73.44 125	73.03 141	74.66 118	78.27 174	75.29 31	75.99 132	78.49 170	65.39 82	75.67 183	83.22 209	61.23 166	66.77 302	53.70 220	85.33 208	81.92 186

UGNet		70.20 170	69.05 185	73.65 133	76.24 204	63.64 120	75.87 133	72.53 226	61.48 120	60.93 318	86.14 165	52.37 231	77.12 206	50.67 237	85.21 210	80.17 219
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
v10		75.69 98	76.20 96	74.16 127	74.44 234	48.69 224	75.84 134	82.93 91	59.02 140	85.92 41	89.17 97	58.56 190	82.74 104	70.73 79	89.14 159	91.05 16

test_prior3		76.71 89	77.19 87	75.27 114	82.15 123	59.85 158	75.57 135	84.33 66	58.92 141	76.53 174	86.78 139	67.83 106	83.39 92	69.81 85	92.76 84	82.58 172

test_prior2							75.57 135		58.92 141	76.53 174	86.78 139	67.83 106		69.81 85	92.76 84

mvs-test1		73.81 121	70.69 172	83.18 5	77.05 189	81.39 3	75.39 137	77.70 181	57.68 152	71.19 246	74.72 294	64.80 136	83.66 86	56.46 191	81.19 260	84.50 119

PAPR		69.20 185	68.66 194	70.82 177	75.15 218	47.77 237	75.31 138	81.11 120	49.62 253	66.33 284	79.27 252	61.53 161	82.96 101	48.12 258	81.50 258	81.74 188

v8		75.07 106	75.64 102	73.35 138	73.42 246	47.46 242	75.20 139	81.45 112	60.05 131	85.64 45	89.26 92	58.08 197	81.80 122	69.71 88	87.97 173	90.79 20

tttt0517		69.46 180	67.79 206	74.46 120	75.34 214	52.72 202	75.05 140	63.27 291	54.69 188	78.87 134	84.37 187	26.63 359	81.15 130	63.95 131	87.93 174	89.51 27

TSAR-MVS + GP.		73.08 133	71.60 162	77.54 83	78.99 168	70.73 63	74.96 141	69.38 258	60.73 127	74.39 203	78.44 263	57.72 202	82.78 103	60.16 164	89.60 147	79.11 230

MAR-MVS		67.72 205	66.16 220	72.40 164	74.45 233	64.99 110	74.87 142	77.50 185	48.67 260	65.78 288	68.58 348	57.01 209	77.79 199	46.68 270	81.92 249	74.42 270
Zhenyu Xu, Yiguang Liu, Xuelei Shi, Ying Wang, Yunan Zheng: MARMVS: Matching Ambiguity Reduced Multiple View Stereo for Efficient Large Scale Scene Reconstruction. CVPR 2020
无先验							74.82 143	70.94 249	47.75 270				76.85 211	54.47 210		72.09 291

CANet		73.00 138	71.84 156	76.48 98	75.82 211	61.28 141	74.81 144	80.37 138	63.17 110	62.43 308	80.50 235	61.10 168	85.16 62	64.00 130	84.34 224	83.01 160

PVSNet_Blended_VisFu		70.04 171	68.88 188	73.53 137	82.71 115	63.62 121	74.81 144	81.95 105	48.53 261	67.16 281	79.18 255	51.42 237	78.38 185	54.39 213	79.72 279	78.60 234

MCST-MVS		73.42 126	73.34 134	73.63 135	81.28 135	59.17 164	74.80 146	83.13 88	45.50 280	72.84 222	83.78 195	65.15 133	80.99 136	64.54 125	89.09 161	80.73 208

原ACMM2							74.78 147

Anonymous20231211		75.54 99	77.19 87	70.59 180	77.67 186	45.70 260	74.73 148	80.19 141	68.80 56	82.95 85	92.91 8	66.26 122	76.76 213	58.41 178	92.77 83	89.30 30

Effi-MVS+		72.10 153	72.28 151	71.58 170	74.21 239	50.33 213	74.72 149	82.73 93	62.62 113	70.77 249	76.83 279	69.96 85	80.97 138	60.20 162	78.43 289	83.45 147

K. test v3		73.67 122	73.61 129	73.87 131	79.78 150	55.62 187	74.69 150	62.04 300	66.16 76	84.76 63	93.23 5	49.47 249	80.97 138	65.66 118	86.67 195	85.02 96

MG-MVS		70.47 168	71.34 166	67.85 222	79.26 158	40.42 299	74.67 151	75.15 209	58.41 145	68.74 271	88.14 122	56.08 215	83.69 85	59.90 168	81.71 255	79.43 227

UniMVSNet_ETH3D		76.74 88	79.02 68	69.92 194	89.27 20	43.81 270	74.47 152	71.70 232	72.33 37	85.50 50	93.65 3	77.98 22	76.88 210	54.60 209	91.64 97	89.08 35

GeoE		73.14 131	73.77 125	71.26 175	78.09 177	52.64 203	74.32 153	79.56 151	56.32 170	76.35 179	83.36 203	70.76 79	77.96 196	63.32 140	81.84 251	83.18 155

DP-MVS Recon		73.57 124	72.69 145	76.23 102	82.85 113	63.39 122	74.32 153	82.96 90	57.75 151	70.35 253	81.98 218	64.34 141	84.41 76	49.69 244	89.95 140	80.89 201

ambc				70.10 190	77.74 184	50.21 215	74.28 155	77.93 180		79.26 130	88.29 117	54.11 223	79.77 161	64.43 126	91.10 112	80.30 216

nrg030		74.87 112	75.99 99	71.52 172	74.90 221	49.88 220	74.10 156	82.58 97	54.55 192	83.50 81	89.21 94	71.51 72	75.74 222	61.24 153	92.34 90	88.94 40

canonicalmvs		72.29 152	73.38 132	69.04 203	74.23 235	47.37 243	73.93 157	83.18 86	54.36 194	76.61 171	81.64 224	72.03 66	75.34 226	57.12 184	87.28 185	84.40 121

CANet_DTU		64.04 242	63.83 239	64.66 249	68.39 289	42.97 280	73.45 158	74.50 213	52.05 225	54.78 341	75.44 289	43.99 278	70.42 277	53.49 222	78.41 290	80.59 212

ETV-MVS		72.72 145	72.16 154	74.38 124	76.90 197	55.95 181	73.34 159	84.67 56	62.04 117	72.19 231	70.81 328	65.90 126	85.24 58	58.64 175	84.96 216	81.95 185

PCF-MVS	63.80 13	72.70 146	71.69 158	75.72 108	78.10 176	60.01 157	73.04 160	81.50 110	45.34 284	79.66 125	84.35 188	65.15 133	82.65 106	48.70 252	89.38 155	84.50 119
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
Regformer-3		72.86 143	72.28 151	74.62 119	74.74 225	60.18 155	72.91 161	71.76 231	64.74 92	78.42 139	72.07 318	67.00 111	76.28 217	67.97 101	80.91 262	87.39 57

Regformer-4		74.64 114	73.67 126	77.55 82	74.74 225	64.49 115	72.91 161	75.42 205	67.45 63	80.24 121	72.07 318	68.98 93	80.19 157	70.29 81	80.91 262	87.98 50

Regformer-1		74.28 116	73.63 128	76.21 103	74.22 236	64.12 118	72.77 163	75.46 204	66.86 68	79.27 129	72.08 316	69.29 90	78.74 175	68.73 91	84.02 228	85.77 85

Regformer-2		75.32 101	74.47 112	77.88 80	74.22 236	66.65 96	72.77 163	77.54 183	68.47 61	80.44 117	72.08 316	70.60 80	80.97 138	70.08 83	84.02 228	86.01 77

test_0402		78.17 78	79.48 66	74.24 126	83.50 98	59.15 165	72.52 165	74.60 212	75.34 17	88.69 13	91.81 23	75.06 44	82.37 111	65.10 121	88.68 165	81.20 192

EU-MVSNet		60.82 269	60.80 267	60.86 289	68.37 290	41.16 290	72.27 166	68.27 265	26.96 367	69.08 264	75.71 284	32.09 336	67.44 294	55.59 201	78.90 284	73.97 272

EI-MVSNet-Vis-set		72.78 144	71.87 155	75.54 111	74.77 224	59.02 166	72.24 167	71.56 235	63.92 99	78.59 135	71.59 324	66.22 123	78.60 177	67.58 104	80.32 270	89.00 38

v1192		73.40 127	73.42 130	73.32 140	74.65 231	48.67 225	72.21 168	81.73 107	52.76 218	81.85 97	84.56 184	57.12 206	82.24 115	68.58 92	87.33 183	89.06 36

iter_conf05		67.34 211	65.62 223	72.50 161	69.82 280	47.06 247	72.19 169	76.86 191	45.32 285	72.86 221	82.85 210	20.53 372	83.73 84	61.13 156	89.02 162	86.70 68

baseline		73.10 132	73.96 121	70.51 182	71.46 266	46.39 254	72.08 170	84.40 65	55.95 173	76.62 170	86.46 155	67.20 109	78.03 195	64.22 128	87.27 186	87.11 64

EI-MVSNet-UG-set		72.63 147	71.68 159	75.47 112	74.67 228	58.64 171	72.02 171	71.50 236	63.53 104	78.58 137	71.39 327	65.98 124	78.53 178	67.30 110	80.18 272	89.23 32

v1144		73.29 130	73.39 131	73.01 146	74.12 240	48.11 232	72.01 172	81.08 123	53.83 208	81.77 99	84.68 182	58.07 198	81.91 119	68.10 96	86.86 191	88.99 39

dcpmvs_2		71.02 162	72.65 146	66.16 240	76.06 209	50.49 212	71.97 173	79.36 153	50.34 244	82.81 89	83.63 196	64.38 140	67.27 296	61.54 151	83.71 234	80.71 210

GBi-Net		68.30 197	68.79 189	66.81 233	73.14 251	40.68 295	71.96 174	73.03 218	54.81 183	74.72 196	90.36 71	48.63 258	75.20 228	47.12 264	85.37 205	84.54 114

test1		68.30 197	68.79 189	66.81 233	73.14 251	40.68 295	71.96 174	73.03 218	54.81 183	74.72 196	90.36 71	48.63 258	75.20 228	47.12 264	85.37 205	84.54 114

FMVSNet1		71.06 160	72.48 148	66.81 233	77.65 187	40.68 295	71.96 174	73.03 218	61.14 122	79.45 128	90.36 71	60.44 172	75.20 228	50.20 241	88.05 170	84.54 114

v1921920		72.96 141	72.98 142	72.89 152	74.67 228	47.58 240	71.92 177	80.69 129	51.70 229	81.69 103	83.89 193	56.58 212	82.25 114	68.34 94	87.36 181	88.82 43

v144192		72.99 139	73.06 140	72.77 154	74.58 232	47.48 241	71.90 178	80.44 136	51.57 230	81.46 105	84.11 191	58.04 199	82.12 116	67.98 100	87.47 179	88.70 46

v1240		73.06 135	73.14 137	72.84 153	74.74 225	47.27 245	71.88 179	81.11 120	51.80 227	82.28 95	84.21 189	56.22 214	82.34 112	68.82 90	87.17 189	88.91 41

FC-MVSNet-test		73.32 129	74.78 109	68.93 208	79.21 160	36.57 323	71.82 180	79.54 152	57.63 156	82.57 92	90.38 68	59.38 183	78.99 170	57.91 181	94.56 36	91.23 15

IterMVS-LS		73.01 137	73.12 139	72.66 158	73.79 243	49.90 217	71.63 181	78.44 171	58.22 146	80.51 116	86.63 149	58.15 194	79.62 162	62.51 144	88.20 167	88.48 47
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
EG-PatchMatch MVS		70.70 165	70.88 169	70.16 188	82.64 117	58.80 168	71.48 182	73.64 216	54.98 182	76.55 172	81.77 221	61.10 168	78.94 171	54.87 206	80.84 265	72.74 284

LF4IMVS		67.50 207	67.31 212	68.08 220	58.86 352	61.93 132	71.43 183	75.90 200	44.67 290	72.42 227	80.20 239	57.16 204	70.44 276	58.99 174	86.12 199	71.88 292

v2v482		72.55 150	72.58 147	72.43 163	72.92 257	46.72 249	71.41 184	79.13 157	55.27 179	81.17 108	85.25 179	55.41 217	81.13 131	67.25 111	85.46 204	89.43 29

Fast-Effi-MVS+-dtu		70.00 172	68.74 192	73.77 132	73.47 245	64.53 114	71.36 185	78.14 176	55.81 175	68.84 270	74.71 295	65.36 131	75.75 221	52.00 227	79.00 283	81.03 196

新几何2							71.33 186

EI-MVSNet		69.61 178	69.01 187	71.41 174	73.94 241	49.90 217	71.31 187	71.32 240	58.22 146	75.40 188	70.44 330	58.16 193	75.85 218	62.51 144	79.81 276	88.48 47

CVMVSNet		59.21 281	58.44 284	61.51 281	73.94 241	47.76 238	71.31 187	64.56 283	26.91 368	60.34 320	70.44 330	36.24 321	67.65 292	53.57 221	68.66 343	69.12 317

thisisatest0530		67.05 215	65.16 227	72.73 157	73.10 254	50.55 211	71.26 189	63.91 287	50.22 246	74.46 202	80.75 231	26.81 358	80.25 153	59.43 171	86.50 196	87.37 58

旧先验2							71.17 190		45.11 287	78.54 138			61.28 324	59.19 173

FIs		72.56 148	73.80 123	68.84 211	78.74 171	37.74 317	71.02 191	79.83 146	56.12 171	80.88 114	89.45 89	58.18 192	78.28 189	56.63 187	93.36 71	90.51 22

TranMVSNet+NR-MVSNet		76.13 93	77.66 83	71.56 171	84.61 83	42.57 284	70.98 192	78.29 174	68.67 59	83.04 83	89.26 92	72.99 63	80.75 144	55.58 202	95.47 10	91.35 14

casdiffmvs		73.06 135	73.84 122	70.72 178	71.32 267	46.71 250	70.93 193	84.26 70	55.62 177	77.46 153	87.10 128	67.09 110	77.81 198	63.95 131	86.83 192	87.64 54

CR-MVSNet		58.96 282	58.49 283	60.36 292	66.37 306	48.24 230	70.93 193	56.40 322	32.87 352	61.35 312	86.66 146	33.19 329	63.22 318	48.50 255	70.17 335	69.62 312

RPMNet		65.77 221	65.08 233	67.84 223	66.37 306	48.24 230	70.93 193	86.27 22	54.66 189	61.35 312	86.77 141	33.29 328	85.67 48	55.93 196	70.17 335	69.62 312

LFMVS		67.06 214	67.89 204	64.56 250	78.02 178	38.25 312	70.81 196	59.60 306	65.18 87	71.06 247	86.56 152	43.85 279	75.22 227	46.35 271	89.63 146	80.21 218

DPM-MVS		69.98 173	69.22 184	72.26 167	82.69 116	58.82 167	70.53 197	81.23 118	47.79 269	64.16 296	80.21 238	51.32 238	83.12 98	60.14 165	84.95 217	74.83 267

h-mvs33		73.08 133	71.61 161	77.48 84	83.89 96	72.89 49	70.47 198	71.12 247	54.28 195	77.89 145	83.41 198	49.04 252	80.98 137	63.62 136	90.77 125	78.58 235

MVS_111021_LR		72.10 153	71.82 157	72.95 149	79.53 154	73.90 41	70.45 199	66.64 270	56.87 162	76.81 167	81.76 222	68.78 94	71.76 266	61.81 147	83.74 232	73.18 279

UniMVSNet (Re)		75.00 107	75.48 105	73.56 136	83.14 103	47.92 235	70.41 200	81.04 124	63.67 102	79.54 126	86.37 157	62.83 146	81.82 120	57.10 185	95.25 15	90.94 18

TinyColmap		67.98 201	69.28 181	64.08 254	67.98 296	46.82 248	70.04 201	75.26 207	53.05 214	77.36 154	86.79 138	59.39 182	72.59 256	45.64 275	88.01 172	72.83 282

VDDNet		71.60 157	73.13 138	67.02 232	86.29 53	41.11 291	69.97 202	66.50 271	68.72 58	74.74 195	91.70 26	59.90 177	75.81 220	48.58 254	91.72 95	84.15 128

EPNet_dtu		58.93 283	58.52 282	60.16 294	67.91 297	47.70 239	69.97 202	58.02 310	49.73 251	47.28 361	73.02 312	38.14 311	62.34 320	36.57 327	85.99 201	70.43 305
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
MVS_Test		69.84 175	70.71 171	67.24 228	67.49 301	43.25 278	69.87 204	81.22 119	52.69 219	71.57 239	86.68 145	62.09 156	74.51 237	66.05 114	78.74 285	83.96 130

alignmvs		70.54 167	71.00 168	69.15 202	73.50 244	48.04 234	69.85 205	79.62 147	53.94 207	76.54 173	82.00 217	59.00 186	74.68 235	57.32 183	87.21 187	84.72 105

GG-mvs-BLEND				52.24 320	60.64 343	29.21 362	69.73 206	42.41 361		45.47 363	52.33 368	20.43 373	68.16 289	25.52 366	65.42 350	59.36 354

pmmvs-eth3d		64.41 238	63.27 246	67.82 224	75.81 212	60.18 155	69.49 207	62.05 299	38.81 325	74.13 206	82.23 216	43.76 280	68.65 286	42.53 288	80.63 269	74.63 268

DU-MVS		74.91 109	75.57 104	72.93 150	83.50 98	45.79 256	69.47 208	80.14 143	65.22 86	81.74 101	87.08 129	61.82 158	81.07 134	56.21 194	94.98 21	91.93 8

EIA-MVS		68.59 194	67.16 213	72.90 151	75.18 217	55.64 186	69.39 209	81.29 115	52.44 220	64.53 292	70.69 329	60.33 173	82.30 113	54.27 215	76.31 300	80.75 207

PAPM		61.79 263	60.37 270	66.05 241	76.09 207	41.87 287	69.30 210	76.79 194	40.64 317	53.80 347	79.62 248	44.38 276	82.92 102	29.64 355	73.11 321	73.36 278

UniMVSNet_NR-MVSNet		74.90 110	75.65 101	72.64 159	83.04 109	45.79 256	69.26 211	78.81 162	66.66 72	81.74 101	86.88 135	63.26 144	81.07 134	56.21 194	94.98 21	91.05 16

MVP-Stereo		61.56 264	59.22 276	68.58 214	79.28 157	60.44 153	69.20 212	71.57 234	43.58 298	56.42 335	78.37 264	39.57 306	76.46 216	34.86 336	60.16 358	68.86 319
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
hse-mvs2		72.32 151	70.66 173	77.31 89	83.10 108	71.77 52	69.19 213	71.45 238	54.28 195	77.89 145	78.26 265	49.04 252	79.23 166	63.62 136	89.13 160	80.92 200

AUN-MVS		70.22 169	67.88 205	77.22 90	82.96 112	71.61 53	69.08 214	71.39 239	49.17 256	71.70 234	78.07 270	37.62 316	79.21 167	61.81 147	89.15 158	80.82 203

gg-mvs-nofinetune		55.75 295	56.75 295	52.72 319	62.87 331	28.04 364	68.92 215	41.36 368	71.09 44	50.80 353	92.63 12	20.74 371	66.86 299	29.97 353	72.41 323	63.25 344

Baseline_NR-MVSNet		70.62 166	73.19 136	62.92 271	76.97 194	34.44 339	68.84 216	70.88 250	60.25 130	79.50 127	90.53 56	61.82 158	69.11 284	54.67 208	95.27 14	85.22 89

v148		69.38 183	69.39 180	69.36 198	69.14 288	44.56 265	68.83 217	72.70 224	54.79 186	78.59 135	84.12 190	54.69 219	76.74 214	59.40 172	82.20 246	86.79 66

FMVSNet2		67.48 208	68.21 200	65.29 245	73.14 251	38.94 308	68.81 218	71.21 246	54.81 183	76.73 169	86.48 154	48.63 258	74.60 236	47.98 259	86.11 200	82.35 178

MVS_111021_HR		72.98 140	72.97 143	72.99 147	80.82 139	65.47 104	68.81 218	72.77 223	57.67 154	75.76 182	82.38 215	71.01 77	77.17 205	61.38 152	86.15 198	76.32 255

Anonymous20240529		72.56 148	73.79 124	68.86 210	76.89 198	45.21 262	68.80 220	77.25 189	67.16 65	76.89 163	90.44 59	65.95 125	74.19 242	50.75 236	90.00 138	87.18 63

Anonymous20240521		63.55 244	66.07 221	55.99 310	66.18 311	44.04 269	68.77 221	68.80 260	46.99 274	72.57 224	85.84 173	39.87 303	50.22 341	53.40 224	92.23 92	73.71 276

CLD-MVS		72.88 142	72.36 150	74.43 122	77.03 191	54.30 193	68.77 221	83.43 85	52.12 223	76.79 168	74.44 298	69.54 89	83.91 81	55.88 197	93.25 73	85.09 92
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
1314		59.83 277	58.86 280	62.74 272	65.71 314	44.78 264	68.59 223	72.63 225	33.54 351	61.05 316	67.29 354	43.62 281	71.26 269	49.49 246	67.84 346	72.19 290

1121		69.23 184	68.26 197	72.12 168	88.36 37	71.40 55	68.59 223	62.06 298	43.80 294	74.75 194	86.18 162	52.92 228	76.85 211	54.47 210	83.27 238	68.12 320

MVS		60.62 272	59.97 272	62.58 273	68.13 294	47.28 244	68.59 223	73.96 215	32.19 353	59.94 323	68.86 346	50.48 242	77.64 202	41.85 293	75.74 302	62.83 345

OpenMVS_ROB	54.93 17	63.23 248	63.28 245	63.07 267	69.81 281	45.34 261	68.52 226	67.14 267	43.74 296	70.61 251	79.22 253	47.90 262	72.66 252	48.75 251	73.84 319	71.21 300

PM-MVS		64.49 235	63.61 242	67.14 231	76.68 200	75.15 32	68.49 227	42.85 360	51.17 237	77.85 147	80.51 234	45.76 265	66.31 305	52.83 225	76.35 299	59.96 353

BH-untuned		69.39 182	69.46 179	69.18 201	77.96 180	56.88 177	68.47 228	77.53 184	56.77 164	77.79 148	79.63 247	60.30 174	80.20 156	46.04 273	80.65 267	70.47 304

testdata1							68.34 229		57.24 160

tpm2		56.12 293	54.64 306	60.55 291	66.24 309	36.01 327	68.14 230	56.77 320	33.60 350	58.25 329	75.52 288	30.25 351	74.33 240	33.27 342	69.76 339	71.32 297

c3_l		69.82 176	69.89 177	69.61 196	66.24 309	43.48 274	68.12 231	79.61 149	51.43 232	77.72 149	80.18 241	54.61 221	78.15 194	63.62 136	87.50 178	87.20 62

CMPMVS	48.73 20	61.54 265	60.89 265	63.52 261	61.08 340	51.55 206	68.07 232	68.00 266	33.88 346	65.87 286	81.25 226	37.91 314	67.71 291	49.32 247	82.60 243	71.31 298
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
test222					87.30 41	69.15 79	67.85 233	59.59 307	41.06 313	73.05 220	85.72 175	48.03 261			80.65 267	66.92 326

VDD-MVS		70.81 164	71.44 165	68.91 209	79.07 166	46.51 251	67.82 234	70.83 251	61.23 121	74.07 208	88.69 107	59.86 178	75.62 223	51.11 233	90.28 131	84.61 110

ab-mvs		64.11 241	65.13 230	61.05 286	71.99 263	38.03 316	67.59 235	68.79 261	49.08 258	65.32 289	86.26 160	58.02 200	66.85 300	39.33 305	79.79 278	78.27 239

eth_miper_zixun_eth		69.42 181	68.73 193	71.50 173	67.99 295	46.42 252	67.58 236	78.81 162	50.72 241	78.13 143	80.34 237	50.15 245	80.34 150	60.18 163	84.65 218	87.74 53

CostFormer		57.35 291	56.14 299	60.97 287	63.76 328	38.43 309	67.50 237	60.22 304	37.14 332	59.12 326	76.34 282	32.78 331	71.99 263	39.12 307	69.27 340	72.47 286

Patchmtry		60.91 268	63.01 249	54.62 313	66.10 312	26.27 369	67.47 238	56.40 322	54.05 203	72.04 232	86.66 146	33.19 329	60.17 326	43.69 283	87.45 180	77.42 248

USDC		62.80 253	63.10 248	61.89 278	65.19 317	43.30 277	67.42 239	74.20 214	35.80 338	72.25 229	84.48 186	45.67 267	71.95 264	37.95 317	84.97 213	70.42 306

xiu_mvs_v1_base_debu		67.87 202	67.07 214	70.26 185	79.13 163	61.90 133	67.34 240	71.25 243	47.98 265	67.70 275	74.19 303	61.31 163	72.62 253	56.51 188	78.26 291	76.27 256

xiu_mvs_v1_base		67.87 202	67.07 214	70.26 185	79.13 163	61.90 133	67.34 240	71.25 243	47.98 265	67.70 275	74.19 303	61.31 163	72.62 253	56.51 188	78.26 291	76.27 256

xiu_mvs_v1_base_debi		67.87 202	67.07 214	70.26 185	79.13 163	61.90 133	67.34 240	71.25 243	47.98 265	67.70 275	74.19 303	61.31 163	72.62 253	56.51 188	78.26 291	76.27 256

test2506		61.23 266	60.85 266	62.38 275	78.80 169	27.88 365	67.33 243	37.42 373	54.23 197	67.55 278	88.68 108	17.87 377	74.39 239	46.33 272	89.41 152	84.86 99

Vis-MVSNet (Re-imp)		62.74 254	63.21 247	61.34 284	72.19 261	31.56 352	67.31 244	53.87 330	53.60 210	69.88 259	83.37 201	40.52 300	70.98 271	41.40 295	86.78 193	81.48 191

jason		64.47 236	62.84 250	69.34 200	76.91 196	59.20 161	67.15 245	65.67 273	35.29 339	65.16 290	76.74 280	44.67 274	70.68 272	54.74 207	79.28 282	78.14 242
jason: jason.
miper_ehance_all_eth		68.36 196	68.16 202	68.98 205	65.14 320	43.34 276	67.07 246	78.92 161	49.11 257	76.21 180	77.72 272	53.48 225	77.92 197	61.16 155	84.59 220	85.68 87

pmmvs6		71.82 155	73.66 127	66.31 239	75.94 210	42.01 286	66.99 247	72.53 226	63.45 106	76.43 177	92.78 10	72.95 64	69.69 280	51.41 231	90.46 129	87.22 60

ECVR-MVS		64.82 229	65.22 225	63.60 259	78.80 169	31.14 355	66.97 248	56.47 321	54.23 197	69.94 258	88.68 108	37.23 317	74.81 234	45.28 278	89.41 152	84.86 99

PatchmatchNet		54.60 301	54.27 307	55.59 311	65.17 319	39.08 305	66.92 249	51.80 341	39.89 319	58.39 327	73.12 311	31.69 339	58.33 330	43.01 287	58.38 364	69.38 315
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
MSDG		67.47 209	67.48 210	67.46 226	70.70 271	54.69 191	66.90 250	78.17 175	60.88 125	70.41 252	74.76 292	61.22 167	73.18 247	47.38 263	76.87 297	74.49 269

cl22		67.14 212	66.51 218	69.03 204	63.20 330	43.46 275	66.88 251	76.25 196	49.22 255	74.48 201	77.88 271	45.49 269	77.40 204	60.64 161	84.59 220	86.24 72

TAMVS		65.31 224	63.75 240	69.97 193	82.23 122	59.76 160	66.78 252	63.37 290	45.20 286	69.79 260	79.37 251	47.42 264	72.17 259	34.48 337	85.15 212	77.99 246

test_post1							66.63 253				2.08 376	30.66 349	59.33 328	40.34 302

FMVSNet3		65.00 228	65.16 227	64.52 251	69.47 284	37.56 320	66.63 253	70.38 253	51.55 231	74.72 196	83.27 206	37.89 315	74.44 238	47.12 264	85.37 205	81.57 190

mvs_anonymous		65.08 227	65.49 224	63.83 257	63.79 327	37.60 319	66.52 255	69.82 256	43.44 299	73.46 214	86.08 168	58.79 189	71.75 267	51.90 228	75.63 304	82.15 182

wuyk23d		61.97 260	66.25 219	49.12 330	58.19 356	60.77 151	66.32 256	52.97 337	55.93 174	90.62 5	86.91 134	73.07 62	35.98 370	20.63 372	91.63 98	50.62 361

tpm cat1		54.02 305	52.63 313	58.19 304	64.85 323	39.86 302	66.26 257	57.28 315	32.16 354	56.90 332	70.39 332	32.75 332	65.30 308	34.29 338	58.79 361	69.41 314

Fast-Effi-MVS+		68.81 190	68.30 196	70.35 184	74.66 230	48.61 226	66.06 258	78.32 172	50.62 242	71.48 242	75.54 286	68.75 95	79.59 164	50.55 239	78.73 286	82.86 164

V42		71.06 160	70.83 170	71.72 169	67.25 302	47.14 246	65.94 259	80.35 139	51.35 233	83.40 82	83.23 207	59.25 184	78.80 173	65.91 116	80.81 266	89.23 32

cl____		68.26 200	68.26 197	68.29 217	64.98 321	43.67 272	65.89 260	74.67 210	50.04 249	76.86 165	82.42 214	48.74 256	75.38 224	60.92 159	89.81 143	85.80 84

DIV-MVS_self_test		68.27 199	68.26 197	68.29 217	64.98 321	43.67 272	65.89 260	74.67 210	50.04 249	76.86 165	82.43 213	48.74 256	75.38 224	60.94 158	89.81 143	85.81 80

tpmvs		55.84 294	55.45 304	57.01 307	60.33 344	33.20 346	65.89 260	59.29 308	47.52 272	56.04 336	73.60 306	31.05 346	68.06 290	40.64 300	64.64 351	69.77 310

lupinMVS		63.36 245	61.49 260	68.97 206	74.93 219	59.19 162	65.80 263	64.52 284	34.68 344	63.53 304	74.25 301	43.19 283	70.62 273	53.88 219	78.67 287	77.10 251

TransMVSNet (Re)		69.62 177	71.63 160	63.57 260	76.51 201	35.93 329	65.75 264	71.29 242	61.05 123	75.02 190	89.90 83	65.88 127	70.41 278	49.79 243	89.48 150	84.38 122

NR-MVSNet		73.62 123	74.05 119	72.33 166	83.50 98	43.71 271	65.65 265	77.32 187	64.32 96	75.59 184	87.08 129	62.45 151	81.34 126	54.90 205	95.63 8	91.93 8

BH-w/o		64.81 230	64.29 236	66.36 238	76.08 208	54.71 190	65.61 266	75.23 208	50.10 248	71.05 248	71.86 323	54.33 222	79.02 169	38.20 315	76.14 301	65.36 335

PVSNet_BlendedMVS		65.38 223	64.30 235	68.61 213	69.81 281	49.36 221	65.60 267	78.96 159	45.50 280	59.98 321	78.61 261	51.82 233	78.20 191	44.30 279	84.11 226	78.27 239

test1111		64.62 232	65.19 226	62.93 270	79.01 167	29.91 359	65.45 268	54.41 329	54.09 202	71.47 243	88.48 111	37.02 318	74.29 241	46.83 269	89.94 141	84.58 113

thres100view900		61.17 267	61.09 263	61.39 283	72.14 262	35.01 335	65.42 269	56.99 318	55.23 180	70.71 250	79.90 243	32.07 337	72.09 260	35.61 333	81.73 252	77.08 252

CDS-MVSNet		64.33 239	62.66 252	69.35 199	80.44 145	58.28 172	65.26 270	65.66 274	44.36 291	67.30 280	75.54 286	43.27 282	71.77 265	37.68 318	84.44 223	78.01 245
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
SCA		58.57 286	58.04 286	60.17 293	70.17 278	41.07 292	65.19 271	53.38 335	43.34 302	61.00 317	73.48 307	45.20 270	69.38 282	40.34 302	70.31 334	70.05 307

HY-MVS	49.31 19	57.96 288	57.59 289	59.10 299	66.85 305	36.17 326	65.13 272	65.39 277	39.24 322	54.69 343	78.14 268	44.28 277	67.18 297	33.75 341	70.79 331	73.95 273

ET-MVSNet_ETH3D		63.32 246	60.69 268	71.20 176	70.15 279	55.66 185	65.02 273	64.32 285	43.28 303	68.99 266	72.05 322	25.46 365	78.19 193	54.16 217	82.80 241	79.74 224

diffmvs		67.42 210	67.50 209	67.20 229	62.26 334	45.21 262	64.87 274	77.04 190	48.21 262	71.74 233	79.70 246	58.40 191	71.17 270	64.99 122	80.27 271	85.22 89

miper_enhance_ethall		65.86 220	65.05 234	68.28 219	61.62 338	42.62 283	64.74 275	77.97 178	42.52 304	73.42 215	72.79 313	49.66 247	77.68 201	58.12 179	84.59 220	84.54 114

thres600view7		61.82 262	61.38 261	63.12 266	71.81 264	34.93 336	64.64 276	56.99 318	54.78 187	70.33 254	79.74 245	32.07 337	72.42 258	38.61 311	83.46 236	82.02 183

BH-RMVSNet		68.69 193	68.20 201	70.14 189	76.40 202	53.90 197	64.62 277	73.48 217	58.01 148	73.91 210	81.78 220	59.09 185	78.22 190	48.59 253	77.96 294	78.31 238

pm-mvs1		68.40 195	69.85 178	64.04 256	73.10 254	39.94 301	64.61 278	70.50 252	55.52 178	73.97 209	89.33 90	63.91 143	68.38 288	49.68 245	88.02 171	83.81 134

pmmvs4		60.78 270	59.04 278	66.00 242	73.06 256	57.67 174	64.53 279	60.22 304	36.91 333	65.96 285	77.27 276	39.66 305	68.54 287	38.87 308	74.89 311	71.80 293

WR-MVS		71.20 159	72.48 148	67.36 227	84.98 76	35.70 331	64.43 280	68.66 262	65.05 89	81.49 104	86.43 156	57.57 203	76.48 215	50.36 240	93.32 72	89.90 24

tpmrst		50.15 319	51.38 319	46.45 337	56.05 362	24.77 371	64.40 281	49.98 345	36.14 335	53.32 348	69.59 339	35.16 323	48.69 344	39.24 306	58.51 363	65.89 332

VPA-MVSNet		68.71 192	70.37 174	63.72 258	76.13 206	38.06 315	64.10 282	71.48 237	56.60 169	74.10 207	88.31 116	64.78 138	69.72 279	47.69 262	90.15 135	83.37 149

MIMVSNet1		66.57 216	69.23 183	58.59 302	81.26 136	37.73 318	64.06 283	57.62 311	57.02 161	78.40 140	90.75 48	62.65 147	58.10 332	41.77 294	89.58 149	79.95 220

MVS_0304		62.51 257	62.27 254	63.25 264	69.39 285	48.47 227	64.05 284	62.48 293	59.69 135	54.10 346	81.04 228	45.71 266	66.31 305	41.38 296	82.58 244	74.96 266

IterMVS		63.12 249	62.48 253	65.02 248	66.34 308	52.86 201	63.81 285	62.25 294	46.57 277	71.51 241	80.40 236	44.60 275	66.82 301	51.38 232	75.47 306	75.38 263
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
IterMVS-SCA-FT		67.68 206	66.07 221	72.49 162	73.34 248	58.20 173	63.80 286	65.55 276	48.10 264	76.91 162	82.64 212	45.20 270	78.84 172	61.20 154	77.89 295	80.44 215

DELS-MVS		68.83 189	68.31 195	70.38 183	70.55 275	48.31 228	63.78 287	82.13 100	54.00 204	68.96 267	75.17 290	58.95 187	80.06 159	58.55 176	82.74 242	82.76 167
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
xiu_mvs_v2_base		64.43 237	63.96 238	65.85 244	77.72 185	51.32 208	63.63 288	72.31 229	45.06 289	61.70 309	69.66 338	62.56 148	73.93 245	49.06 249	73.91 317	72.31 288

tfpnnormal		66.48 217	67.93 203	62.16 277	73.40 247	36.65 322	63.45 289	64.99 279	55.97 172	72.82 223	87.80 125	57.06 208	69.10 285	48.31 257	87.54 176	80.72 209

TR-MVS		64.59 233	63.54 243	67.73 225	75.75 213	50.83 210	63.39 290	70.29 254	49.33 254	71.55 240	74.55 296	50.94 239	78.46 181	40.43 301	75.69 303	73.89 274

PS-MVSNAJ		64.27 240	63.73 241	65.90 243	77.82 183	51.42 207	63.33 291	72.33 228	45.09 288	61.60 310	68.04 349	62.39 152	73.95 244	49.07 248	73.87 318	72.34 287

tfpn200view9		60.35 274	59.97 272	61.51 281	70.78 269	35.35 333	63.27 292	57.47 312	53.00 215	68.31 272	77.09 277	32.45 334	72.09 260	35.61 333	81.73 252	77.08 252

thres400		60.77 271	59.97 272	63.15 265	70.78 269	35.35 333	63.27 292	57.47 312	53.00 215	68.31 272	77.09 277	32.45 334	72.09 260	35.61 333	81.73 252	82.02 183

test_yl		65.11 225	65.09 231	65.18 246	70.59 272	40.86 293	63.22 294	72.79 221	57.91 149	68.88 268	79.07 258	42.85 286	74.89 232	45.50 276	84.97 213	79.81 221

DCV-MVSNet		65.11 225	65.09 231	65.18 246	70.59 272	40.86 293	63.22 294	72.79 221	57.91 149	68.88 268	79.07 258	42.85 286	74.89 232	45.50 276	84.97 213	79.81 221

baseline1		57.82 289	58.36 285	56.19 309	69.17 287	30.76 357	62.94 296	55.21 325	46.04 279	63.83 300	78.47 262	41.20 294	63.68 315	39.44 304	68.99 341	74.13 271

baseline2		55.57 298	52.74 312	64.05 255	65.26 316	44.11 268	62.38 297	54.43 328	39.03 323	51.21 351	67.35 353	33.66 327	72.45 257	37.14 323	64.22 353	75.60 259

FPMVS		59.43 280	60.07 271	57.51 306	77.62 188	71.52 54	62.33 298	50.92 342	57.40 159	69.40 262	80.00 242	39.14 307	61.92 322	37.47 321	66.36 348	39.09 370

PatchMatch-RL		58.68 285	57.72 288	61.57 280	76.21 205	73.59 44	61.83 299	49.00 349	47.30 273	61.08 314	68.97 343	50.16 244	59.01 329	36.06 332	68.84 342	52.10 360

cascas		64.59 233	62.77 251	70.05 191	75.27 215	50.02 216	61.79 300	71.61 233	42.46 305	63.68 302	68.89 345	49.33 251	80.35 149	47.82 261	84.05 227	79.78 223

LCM-MVSNet-Re		69.10 187	71.57 163	61.70 279	70.37 276	34.30 341	61.45 301	79.62 147	56.81 163	89.59 8	88.16 121	68.44 99	72.94 249	42.30 289	87.33 183	77.85 247

1112_ss		59.48 279	58.99 279	60.96 288	77.84 182	42.39 285	61.42 302	68.45 264	37.96 328	59.93 324	67.46 351	45.11 272	65.07 309	40.89 299	71.81 326	75.41 262

IB-MVS	49.67 18	59.69 278	56.96 293	67.90 221	68.19 293	50.30 214	61.42 302	65.18 278	47.57 271	55.83 338	67.15 355	23.77 369	79.60 163	43.56 285	79.97 274	73.79 275
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
PVSNet_Blended		62.90 252	61.64 257	66.69 236	69.81 281	49.36 221	61.23 304	78.96 159	42.04 306	59.98 321	68.86 346	51.82 233	78.20 191	44.30 279	77.77 296	72.52 285

GA-MVS		62.91 251	61.66 256	66.66 237	67.09 304	44.49 266	61.18 305	69.36 259	51.33 234	69.33 263	74.47 297	36.83 319	74.94 231	50.60 238	74.72 312	80.57 213

MS-PatchMatch		55.59 297	54.89 305	57.68 305	69.18 286	49.05 223	61.00 306	62.93 292	35.98 336	58.36 328	68.93 344	36.71 320	66.59 303	37.62 320	63.30 354	57.39 356

patch_mono-2		62.73 255	64.08 237	58.68 301	70.36 277	55.87 183	60.84 307	64.11 286	41.23 311	64.04 297	78.22 266	60.00 175	48.80 343	54.17 216	83.71 234	71.37 296

MVSTER		63.29 247	61.60 259	68.36 215	59.77 349	46.21 255	60.62 308	71.32 240	41.83 307	75.40 188	79.12 256	30.25 351	75.85 218	56.30 193	79.81 276	83.03 159

thisisatest0515		60.48 273	57.86 287	68.34 216	67.25 302	46.42 252	60.58 309	62.14 295	40.82 315	63.58 303	69.12 341	26.28 361	78.34 187	48.83 250	82.13 247	80.26 217

tpm		50.60 317	52.42 315	45.14 342	65.18 318	26.29 368	60.30 310	43.50 358	37.41 330	57.01 331	79.09 257	30.20 353	42.32 363	32.77 344	66.36 348	66.81 329

VPNet		65.58 222	67.56 207	59.65 296	79.72 151	30.17 358	60.27 311	62.14 295	54.19 200	71.24 244	86.63 149	58.80 188	67.62 293	44.17 282	90.87 122	81.18 193

MIMVSNet		54.39 302	56.12 300	49.20 328	72.57 258	30.91 356	59.98 312	48.43 351	41.66 308	55.94 337	83.86 194	41.19 295	50.42 340	26.05 362	75.38 308	66.27 331

HyFIR lowres test		63.01 250	60.47 269	70.61 179	83.04 109	54.10 194	59.93 313	72.24 230	33.67 349	69.00 265	75.63 285	38.69 309	76.93 208	36.60 326	75.45 307	80.81 206

Patchmatch-RL test		59.95 276	59.12 277	62.44 274	72.46 259	54.61 192	59.63 314	47.51 353	41.05 314	74.58 200	74.30 300	31.06 345	65.31 307	51.61 229	79.85 275	67.39 323

PatchT		53.35 307	56.47 297	43.99 346	64.19 325	17.46 377	59.15 315	43.10 359	52.11 224	54.74 342	86.95 133	29.97 354	49.98 342	43.62 284	74.40 315	64.53 343

JIA-IIPM		54.03 304	51.62 316	61.25 285	59.14 351	55.21 188	59.10 316	47.72 352	50.85 239	50.31 357	85.81 174	20.10 374	63.97 313	36.16 331	55.41 369	64.55 342

Anonymous202405211		66.02 219	66.89 217	63.43 263	74.22 236	38.14 313	59.00 317	66.13 272	63.33 109	69.76 261	85.95 172	51.88 232	70.50 275	44.23 281	87.52 177	81.64 189

MDTV_nov1_ep13			54.05 308		65.54 315	29.30 361	59.00 317	55.22 324	35.96 337	52.44 349	75.98 283	30.77 348	59.62 327	38.21 314	73.33 320

thres200		57.55 290	57.02 292	59.17 298	67.89 298	34.93 336	58.91 319	57.25 316	50.24 245	64.01 298	71.46 326	32.49 333	71.39 268	31.31 347	79.57 280	71.19 301

ANet_high		67.08 213	69.94 176	58.51 303	57.55 357	27.09 366	58.43 320	76.80 193	63.56 103	82.40 94	91.93 21	59.82 179	64.98 310	50.10 242	88.86 164	83.46 146

ppachtmachnet_test		60.26 275	59.61 275	62.20 276	67.70 299	44.33 267	58.18 321	60.96 303	40.75 316	65.80 287	72.57 314	41.23 293	63.92 314	46.87 268	82.42 245	78.33 237

KD-MVS_self_test		66.38 218	67.51 208	62.97 269	61.76 336	34.39 340	58.11 322	75.30 206	50.84 240	77.12 157	85.42 176	56.84 210	69.44 281	51.07 234	91.16 109	85.08 94

Test_1112_low_res		58.78 284	58.69 281	59.04 300	79.41 155	38.13 314	57.62 323	66.98 269	34.74 342	59.62 325	77.56 274	42.92 285	63.65 316	38.66 310	70.73 332	75.35 264

VNet		64.01 243	65.15 229	60.57 290	73.28 249	35.61 332	57.60 324	67.08 268	54.61 190	66.76 283	83.37 201	56.28 213	66.87 298	42.19 290	85.20 211	79.23 229

DSMNet-mixed		43.18 336	44.66 337	38.75 354	54.75 369	28.88 363	57.06 325	27.42 379	13.47 373	47.27 362	77.67 273	38.83 308	39.29 369	25.32 367	60.12 359	48.08 363

CL-MVSNet_self_test		62.44 258	63.40 244	59.55 297	72.34 260	32.38 348	56.39 326	64.84 280	51.21 236	67.46 279	81.01 229	50.75 240	63.51 317	38.47 313	88.12 169	82.75 168

D2MVS		62.58 256	61.05 264	67.20 229	63.85 326	47.92 235	56.29 327	69.58 257	39.32 320	70.07 257	78.19 267	34.93 324	72.68 251	53.44 223	83.74 232	81.00 198

FMVSNet5		55.08 300	55.54 303	53.71 314	65.80 313	33.50 345	56.22 328	52.50 339	43.72 297	61.06 315	83.38 200	25.46 365	54.87 335	30.11 352	81.64 257	72.75 283

MVS-HIRNet		45.53 329	47.29 329	40.24 352	62.29 333	26.82 367	56.02 329	37.41 374	29.74 363	43.69 370	81.27 225	33.96 326	55.48 334	24.46 368	56.79 365	38.43 371

pmmvs3		46.71 327	45.09 334	51.55 322	56.76 360	48.25 229	55.78 330	39.53 372	24.13 371	50.35 356	63.40 359	15.90 380	51.08 339	29.29 357	70.69 333	55.33 359

pmmvs5		52.49 311	52.58 314	52.21 321	54.99 368	32.38 348	55.45 331	53.84 331	32.15 355	55.49 340	74.81 291	38.08 312	57.37 333	34.02 339	74.40 315	66.88 327

our_test_3		56.46 292	56.51 296	56.30 308	67.70 299	39.66 303	55.36 332	52.34 340	40.57 318	63.85 299	69.91 337	40.04 302	58.22 331	43.49 286	75.29 310	71.03 303

EPMVS		45.74 328	46.53 331	43.39 347	54.14 372	22.33 374	55.02 333	35.00 376	34.69 343	51.09 352	70.20 334	25.92 363	42.04 365	37.19 322	55.50 368	65.78 333

dp		44.09 335	44.88 336	41.72 351	58.53 354	23.18 373	54.70 334	42.38 363	34.80 341	44.25 368	65.61 357	24.48 368	44.80 355	29.77 354	49.42 371	57.18 357

CHOSEN 1792x2688		58.09 287	56.30 298	63.45 262	79.95 149	50.93 209	54.07 335	65.59 275	28.56 364	61.53 311	74.33 299	41.09 296	66.52 304	33.91 340	67.69 347	72.92 281

MDTV_nov1_ep13_2view						18.41 376	53.74 336		31.57 359	44.89 365		29.90 355		32.93 343		71.48 295

test-LLR		50.43 318	50.69 323	49.64 326	60.76 341	41.87 287	53.18 337	45.48 356	43.41 300	49.41 358	60.47 363	29.22 356	44.73 356	42.09 291	72.14 324	62.33 349

TESTMET0.1,1		45.17 330	44.93 335	45.89 339	56.02 363	38.31 310	53.18 337	41.94 366	27.85 365	44.86 366	56.47 365	17.93 376	41.50 367	38.08 316	68.06 344	57.85 355

test-mter		48.56 323	48.20 328	49.64 326	60.76 341	41.87 287	53.18 337	45.48 356	31.91 358	49.41 358	60.47 363	18.34 375	44.73 356	42.09 291	72.14 324	62.33 349

Anonymous20231206		54.13 303	55.82 301	49.04 331	70.89 268	35.96 328	51.73 340	50.87 343	34.86 340	62.49 307	79.22 253	42.52 289	44.29 358	27.95 360	81.88 250	66.88 327

XXY-MVS		55.19 299	57.40 291	48.56 332	64.45 324	34.84 338	51.54 341	53.59 332	38.99 324	63.79 301	79.43 249	56.59 211	45.57 350	36.92 325	71.29 328	65.25 336

test20.03		55.74 296	57.51 290	50.42 323	59.89 348	32.09 350	50.63 342	49.01 348	50.11 247	65.07 291	83.23 207	45.61 268	48.11 346	30.22 351	83.82 231	71.07 302

UnsupCasMVSNet_eth		52.26 312	53.29 311	49.16 329	55.08 367	33.67 344	50.03 343	58.79 309	37.67 329	63.43 306	74.75 293	41.82 291	45.83 349	38.59 312	59.42 360	67.98 322

testgi		54.00 306	56.86 294	45.45 340	58.20 355	25.81 370	49.05 344	49.50 347	45.43 283	67.84 274	81.17 227	51.81 235	43.20 362	29.30 356	79.41 281	67.34 325

Patchmatch-test		47.93 324	49.96 325	41.84 349	57.42 358	24.26 372	48.75 345	41.49 367	39.30 321	56.79 333	73.48 307	30.48 350	33.87 371	29.29 357	72.61 322	67.39 323

UnsupCasMVSNet_bld		50.01 320	51.03 322	46.95 333	58.61 353	32.64 347	48.31 346	53.27 336	34.27 345	60.47 319	71.53 325	41.40 292	47.07 347	30.68 349	60.78 357	61.13 351

PVSNet	43.83 21	51.56 316	51.17 320	52.73 318	68.34 291	38.27 311	48.22 347	53.56 333	36.41 334	54.29 344	64.94 358	34.60 325	54.20 338	30.34 350	69.87 337	65.71 334

MDA-MVSNet-bldmvs		62.34 259	61.73 255	64.16 252	61.64 337	49.90 217	48.11 348	57.24 317	53.31 213	80.95 110	79.39 250	49.00 254	61.55 323	45.92 274	80.05 273	81.03 196

PMMVS		44.69 332	43.95 339	46.92 334	50.05 376	53.47 199	48.08 349	42.40 362	22.36 372	44.01 369	53.05 367	42.60 288	45.49 351	31.69 346	61.36 356	41.79 368

miper_lstm_enhance		61.97 260	61.63 258	62.98 268	60.04 345	45.74 259	47.53 350	70.95 248	44.04 292	73.06 219	78.84 260	39.72 304	60.33 325	55.82 198	84.64 219	82.88 162

ADS-MVSNet2		48.76 322	47.25 330	53.29 317	55.90 364	40.54 298	47.34 351	54.99 327	31.41 360	50.48 354	72.06 320	31.23 342	54.26 337	25.93 363	55.93 366	65.07 337

ADS-MVSNet		44.62 333	45.58 332	41.73 350	55.90 364	20.83 375	47.34 351	39.94 371	31.41 360	50.48 354	72.06 320	31.23 342	39.31 368	25.93 363	55.93 366	65.07 337

WTY-MVS		49.39 321	50.31 324	46.62 336	61.22 339	32.00 351	46.61 353	49.77 346	33.87 347	54.12 345	69.55 340	41.96 290	45.40 352	31.28 348	64.42 352	62.47 348

test0.0.03 1		47.72 325	48.31 327	45.93 338	55.53 366	29.39 360	46.40 354	41.21 369	43.41 300	55.81 339	67.65 350	29.22 356	43.77 361	25.73 365	69.87 337	64.62 341

test123		4.43 347	5.78 350	0.39 361	0.97 383	0.28 384	46.33 355	0.45 384	0.31 378	0.62 379	1.50 378	0.61 384	0.11 380	0.56 377	0.63 377	0.77 376

sss		47.59 326	48.32 326	45.40 341	56.73 361	33.96 342	45.17 356	48.51 350	32.11 357	52.37 350	65.79 356	40.39 301	41.91 366	31.85 345	61.97 355	60.35 352

KD-MVS_2432*1600		52.05 314	51.58 317	53.44 315	52.11 373	31.20 353	44.88 357	64.83 281	41.53 309	64.37 293	70.03 335	15.61 381	64.20 311	36.25 328	74.61 313	64.93 339

miper_refine_blended		52.05 314	51.58 317	53.44 315	52.11 373	31.20 353	44.88 357	64.83 281	41.53 309	64.37 293	70.03 335	15.61 381	64.20 311	36.25 328	74.61 313	64.93 339

testmvs		4.06 348	5.28 351	0.41 360	0.64 384	0.16 385	42.54 359	0.31 385	0.26 379	0.50 380	1.40 379	0.77 383	0.17 379	0.56 377	0.55 378	0.90 375

PVSNet_0	36.71 22	41.12 338	40.78 341	42.14 348	59.97 346	40.13 300	40.97 360	42.24 365	30.81 362	44.86 366	49.41 370	40.70 299	45.12 354	23.15 369	34.96 373	41.16 369

YYNet1		52.58 309	53.50 309	49.85 324	54.15 371	36.45 325	40.53 361	46.55 355	38.09 327	75.52 186	73.31 310	41.08 297	43.88 359	41.10 297	71.14 330	69.21 316

MDA-MVSNet_test_wron		52.57 310	53.49 310	49.81 325	54.24 370	36.47 324	40.48 362	46.58 354	38.13 326	75.47 187	73.32 309	41.05 298	43.85 360	40.98 298	71.20 329	69.10 318

new_pmnet		37.55 340	39.80 343	30.79 355	56.83 359	16.46 378	39.35 363	30.65 377	25.59 369	45.26 364	61.60 362	24.54 367	28.02 374	21.60 370	52.80 370	47.90 364

E-PMN		45.17 330	45.36 333	44.60 344	50.07 375	42.75 281	38.66 364	42.29 364	46.39 278	39.55 371	51.15 369	26.00 362	45.37 353	37.68 318	76.41 298	45.69 367

EMVS		44.61 334	44.45 338	45.10 343	48.91 377	43.00 279	37.92 365	41.10 370	46.75 276	38.00 373	48.43 371	26.42 360	46.27 348	37.11 324	75.38 308	46.03 366

N_pmnet		52.06 313	51.11 321	54.92 312	59.64 350	71.03 59	37.42 366	61.62 302	33.68 348	57.12 330	72.10 315	37.94 313	31.03 372	29.13 359	71.35 327	62.70 346

new-patchmatchnet		52.89 308	55.76 302	44.26 345	59.94 347	6.31 380	37.36 367	50.76 344	41.10 312	64.28 295	79.82 244	44.77 273	48.43 345	36.24 330	87.61 175	78.03 244

CHOSEN 280x420		41.62 337	39.89 342	46.80 335	61.81 335	51.59 205	33.56 368	35.74 375	27.48 366	37.64 374	53.53 366	23.24 370	42.09 364	27.39 361	58.64 362	46.72 365

PMMVS2		37.74 339	40.87 340	28.36 356	42.41 379	5.35 381	24.61 369	27.75 378	32.15 355	47.85 360	70.27 333	35.85 322	29.51 373	19.08 373	67.85 345	50.22 362

MVE	27.91 23	36.69 341	35.64 344	39.84 353	43.37 378	35.85 330	19.49 370	24.61 380	24.68 370	39.05 372	62.63 361	38.67 310	27.10 375	21.04 371	47.25 372	56.56 358
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
tmp_tt		11.98 344	14.73 347	3.72 359	2.28 382	4.62 382	19.44 371	14.50 382	0.47 377	21.55 375	9.58 375	25.78 364	4.57 378	11.61 375	27.37 374	1.96 374

test_method		19.26 342	19.12 346	19.71 357	9.09 381	1.91 383	7.79 372	53.44 334	1.42 375	10.27 377	35.80 372	17.42 378	25.11 376	12.44 374	24.38 375	32.10 372

test_blank		0.00 349	0.00 352	0.00 362	0.00 385	0.00 386	0.00 373	0.00 386	0.00 380	0.00 381	0.00 380	0.00 385	0.00 381	0.00 379	0.00 379	0.00 377

uanet_test		0.00 349	0.00 352	0.00 362	0.00 385	0.00 386	0.00 373	0.00 386	0.00 380	0.00 381	0.00 380	0.00 385	0.00 381	0.00 379	0.00 379	0.00 377

DCPMVS		0.00 349	0.00 352	0.00 362	0.00 385	0.00 386	0.00 373	0.00 386	0.00 380	0.00 381	0.00 380	0.00 385	0.00 381	0.00 379	0.00 379	0.00 377

cdsmvs_eth3d_5k		17.71 343	23.62 345	0.00 362	0.00 385	0.00 386	0.00 373	70.17 255	0.00 380	0.00 381	74.25 301	68.16 102	0.00 381	0.00 379	0.00 379	0.00 377

pcd_1.5k_mvsjas		5.20 346	6.93 349	0.00 362	0.00 385	0.00 386	0.00 373	0.00 386	0.00 380	0.00 381	0.00 380	62.39 152	0.00 381	0.00 379	0.00 379	0.00 377

sosnet-low-res		0.00 349	0.00 352	0.00 362	0.00 385	0.00 386	0.00 373	0.00 386	0.00 380	0.00 381	0.00 380	0.00 385	0.00 381	0.00 379	0.00 379	0.00 377

sosnet		0.00 349	0.00 352	0.00 362	0.00 385	0.00 386	0.00 373	0.00 386	0.00 380	0.00 381	0.00 380	0.00 385	0.00 381	0.00 379	0.00 379	0.00 377

uncertanet		0.00 349	0.00 352	0.00 362	0.00 385	0.00 386	0.00 373	0.00 386	0.00 380	0.00 381	0.00 380	0.00 385	0.00 381	0.00 379	0.00 379	0.00 377

Regformer		0.00 349	0.00 352	0.00 362	0.00 385	0.00 386	0.00 373	0.00 386	0.00 380	0.00 381	0.00 380	0.00 385	0.00 381	0.00 379	0.00 379	0.00 377

ab-mvs-re		5.62 345	7.50 348	0.00 362	0.00 385	0.00 386	0.00 373	0.00 386	0.00 380	0.00 381	67.46 351	0.00 385	0.00 381	0.00 379	0.00 379	0.00 377

uanet		0.00 349	0.00 352	0.00 362	0.00 385	0.00 386	0.00 373	0.00 386	0.00 380	0.00 381	0.00 380	0.00 385	0.00 381	0.00 379	0.00 379	0.00 377

MSC_two_6792asdad				79.02 61	83.14 103	67.03 92		80.75 127					86.24 22	77.27 35	94.85 26	83.78 135

PC_three_1452									46.98 275	81.83 98	86.28 158	66.55 120	84.47 73	63.31 141	90.78 123	83.49 142

No_MVS				79.02 61	83.14 103	67.03 92		80.75 127					86.24 22	77.27 35	94.85 26	83.78 135

test_one_0601					85.84 67	61.45 139		85.63 32	75.27 19	85.62 48	90.38 68	76.72 29

eth-test2					0.00 385

eth-test					0.00 385

ZD-MVS					83.91 94	69.36 75		81.09 122	58.91 143	82.73 91	89.11 99	75.77 37	86.63 12	72.73 65	92.93 79

IU-MVS					86.12 59	60.90 147		80.38 137	45.49 282	81.31 106				75.64 44	94.39 44	84.65 106

test_241102_TWO								84.80 50	72.61 32	84.93 58	89.70 85	77.73 23	85.89 41	75.29 45	94.22 56	83.25 152

test_241102_ONE					86.12 59	61.06 143		84.72 54	72.64 31	87.38 25	89.47 88	77.48 24	85.74 45

test_0728_THIRD									74.03 23	85.83 43	90.41 63	75.58 39	85.69 46	77.43 33	94.74 31	84.31 124

GSMVS																70.05 307

test_part2					85.90 63	66.44 97				84.61 66

sam_mvs1												31.41 340				70.05 307

sam_mvs												31.21 344

MTGPA								80.63 130

test_post											1.99 377	30.91 347	54.76 336

patchmatchnet-post											68.99 342	31.32 341	69.38 282

gm-plane-assit					62.51 332	33.91 343			37.25 331		62.71 360		72.74 250	38.70 309

test9_res														72.12 73	91.37 104	77.40 249

agg_prior2														70.70 80	90.93 117	78.55 236

agg_prior					84.44 87	66.02 101		78.62 168		76.95 160			80.34 150

TestCases				78.35 73	79.19 161	70.81 61		88.64 3	65.37 83	80.09 122	88.17 119	70.33 81	78.43 183	55.60 199	90.90 119	85.81 80

test_prior				75.27 114	82.15 123	59.85 158		84.33 66					83.39 92			82.58 172

新几何1				69.99 192	88.37 36	71.34 57		62.08 297	43.85 293	74.99 191	86.11 167	52.85 229	70.57 274	50.99 235	83.23 239	68.05 321

旧先验1					84.55 84	60.36 154		63.69 288			87.05 132	54.65 220			83.34 237	69.66 311

原ACMM1				73.90 130	85.90 63	65.15 109		81.67 108	50.97 238	74.25 204	86.16 164	61.60 160	83.54 88	56.75 186	91.08 113	73.00 280

testdata2													67.30 295	48.34 256

segment_acmp												68.30 101

testdata				64.13 253	85.87 65	63.34 123		61.80 301	47.83 268	76.42 178	86.60 151	48.83 255	62.31 321	54.46 212	81.26 259	66.74 330

test12				76.51 97	82.28 121	60.94 146		81.64 109		73.60 211		64.88 135	85.19 61		90.42 130	83.38 148

plane_prior7					85.18 72	66.21 99

plane_prior6					84.18 91	65.31 106						60.83 170

plane_prior5								85.49 34					86.15 27	71.09 77	90.94 115	84.82 101

plane_prior4											89.11 99

plane_prior3						65.67 103			63.82 101	78.23 141

plane_prior1					84.46 86

n2								0.00 386

nn								0.00 386

door-mid								55.02 326

lessismore_v0				72.75 155	79.60 153	56.83 179		57.37 314		83.80 78	89.01 102	47.45 263	78.74 175	64.39 127	86.49 197	82.69 170

LGP-MVS_train				80.90 37	87.00 43	70.41 66		86.35 19	69.77 53	87.75 16	91.13 37	81.83 3	86.20 24	77.13 37	95.96 5	86.08 74

test11								82.71 94

door								52.91 338

HQP5-MVS						58.80 168

BP-MVS														67.38 108

HQP4-MVS										71.59 235			85.31 54			83.74 137

HQP3-MVS								84.12 74							89.16 156

HQP2-MVS												58.09 195

NP-MVS					83.34 102	63.07 126					85.97 170

ACMMP++_ref															89.47 151

ACMMP++															91.96 94

Test By Simon												62.56 148

ITE_SJBPF				80.35 43	76.94 195	73.60 43		80.48 134	66.87 67	83.64 80	86.18 162	70.25 83	79.90 160	61.12 157	88.95 163	87.56 56

DeepMVS_CX				11.83 358	15.51 380	13.86 379		11.25 383	5.76 374	20.85 376	26.46 373	17.06 379	9.22 377	9.69 376	13.82 376	12.42 373

High-resolution multi-view benchmark