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.

MCST-MVS		91.08 1	91.46 2	89.94 2	97.66 2	73.37 7	97.13 1	95.58 10	89.33 1	85.77 23	96.26 7	72.84 9	99.38 1	92.64 4	95.93 4	97.08 4

DELS-MVS		90.05 4	90.09 5	89.94 2	93.14 49	73.88 6	97.01 2	94.40 36	88.32 2	85.71 24	94.91 45	74.11 7	98.91 6	87.26 26	95.94 3	97.03 5
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
DeepPCF-MVS	81.17 1	89.72 5	91.38 3	84.72 103	93.00 52	58.16 253	96.72 3	94.41 35	86.50 5	90.25 3	97.83 1	75.46 5	98.67 12	92.78 2	95.49 7	97.32 1

lupinMVS		87.74 16	87.77 15	87.63 22	89.24 128	71.18 14	96.57 4	92.90 82	82.70 16	87.13 15	95.27 30	64.99 49	95.80 106	89.34 12	91.80 52	95.93 24

CANet		89.61 6	89.99 6	88.46 13	94.39 24	69.71 32	96.53 5	93.78 43	86.89 4	89.68 4	95.78 15	65.94 40	99.10 2	92.99 1	93.91 25	96.58 11

CNVR-MVS		90.32 3	90.89 4	88.61 11	96.76 4	70.65 18	96.47 6	94.83 21	84.83 9	89.07 7	96.80 2	70.86 14	99.06 3	92.64 4	95.71 5	96.12 18

NCCC		89.07 8	89.46 8	87.91 16	96.60 5	69.05 40	96.38 7	94.64 29	84.42 10	86.74 18	96.20 8	66.56 35	98.76 11	89.03 16	94.56 18	95.92 25

PVSNet_Blended		86.73 31	86.86 27	86.31 59	93.76 35	67.53 72	96.33 8	93.61 51	82.34 18	81.00 57	93.08 79	63.19 67	97.29 52	87.08 27	91.38 59	94.13 81

SteuartSystems-ACMMP		86.82 30	86.90 26	86.58 46	90.42 106	66.38 118	96.09 9	93.87 41	77.73 60	84.01 42	95.66 19	63.39 64	97.94 27	87.40 25	93.55 33	95.42 32
Skip Steuart: Steuart Systems R&D Blog.
MVS_0304		88.39 9	88.35 12	88.50 12	93.01 51	70.11 23	95.90 10	92.20 107	86.27 6	88.70 9	95.92 13	56.76 119	99.02 4	92.68 3	93.76 28	96.37 15

PS-MVSNAJ		88.14 10	87.61 17	89.71 4	92.06 72	76.72 1	95.75 11	93.26 66	83.86 11	89.55 5	96.06 11	53.55 167	97.89 30	91.10 6	93.31 35	94.54 66

xiu_mvs_v2_base		87.92 14	87.38 22	89.55 7	91.41 95	76.43 2	95.74 12	93.12 74	83.53 13	89.55 5	95.95 12	53.45 172	97.68 32	91.07 7	92.62 42	94.54 66

DeepC-MVS_fast	79.48 2	87.95 13	88.00 13	87.79 19	95.86 12	68.32 55	95.74 12	94.11 39	83.82 12	83.49 44	96.19 9	64.53 53	98.44 17	83.42 51	94.88 12	96.61 9
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
VNet		86.20 35	85.65 40	87.84 18	93.92 34	69.99 26	95.73 14	95.94 9	78.43 53	86.00 21	93.07 81	58.22 103	97.00 67	85.22 39	84.33 112	96.52 13

jason		86.40 32	86.17 32	87.11 33	86.16 178	70.54 20	95.71 15	92.19 109	82.00 24	84.58 34	94.34 60	61.86 76	95.53 122	87.76 22	90.89 64	95.27 40
jason: jason.
alignmvs		87.28 20	86.97 25	88.24 15	91.30 96	71.14 16	95.61 16	93.56 53	79.30 38	87.07 17	95.25 32	68.43 19	96.93 77	87.87 21	84.33 112	96.65 8

IB-MVS	77.80 4	82.18 83	80.46 94	87.35 27	89.14 130	70.28 22	95.59 17	95.17 14	78.85 47	70.19 157	85.82 170	70.66 16	97.67 33	72.19 122	66.52 224	94.09 84
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
CLD-MVS		82.73 75	82.35 73	83.86 118	87.90 156	67.65 69	95.45 18	92.18 110	85.06 8	72.58 132	92.27 98	52.46 180	95.78 107	84.18 44	79.06 141	88.16 177
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
VDD-MVS		83.06 72	81.81 78	86.81 38	90.86 103	67.70 67	95.40 19	91.50 133	75.46 86	81.78 52	92.34 97	40.09 256	97.13 61	86.85 30	82.04 126	95.60 29

PHI-MVS		86.83 29	86.85 28	86.78 40	93.47 43	65.55 135	95.39 20	95.10 17	71.77 162	85.69 25	96.52 3	62.07 74	98.77 10	86.06 34	95.60 6	96.03 21

EPNet		87.84 15	88.38 10	86.23 61	93.30 44	66.05 125	95.26 21	94.84 20	87.09 3	88.06 11	94.53 52	66.79 33	97.34 50	83.89 48	91.68 54	95.29 38
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
HPM-MVS++		89.37 7	89.95 7	87.64 20	95.10 17	68.23 59	95.24 22	94.49 32	82.43 17	88.90 8	96.35 5	71.89 13	98.63 13	88.76 18	96.40 2	96.06 19

WTY-MVS		86.32 33	85.81 36	87.85 17	92.82 57	69.37 37	95.20 23	95.25 13	82.71 15	81.91 51	94.73 49	67.93 26	97.63 38	79.55 73	82.25 124	96.54 12

3Dnovator+	73.60 7	82.10 87	80.60 92	86.60 44	90.89 102	66.80 99	95.20 23	93.44 59	74.05 110	67.42 200	92.49 92	49.46 202	97.65 37	70.80 135	91.68 54	95.33 35

TSAR-MVS + GP.		87.96 12	88.37 11	86.70 41	93.51 42	65.32 138	95.15 25	93.84 42	78.17 55	85.93 22	94.80 48	75.80 4	98.21 21	89.38 11	88.78 77	96.59 10

DP-MVS Recon		82.73 75	81.65 80	85.98 64	97.31 3	67.06 83	95.15 25	91.99 114	69.08 200	76.50 101	93.89 68	54.48 156	98.20 22	70.76 136	85.66 101	92.69 121

test_prior3		87.38 19	87.70 16	86.42 53	94.71 21	67.35 75	95.10 27	93.10 75	75.40 89	85.25 30	95.61 21	67.94 24	96.84 79	87.47 23	94.77 13	95.05 50

test_prior2							95.10 27		75.40 89	85.25 30	95.61 21	67.94 24		87.47 23	94.77 13

MSLP-MVS++		86.27 34	85.91 35	87.35 27	92.01 73	68.97 43	95.04 29	92.70 87	79.04 46	81.50 54	96.50 4	58.98 100	96.78 81	83.49 50	93.93 24	96.29 16

LFMVS		84.34 54	82.73 69	89.18 8	94.76 19	73.25 8	94.99 30	91.89 118	71.90 153	82.16 50	93.49 74	47.98 216	97.05 62	82.55 55	84.82 105	97.25 2

MG-MVS		87.11 23	86.27 29	89.62 5	97.79 1	76.27 3	94.96 31	94.49 32	78.74 51	83.87 43	92.94 84	64.34 54	96.94 75	75.19 100	94.09 22	95.66 27

APDe-MVS		87.54 17	87.84 14	86.65 42	96.07 9	66.30 121	94.84 32	93.78 43	69.35 197	88.39 10	96.34 6	67.74 28	97.66 36	90.62 9	93.44 34	96.01 22

CP-MVS		83.71 66	83.40 59	84.65 104	93.14 49	63.84 169	94.59 33	92.28 100	71.03 174	77.41 91	94.92 44	55.21 139	96.19 93	81.32 66	90.70 66	93.91 93

VDDNet		80.50 104	78.26 123	87.21 29	86.19 177	69.79 30	94.48 34	91.31 140	60.42 266	79.34 71	90.91 111	38.48 262	96.56 89	82.16 56	81.05 130	95.27 40

MAR-MVS		84.18 56	83.43 57	86.44 52	96.25 7	65.93 128	94.28 35	94.27 38	74.41 100	79.16 74	95.61 21	53.99 162	98.88 9	69.62 144	93.26 36	94.50 69
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
TEST9					94.18 27	67.28 77	94.16 36	93.51 55	71.75 163	85.52 26	95.33 26	68.01 23	97.27 54

train_agg		87.21 22	87.42 21	86.60 44	94.18 27	67.28 77	94.16 36	93.51 55	71.87 155	85.52 26	95.33 26	68.19 21	97.27 54	89.09 13	94.90 10	95.25 43

test_8					94.19 26	67.19 79	94.15 38	93.42 60	71.87 155	85.38 28	95.35 25	68.19 21	96.95 74

agg_prior3		86.93 26	87.08 24	86.48 50	94.21 25	66.95 88	94.14 39	93.40 61	71.80 160	84.86 32	95.13 36	66.16 37	97.25 56	89.09 13	94.90 10	95.25 43

Fast-Effi-MVS+		81.14 96	80.01 96	84.51 109	90.24 110	65.86 129	94.12 40	89.15 213	73.81 118	75.37 109	88.26 141	57.26 111	94.53 146	66.97 165	84.92 104	93.15 110

#test#		84.98 47	84.74 46	85.72 74	93.75 37	65.01 147	94.09 41	93.19 70	73.55 124	79.22 72	94.93 42	59.04 98	97.67 33	82.66 54	92.21 46	94.49 70

agg_prior1		87.02 24	87.26 23	86.28 60	94.16 31	66.97 86	94.08 42	93.31 64	71.85 157	84.49 35	95.39 24	68.91 17	96.75 83	88.84 17	94.32 20	95.13 47

HQP-NCC					87.54 159		94.06 43		79.80 33	74.18 115

ACMP_Plane					87.54 159		94.06 43		79.80 33	74.18 115

PVSNet_BlendedMVS		83.38 67	83.43 57	83.22 131	93.76 35	67.53 72	94.06 43	93.61 51	79.13 43	81.00 57	85.14 176	63.19 67	97.29 52	87.08 27	73.91 179	84.83 237

HQP-MVS		81.14 96	80.64 91	82.64 142	87.54 159	63.66 178	94.06 43	91.70 126	79.80 33	74.18 115	90.30 120	51.63 187	95.61 116	77.63 88	78.90 142	88.63 169

MVS_111021_HR		86.19 36	85.80 37	87.37 26	93.17 48	69.79 30	93.99 47	93.76 46	79.08 45	78.88 76	93.99 66	62.25 73	98.15 24	85.93 35	91.15 62	94.15 80

mvs-test1		78.74 139	77.95 128	81.14 186	83.22 213	57.13 263	93.96 48	87.78 241	75.42 87	72.68 129	90.80 113	45.08 236	94.54 145	75.08 102	77.49 156	91.74 138

Regformer-1		87.24 21	87.60 18	86.15 62	95.14 15	65.83 131	93.95 49	95.12 15	82.11 21	84.25 37	95.73 17	67.88 27	98.35 19	85.60 36	88.64 78	94.26 73

Regformer-2		87.00 25	87.43 20	85.71 76	95.14 15	64.73 150	93.95 49	94.95 18	81.69 26	84.03 41	95.73 17	67.35 31	98.19 23	85.40 38	88.64 78	94.20 75

VPNet		78.82 135	77.53 135	82.70 139	84.52 196	66.44 117	93.93 51	92.23 102	80.46 30	72.60 131	88.38 138	49.18 205	93.13 198	72.47 118	63.97 247	88.55 171

test_prior4						67.18 81	93.92 52

SD-MVS		87.49 18	87.49 19	87.50 24	93.60 39	68.82 46	93.90 53	92.63 92	76.86 71	87.90 12	95.76 16	66.17 36	97.63 38	89.06 15	91.48 58	96.05 20

CDPH-MVS		85.71 41	85.46 41	86.46 51	94.75 20	67.19 79	93.89 54	92.83 84	70.90 176	83.09 46	95.28 29	63.62 61	97.36 48	80.63 68	94.18 21	94.84 58

plane_prior						62.42 196	93.85 55		79.38 37						78.80 144

CSCG		86.87 27	86.26 30	88.72 9	95.05 18	70.79 17	93.83 56	95.33 12	68.48 210	77.63 88	94.35 59	73.04 8	98.45 16	84.92 41	93.71 30	96.92 6

PVSNet_Blended_VisFu		83.97 59	83.50 54	85.39 85	90.02 112	66.59 111	93.77 57	91.73 123	77.43 66	77.08 97	89.81 127	63.77 60	96.97 72	79.67 72	88.21 81	92.60 124

TR-MVS		78.77 138	77.37 140	82.95 134	90.49 105	60.88 215	93.67 58	90.07 182	70.08 191	74.51 114	91.37 108	45.69 232	95.70 115	60.12 220	80.32 133	92.29 131

API-MVS		82.28 82	80.53 93	87.54 23	96.13 8	70.59 19	93.63 59	91.04 150	65.72 232	75.45 108	92.83 88	56.11 130	98.89 8	64.10 191	89.75 74	93.15 110

BH-w/o		80.49 105	79.30 111	84.05 116	90.83 104	64.36 161	93.60 60	89.42 203	74.35 105	69.09 175	90.15 122	55.23 138	95.61 116	64.61 186	86.43 97	92.17 134

APD-MVS		85.93 38	85.99 33	85.76 73	95.98 11	65.21 140	93.59 61	92.58 94	66.54 225	86.17 19	95.88 14	63.83 58	97.00 67	86.39 32	92.94 38	95.06 49
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
BH-RMVSNet		79.46 126	77.65 132	84.89 97	91.68 83	65.66 133	93.55 62	88.09 237	72.93 134	73.37 123	91.12 110	46.20 231	96.12 96	56.28 235	85.61 102	92.91 118

canonicalmvs		86.85 28	86.25 31	88.66 10	91.80 80	71.92 10	93.54 63	91.71 125	80.26 31	87.55 13	95.25 32	63.59 63	96.93 77	88.18 19	84.34 111	97.11 3

HFP-MVS		84.73 49	84.40 49	85.72 74	93.75 37	65.01 147	93.50 64	93.19 70	72.19 147	79.22 72	94.93 42	59.04 98	97.67 33	81.55 62	92.21 46	94.49 70

ACMMPR		84.37 52	84.06 50	85.28 88	93.56 40	64.37 160	93.50 64	93.15 73	72.19 147	78.85 78	94.86 46	56.69 123	97.45 44	81.55 62	92.20 48	94.02 89

Vis-MVSNet		80.92 100	79.98 98	83.74 120	88.48 143	61.80 207	93.44 66	88.26 236	73.96 114	77.73 85	91.76 104	49.94 198	94.76 136	65.84 177	90.37 70	94.65 62
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
region2R		84.36 53	84.03 51	85.36 86	93.54 41	64.31 162	93.43 67	92.95 80	72.16 150	78.86 77	94.84 47	56.97 116	97.53 42	81.38 65	92.11 50	94.24 74

QAPM		79.95 116	77.39 139	87.64 20	89.63 119	71.41 12	93.30 68	93.70 48	65.34 235	67.39 202	91.75 105	47.83 217	98.96 5	57.71 231	89.81 72	92.54 126

MP-MVS		85.02 46	84.97 45	85.17 92	92.60 61	64.27 165	93.24 69	92.27 101	73.13 130	79.63 69	94.43 53	61.90 75	97.17 58	85.00 40	92.56 43	94.06 87

nrg030		80.93 99	79.86 99	84.13 114	83.69 208	68.83 45	93.23 70	91.20 143	75.55 85	75.06 111	88.22 144	63.04 70	94.74 138	81.88 59	66.88 221	88.82 167

VPA-MVSNet		79.03 130	78.00 127	82.11 167	85.95 181	64.48 154	93.22 71	94.66 27	75.05 95	74.04 120	84.95 178	52.17 182	93.52 192	74.90 107	67.04 220	88.32 176

HQP_MVS		80.34 107	79.75 101	82.12 164	86.94 167	62.42 196	93.13 72	91.31 140	78.81 49	72.53 133	89.14 131	50.66 191	95.55 120	76.74 91	78.53 146	88.39 174

plane_prior2							93.13 72		78.81 49

HSP-MVS		90.38 2	91.89 1	85.84 68	92.83 55	64.03 168	93.06 74	94.52 30	82.19 19	93.65 1	96.15 10	85.89 1	97.19 57	91.02 8	97.75 1	96.29 16

thres200		79.66 121	78.33 121	83.66 126	92.54 62	65.82 132	93.06 74	96.31 6	74.90 97	73.30 124	88.66 133	59.67 92	95.61 116	47.84 264	78.67 145	89.56 163

EPP-MVSNet		81.79 90	81.52 81	82.61 143	88.77 138	60.21 230	93.02 76	93.66 50	68.52 209	72.90 127	90.39 119	72.19 11	94.96 130	74.93 105	79.29 140	92.67 122

cascas		78.18 147	75.77 158	85.41 84	87.14 165	69.11 39	92.96 77	91.15 145	66.71 224	70.47 152	86.07 167	37.49 272	96.48 90	70.15 140	79.80 135	90.65 151

Regformer-3		85.80 40	85.92 34	85.46 80	94.17 29	65.09 146	92.95 78	95.11 16	81.13 27	81.68 53	95.04 37	65.82 42	98.32 20	83.02 52	84.36 109	92.97 116

Regformer-4		85.45 43	85.69 39	84.73 101	94.17 29	63.23 183	92.95 78	94.83 21	80.66 29	81.29 55	95.04 37	65.12 47	98.08 26	82.74 53	84.36 109	92.88 120

XVS		83.87 62	83.47 55	85.05 94	93.22 45	63.78 171	92.92 80	92.66 90	73.99 111	78.18 82	94.31 62	55.25 136	97.41 45	79.16 76	91.58 56	93.95 91

X-MVStestdata		76.86 171	74.13 184	85.05 94	93.22 45	63.78 171	92.92 80	92.66 90	73.99 111	78.18 82	10.19 340	55.25 136	97.41 45	79.16 76	91.58 56	93.95 91

114514_t		79.17 129	77.67 131	83.68 124	95.32 14	65.53 136	92.85 82	91.60 129	63.49 245	67.92 194	90.63 116	46.65 226	95.72 114	67.01 164	83.54 117	89.79 159

mPP-MVS		82.96 74	82.44 71	84.52 108	92.83 55	62.92 189	92.76 83	91.85 120	71.52 169	75.61 106	94.24 63	53.48 171	96.99 70	78.97 79	90.73 65	93.64 98

OpenMVS	70.45 11	78.54 144	75.92 156	86.41 55	85.93 184	71.68 11	92.74 84	92.51 96	66.49 226	64.56 216	91.96 100	43.88 242	98.10 25	54.61 239	90.65 67	89.44 164

无先验							92.71 85	92.61 93	62.03 256				97.01 65	66.63 166		93.97 90

test-LLR		80.10 112	79.56 104	81.72 173	86.93 169	61.17 212	92.70 86	91.54 130	71.51 170	75.62 104	86.94 159	53.83 163	92.38 222	72.21 120	84.76 107	91.60 139

TESTMET0.1,1		82.41 80	81.98 76	83.72 123	88.08 151	63.74 173	92.70 86	93.77 45	79.30 38	77.61 89	87.57 150	58.19 104	94.08 172	73.91 109	86.68 92	93.33 105

test-mter		79.96 115	79.38 110	81.72 173	86.93 169	61.17 212	92.70 86	91.54 130	73.85 116	75.62 104	86.94 159	49.84 200	92.38 222	72.21 120	84.76 107	91.60 139

BH-untuned		78.68 140	77.08 142	83.48 129	89.84 116	63.74 173	92.70 86	88.59 228	71.57 167	66.83 207	88.65 134	51.75 185	95.39 123	59.03 225	84.77 106	91.32 145

AdaColmap		78.94 133	77.00 144	84.76 100	96.34 6	65.86 129	92.66 90	87.97 240	62.18 255	70.56 151	92.37 96	43.53 243	97.35 49	64.50 188	82.86 120	91.05 148

WR-MVS		76.76 174	75.74 159	79.82 210	84.60 194	62.27 200	92.60 91	92.51 96	76.06 80	67.87 196	85.34 173	56.76 119	90.24 253	62.20 209	63.69 249	86.94 200

3Dnovator	73.91 6	82.69 78	80.82 88	88.31 14	89.57 120	71.26 13	92.60 91	94.39 37	78.84 48	67.89 195	92.48 93	48.42 211	98.52 15	68.80 152	94.40 19	95.15 46

xiu_mvs_v1_base_debu		82.16 84	81.12 85	85.26 89	86.42 172	68.72 47	92.59 93	90.44 162	73.12 131	84.20 38	94.36 55	38.04 266	95.73 110	84.12 45	86.81 89	91.33 142

xiu_mvs_v1_base		82.16 84	81.12 85	85.26 89	86.42 172	68.72 47	92.59 93	90.44 162	73.12 131	84.20 38	94.36 55	38.04 266	95.73 110	84.12 45	86.81 89	91.33 142

xiu_mvs_v1_base_debi		82.16 84	81.12 85	85.26 89	86.42 172	68.72 47	92.59 93	90.44 162	73.12 131	84.20 38	94.36 55	38.04 266	95.73 110	84.12 45	86.81 89	91.33 142

PVSNet	73.49 8	80.05 113	78.63 118	84.31 111	90.92 101	64.97 149	92.47 96	91.05 149	79.18 41	72.43 137	90.51 118	37.05 278	94.06 173	68.06 154	86.00 99	93.90 94

PAPM		85.89 39	85.46 41	87.18 30	88.20 150	72.42 9	92.41 97	92.77 85	82.11 21	80.34 62	93.07 81	68.27 20	95.02 128	78.39 83	93.59 32	94.09 84

1112_ss		80.56 103	79.83 100	82.77 137	88.65 139	60.78 217	92.29 98	88.36 232	72.58 139	72.46 136	94.95 40	65.09 48	93.42 195	66.38 170	77.71 151	94.10 83

UniMVSNet_NR-MVSNet		78.15 148	77.55 134	79.98 205	84.46 198	60.26 228	92.25 99	93.20 69	77.50 64	68.88 179	86.61 161	66.10 38	92.13 228	66.38 170	62.55 250	87.54 181

sss		82.71 77	82.38 72	83.73 122	89.25 126	59.58 240	92.24 100	94.89 19	77.96 57	79.86 66	92.38 95	56.70 122	97.05 62	77.26 90	80.86 132	94.55 64

DeepC-MVS	77.85 3	85.52 42	85.24 43	86.37 56	88.80 137	66.64 108	92.15 101	93.68 49	81.07 28	76.91 98	93.64 71	62.59 72	98.44 17	85.50 37	92.84 40	94.03 88
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
UGNet		79.87 117	78.68 117	83.45 130	89.96 113	61.51 210	92.13 102	90.79 154	76.83 72	78.85 78	86.33 165	38.16 264	96.17 94	67.93 156	87.17 87	92.67 122
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
ACMMP		81.49 92	80.67 90	83.93 117	91.71 82	62.90 190	92.13 102	92.22 106	71.79 161	71.68 147	93.49 74	50.32 193	96.96 73	78.47 81	84.22 116	91.93 136
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
CPTT-MVS		79.59 123	79.16 114	80.89 194	91.54 87	59.80 237	92.10 104	88.54 230	60.42 266	72.96 125	93.28 76	48.27 212	92.80 209	78.89 80	86.50 96	90.06 156

Test_1112_low_res		79.56 124	78.60 119	82.43 148	88.24 149	60.39 226	92.09 105	87.99 239	72.10 151	71.84 143	87.42 152	64.62 52	93.04 199	65.80 178	77.30 159	93.85 95

CDS-MVSNet		81.43 93	80.74 89	83.52 127	86.26 176	64.45 155	92.09 105	90.65 160	75.83 83	73.95 121	89.81 127	63.97 56	92.91 206	71.27 129	82.82 121	93.20 109
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
CHOSEN 1792x2688		84.98 47	83.45 56	89.57 6	89.94 114	75.14 4	92.07 107	92.32 99	81.87 25	75.68 103	88.27 140	60.18 88	98.60 14	80.46 70	90.27 71	94.96 55

tfpn200view9		78.79 137	77.43 137	82.88 135	92.21 70	64.49 152	92.05 108	96.28 7	73.48 125	71.75 145	88.26 141	60.07 89	95.32 125	45.16 273	77.58 154	88.83 166

thres400		78.68 140	77.43 137	82.43 148	92.21 70	64.49 152	92.05 108	96.28 7	73.48 125	71.75 145	88.26 141	60.07 89	95.32 125	45.16 273	77.58 154	87.48 183

原ACMM2							92.01 110

XXY-MVS		77.94 151	76.44 150	82.43 148	82.60 219	64.44 156	92.01 110	91.83 121	73.59 123	70.00 160	85.82 170	54.43 157	94.76 136	69.63 143	68.02 215	88.10 178

旧先验2							92.00 112		59.37 273	87.54 14			93.47 194	75.39 99

IS-MVSNet		80.14 111	79.41 108	82.33 155	87.91 155	60.08 234	91.97 113	88.27 235	72.90 135	71.44 149	91.73 106	61.44 78	93.66 190	62.47 208	86.53 95	93.24 107

v1141		77.28 162	75.57 164	82.42 151	80.63 243	66.73 101	91.96 114	90.42 165	74.41 100	69.46 168	82.12 208	55.09 143	94.40 153	70.99 132	65.05 234	86.12 212

divwei89l23v2f112		77.28 162	75.57 164	82.42 151	80.62 244	66.72 103	91.96 114	90.42 165	74.41 100	69.46 168	82.12 208	55.11 142	94.40 153	71.00 130	65.04 235	86.12 212

v1		77.29 161	75.57 164	82.42 151	80.61 247	66.73 101	91.96 114	90.42 165	74.41 100	69.46 168	82.12 208	55.14 141	94.40 153	71.00 130	65.04 235	86.13 211

EPNet_dtu		78.80 136	79.26 112	77.43 249	88.06 152	49.71 297	91.96 114	91.95 117	77.67 61	76.56 100	91.28 109	58.51 102	90.20 255	56.37 234	80.95 131	92.39 128
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
v1neww		77.39 157	75.71 160	82.44 145	80.69 237	66.83 91	91.94 118	90.18 177	74.19 107	69.60 165	82.51 198	54.99 147	94.44 148	71.68 125	65.60 227	86.05 215

v7new		77.39 157	75.71 160	82.44 145	80.69 237	66.83 91	91.94 118	90.18 177	74.19 107	69.60 165	82.51 198	54.99 147	94.44 148	71.68 125	65.60 227	86.05 215

v6		77.39 157	75.71 160	82.44 145	80.67 239	66.82 93	91.94 118	90.18 177	74.19 107	69.60 165	82.50 201	55.00 146	94.44 148	71.68 125	65.60 227	86.05 215

MVSTER		82.47 79	82.05 74	83.74 120	92.68 60	69.01 41	91.90 121	93.21 67	79.83 32	72.14 140	85.71 172	74.72 6	94.72 139	75.72 96	72.49 188	87.50 182

CANet_DTU		84.09 58	83.52 53	85.81 69	90.30 109	66.82 93	91.87 122	89.01 219	85.27 7	86.09 20	93.74 70	47.71 219	96.98 71	77.90 87	89.78 73	93.65 97

FMVSNet3		77.73 153	76.04 154	82.80 136	91.20 98	68.99 42	91.87 122	91.99 114	73.35 128	67.04 204	83.19 194	56.62 124	92.14 227	59.80 222	69.34 204	87.28 194

v2v482		77.42 156	75.65 163	82.73 138	80.38 249	67.13 82	91.85 124	90.23 174	75.09 94	69.37 171	83.39 192	53.79 165	94.44 148	71.77 123	65.00 238	86.63 206

PAPR		85.15 45	84.47 47	87.18 30	96.02 10	68.29 56	91.85 124	93.00 79	76.59 76	79.03 75	95.00 39	61.59 77	97.61 40	78.16 84	89.00 76	95.63 28

ACMMP_Plus		86.05 37	85.80 37	86.80 39	91.58 84	67.53 72	91.79 126	93.49 57	74.93 96	84.61 33	95.30 28	59.42 94	97.92 28	86.13 33	94.92 9	94.94 56

Baseline_NR-MVSNet		73.99 205	72.83 198	77.48 248	80.78 233	59.29 245	91.79 126	84.55 277	68.85 202	68.99 177	80.70 230	56.16 128	92.04 231	62.67 206	60.98 265	81.11 280

TransMVSNet (Re)		70.07 238	67.66 239	77.31 252	80.62 244	59.13 247	91.78 128	84.94 275	65.97 229	60.08 242	80.44 234	50.78 190	91.87 233	48.84 260	45.46 312	80.94 282

EI-MVSNet-Vis-set		83.77 64	83.67 52	84.06 115	92.79 59	63.56 180	91.76 129	94.81 23	79.65 36	77.87 84	94.09 64	63.35 65	97.90 29	79.35 74	79.36 138	90.74 150

UniMVSNet (Re)		77.58 154	76.78 146	79.98 205	84.11 204	60.80 216	91.76 129	93.17 72	76.56 77	69.93 163	84.78 180	63.32 66	92.36 224	64.89 184	62.51 252	86.78 202

MS-PatchMatch		77.90 152	76.50 149	82.12 164	85.99 180	69.95 27	91.75 131	92.70 87	73.97 113	62.58 234	84.44 184	41.11 253	95.78 107	63.76 192	92.17 49	80.62 286

v148		76.19 179	74.47 180	81.36 178	80.05 261	64.44 156	91.75 131	90.23 174	73.68 121	67.13 203	80.84 229	55.92 134	93.86 186	68.95 150	61.73 259	85.76 225

FIs		79.47 125	79.41 108	79.67 212	85.95 181	59.40 242	91.68 133	93.94 40	78.06 56	68.96 178	88.28 139	66.61 34	91.77 235	66.20 173	74.99 173	87.82 179

v1144		76.73 175	74.88 174	82.27 158	80.23 257	66.60 109	91.68 133	90.21 176	73.69 120	69.06 176	81.89 213	52.73 177	94.40 153	69.21 148	65.23 231	85.80 222

v7		76.83 173	75.01 173	82.29 157	80.35 250	66.70 105	91.68 133	89.97 186	73.47 127	69.22 173	82.22 205	52.52 178	94.43 152	69.73 142	65.96 226	85.74 226

OPM-MVS		79.00 131	78.09 125	81.73 172	83.52 211	63.83 170	91.64 136	90.30 172	76.36 79	71.97 142	89.93 126	46.30 230	95.17 127	75.10 101	77.70 152	86.19 210

MPTG		84.73 49	84.47 47	85.50 78	91.89 78	65.16 141	91.55 137	92.23 102	75.32 91	80.53 60	95.21 34	56.06 131	97.16 59	84.86 42	92.55 44	94.18 76

MP-MVS-pluss		85.24 44	85.13 44	85.56 77	91.42 93	65.59 134	91.54 138	92.51 96	74.56 99	80.62 59	95.64 20	59.15 97	97.00 67	86.94 29	93.80 26	94.07 86
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
GA-MVS		78.33 146	76.23 152	84.65 104	83.65 209	66.30 121	91.44 139	90.14 180	76.01 81	70.32 155	84.02 186	42.50 246	94.72 139	70.98 133	77.00 161	92.94 117

新几何2							91.41 140

v144192		76.05 182	74.03 185	82.12 164	79.50 266	66.55 113	91.39 141	89.71 197	72.30 144	68.17 191	81.33 221	51.75 185	94.03 177	67.94 155	64.19 244	85.77 223

APD-MVS_3200maxsize		81.64 91	81.32 83	82.59 144	92.36 63	58.74 250	91.39 141	91.01 151	63.35 246	79.72 68	94.62 51	51.82 183	96.14 95	79.71 71	87.93 83	92.89 119

EI-MVSNet-UG-set		83.14 70	82.96 63	83.67 125	92.28 67	63.19 184	91.38 143	94.68 26	79.22 40	76.60 99	93.75 69	62.64 71	97.76 31	78.07 85	78.01 149	90.05 157

TranMVSNet+NR-MVSNet		75.86 185	74.52 179	79.89 208	82.44 220	60.64 223	91.37 144	91.37 139	76.63 75	67.65 198	86.21 166	52.37 181	91.55 239	61.84 211	60.81 266	87.48 183

Effi-MVS+		83.82 63	82.76 68	86.99 37	89.56 121	69.40 36	91.35 145	86.12 266	72.59 138	83.22 45	92.81 89	59.60 93	96.01 102	81.76 60	87.80 84	95.56 30

FMVSNet2		76.07 181	74.01 186	82.26 160	88.85 134	67.66 68	91.33 146	91.61 128	70.84 177	65.98 209	82.25 204	48.03 213	92.00 232	58.46 228	68.73 210	87.10 196

HPM-MVS_fast		80.25 108	79.55 106	82.33 155	91.55 86	59.95 235	91.32 147	89.16 212	65.23 236	74.71 113	93.07 81	47.81 218	95.74 109	74.87 108	88.23 80	91.31 146

thres600view7		78.00 149	76.66 147	82.03 169	91.93 75	63.69 176	91.30 148	96.33 5	72.43 141	70.46 153	87.89 147	60.31 87	94.92 133	42.64 283	76.64 162	87.48 183

DU-MVS		76.86 171	75.84 157	79.91 207	82.96 217	60.26 228	91.26 149	91.54 130	76.46 78	68.88 179	86.35 163	56.16 128	92.13 228	66.38 170	62.55 250	87.35 192

TAMVS		80.37 106	79.45 107	83.13 133	85.14 189	63.37 181	91.23 150	90.76 156	74.81 98	72.65 130	88.49 135	60.63 86	92.95 202	69.41 146	81.95 127	93.08 113

v1192		75.98 184	73.92 187	82.15 163	79.73 262	66.24 123	91.22 151	89.75 191	72.67 137	68.49 189	81.42 219	49.86 199	94.27 161	67.08 163	65.02 237	85.95 219

test0.0.03 1		72.76 214	72.71 200	72.88 279	80.25 256	47.99 302	91.22 151	89.45 201	71.51 170	62.51 235	87.66 148	53.83 163	85.06 292	50.16 255	67.84 218	85.58 227

Fast-Effi-MVS+-dtu		75.04 195	73.37 194	80.07 203	80.86 232	59.52 241	91.20 153	85.38 273	71.90 153	65.20 211	84.84 179	41.46 252	92.97 201	66.50 169	72.96 184	87.73 180

PMMVS		81.98 89	82.04 75	81.78 171	89.76 118	56.17 267	91.13 154	90.69 157	77.96 57	80.09 64	93.57 72	46.33 229	94.99 129	81.41 64	87.46 86	94.17 78

pmmvs5		73.35 209	71.52 211	78.86 231	78.64 277	60.61 224	91.08 155	86.90 250	67.69 216	63.32 227	83.64 188	44.33 241	90.53 248	62.04 210	66.02 225	85.46 230

v1921920		75.63 189	73.49 192	82.06 168	79.38 267	66.35 119	91.07 156	89.48 200	71.98 152	67.99 192	81.22 224	49.16 207	93.90 183	66.56 168	64.56 243	85.92 221

HPM-MVS		83.25 68	82.95 64	84.17 113	92.25 68	62.88 191	90.91 157	91.86 119	70.30 189	77.12 95	93.96 67	56.75 121	96.28 91	82.04 58	91.34 61	93.34 103

CNLPA		74.31 202	72.30 205	80.32 198	91.49 88	61.66 208	90.85 158	80.72 299	56.67 286	63.85 223	90.64 114	46.75 224	90.84 247	53.79 243	75.99 166	88.47 173

NR-MVSNet		76.05 182	74.59 176	80.44 196	82.96 217	62.18 201	90.83 159	91.73 123	77.12 67	60.96 238	86.35 163	59.28 96	91.80 234	60.74 216	61.34 263	87.35 192

pm-mvs1		72.89 212	71.09 214	78.26 238	79.10 273	57.62 259	90.80 160	89.30 206	67.66 217	62.91 231	81.78 215	49.11 208	92.95 202	60.29 219	58.89 275	84.22 241

ACMP	71.68 10	75.58 190	74.23 183	79.62 214	84.97 191	59.64 238	90.80 160	89.07 217	70.39 188	62.95 230	87.30 157	38.28 263	93.87 184	72.89 112	71.45 195	85.36 232
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
v1240		75.21 194	72.98 197	81.88 170	79.20 269	66.00 126	90.75 162	89.11 215	71.63 165	67.41 201	81.22 224	47.36 221	93.87 184	65.46 181	64.72 241	85.77 223

DI_MVS_plusplus_test		79.78 120	77.50 136	86.62 43	80.90 231	69.46 35	90.69 163	91.97 116	77.00 68	59.07 248	82.34 202	46.82 223	95.88 104	82.14 57	86.59 94	94.53 68

test_normal		79.66 121	77.36 141	86.54 47	80.72 235	69.21 38	90.68 164	92.16 111	76.99 69	58.63 252	82.03 211	46.70 225	95.86 105	81.74 61	86.63 93	94.56 63

IterMVS-LS		76.49 176	75.18 172	80.43 197	84.49 197	62.74 193	90.64 165	88.80 223	72.40 142	65.16 212	81.72 216	60.98 80	92.27 226	67.74 157	64.65 242	86.29 208
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
PLC	68.80 14	75.23 193	73.68 190	79.86 209	92.93 53	58.68 251	90.64 165	88.30 233	60.90 263	64.43 219	90.53 117	42.38 247	94.57 142	56.52 233	76.54 163	86.33 207
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
PS-MVSNAJss		77.26 164	76.31 151	80.13 202	80.64 242	59.16 246	90.63 167	91.06 148	72.80 136	68.58 184	84.57 183	53.55 167	93.96 180	72.97 111	71.96 191	87.27 195

PGM-MVS		83.25 68	82.70 70	84.92 96	92.81 58	64.07 167	90.44 168	92.20 107	71.28 172	77.23 94	94.43 53	55.17 140	97.31 51	79.33 75	91.38 59	93.37 102

LPG-MVS_test		75.82 186	74.58 177	79.56 216	84.31 201	59.37 243	90.44 168	89.73 194	69.49 195	64.86 213	88.42 136	38.65 260	94.30 159	72.56 116	72.76 185	85.01 235

Vis-MVSNet (Re-imp)		79.24 128	79.57 103	78.24 239	88.46 144	52.29 284	90.41 170	89.12 214	74.24 106	69.13 174	91.91 101	65.77 43	90.09 260	59.00 226	88.09 82	92.33 129

TSAR-MVS + MP.		88.11 11	88.64 9	86.54 47	91.73 81	68.04 61	90.36 171	93.55 54	82.89 14	91.29 2	92.89 87	72.27 10	96.03 100	87.99 20	94.77 13	95.54 31

ACMM	69.62 13	74.34 201	72.73 199	79.17 228	84.25 203	57.87 255	90.36 171	89.93 187	63.17 249	65.64 210	86.04 169	37.79 270	94.10 170	65.89 176	71.52 194	85.55 229
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
FC-MVSNet-test		77.99 150	78.08 126	77.70 244	84.89 192	55.51 271	90.27 173	93.75 47	76.87 70	66.80 208	87.59 149	65.71 44	90.23 254	62.89 203	73.94 178	87.37 190

V42		76.46 177	74.55 178	82.19 162	79.14 271	67.82 64	90.26 174	89.42 203	73.75 119	68.63 183	81.89 213	51.31 189	94.09 171	71.69 124	64.84 239	84.66 238

HyFIR lowres test		81.03 98	79.56 104	85.43 83	87.81 157	68.11 60	90.18 175	90.01 185	70.65 184	72.95 126	86.06 168	63.61 62	94.50 147	75.01 104	79.75 136	93.67 96

GBi-Net		75.65 187	73.83 188	81.10 188	88.85 134	65.11 143	90.01 176	90.32 168	70.84 177	67.04 204	80.25 238	48.03 213	91.54 240	59.80 222	69.34 204	86.64 203

test1		75.65 187	73.83 188	81.10 188	88.85 134	65.11 143	90.01 176	90.32 168	70.84 177	67.04 204	80.25 238	48.03 213	91.54 240	59.80 222	69.34 204	86.64 203

FMVSNet1		72.71 215	69.91 219	81.10 188	83.60 210	65.11 143	90.01 176	90.32 168	63.92 243	63.56 225	80.25 238	36.35 280	91.54 240	54.46 240	66.75 222	86.64 203

MVS_Test		84.16 57	83.20 62	87.05 35	91.56 85	69.82 29	89.99 179	92.05 112	77.77 59	82.84 47	86.57 162	63.93 57	96.09 97	74.91 106	89.18 75	95.25 43

view600		76.93 167	75.50 167	81.23 181	91.44 89	62.00 202	89.94 180	96.56 1	70.68 180	68.54 185	87.31 153	60.79 81	94.19 164	38.90 296	75.31 169	87.48 183

view800		76.93 167	75.50 167	81.23 181	91.44 89	62.00 202	89.94 180	96.56 1	70.68 180	68.54 185	87.31 153	60.79 81	94.19 164	38.90 296	75.31 169	87.48 183

conf0.05thres1000		76.93 167	75.50 167	81.23 181	91.44 89	62.00 202	89.94 180	96.56 1	70.68 180	68.54 185	87.31 153	60.79 81	94.19 164	38.90 296	75.31 169	87.48 183

tfpn		76.93 167	75.50 167	81.23 181	91.44 89	62.00 202	89.94 180	96.56 1	70.68 180	68.54 185	87.31 153	60.79 81	94.19 164	38.90 296	75.31 169	87.48 183

Effi-MVS+-dtu		76.14 180	75.28 171	78.72 232	83.22 213	55.17 273	89.87 184	87.78 241	75.42 87	67.98 193	81.43 218	45.08 236	92.52 218	75.08 102	71.63 192	88.48 172

EG-PatchMatch MVS		68.55 249	65.41 251	77.96 243	78.69 276	62.93 187	89.86 185	89.17 211	60.55 265	50.27 292	77.73 257	22.60 316	94.06 173	47.18 267	72.65 187	76.88 307

MVS_111021_LR		82.02 88	81.52 81	83.51 128	88.42 146	62.88 191	89.77 186	88.93 221	76.78 73	75.55 107	93.10 77	50.31 194	95.38 124	83.82 49	87.02 88	92.26 133

DP-MVS		69.90 239	66.48 245	80.14 201	95.36 13	62.93 187	89.56 187	76.11 307	50.27 301	57.69 258	85.23 175	39.68 257	95.73 110	33.35 311	71.05 198	81.78 267

test222					89.77 117	61.60 209	89.55 188	89.42 203	56.83 285	77.28 93	92.43 94	52.76 176			91.14 63	93.09 112

v8		75.35 191	73.26 195	81.61 176	80.67 239	66.82 93	89.54 189	89.27 207	71.65 164	63.30 228	80.30 237	54.99 147	94.06 173	67.33 162	62.33 253	83.94 243

EI-MVSNet		78.97 132	78.22 124	81.25 180	85.33 186	62.73 194	89.53 190	93.21 67	72.39 143	72.14 140	90.13 123	60.99 79	94.72 139	67.73 158	72.49 188	86.29 208

CVMVSNet		74.04 204	74.27 182	73.33 275	85.33 186	43.94 311	89.53 190	88.39 231	54.33 292	70.37 154	90.13 123	49.17 206	84.05 296	61.83 212	79.36 138	91.99 135

MVP-Stereo		77.12 166	76.23 152	79.79 211	81.72 225	66.34 120	89.29 192	90.88 152	70.56 185	62.01 237	82.88 195	49.34 203	94.13 169	65.55 180	93.80 26	78.88 299
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
OpenMVS_ROB	61.12 18	66.39 262	62.92 267	76.80 256	76.51 288	57.77 256	89.22 193	83.41 287	55.48 290	53.86 277	77.84 256	26.28 311	93.95 181	34.90 309	68.76 209	78.68 301

testdata1							89.21 194		77.55 63

TAPA-MVS	70.22 12	74.94 198	73.53 191	79.17 228	90.40 107	52.07 285	89.19 195	89.61 198	62.69 252	70.07 158	92.67 90	48.89 210	94.32 158	38.26 301	79.97 134	91.12 147
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
v10		74.77 199	72.54 203	81.46 177	80.33 254	66.71 104	89.15 196	89.08 216	70.94 175	63.08 229	79.86 242	52.52 178	94.04 176	65.70 179	62.17 254	83.64 245

DWT-MVSNet_test		83.95 60	82.80 67	87.41 25	92.90 54	70.07 25	89.12 197	94.42 34	82.15 20	77.64 87	91.77 103	70.81 15	96.22 92	65.03 183	81.36 128	95.94 23

MVSFormer		83.75 65	82.88 65	86.37 56	89.24 128	71.18 14	89.07 198	90.69 157	65.80 230	87.13 15	94.34 60	64.99 49	92.67 214	72.83 113	91.80 52	95.27 40

test_djsdf		73.76 208	72.56 202	77.39 250	77.00 287	53.93 278	89.07 198	90.69 157	65.80 230	63.92 221	82.03 211	43.14 245	92.67 214	72.83 113	68.53 211	85.57 228

tfpnnormal		70.10 237	67.36 240	78.32 235	83.45 212	60.97 214	88.85 200	92.77 85	64.85 238	60.83 239	78.53 252	43.52 244	93.48 193	31.73 317	61.70 260	80.52 287

jajsoiax		73.05 210	71.51 212	77.67 245	77.46 284	54.83 274	88.81 201	90.04 184	69.13 199	62.85 232	83.51 190	31.16 298	92.75 211	70.83 134	69.80 200	85.43 231

pmmvs6		67.57 256	64.76 255	76.00 261	72.82 301	53.37 280	88.71 202	86.78 251	53.19 293	57.58 259	78.03 255	35.33 283	92.41 221	55.56 237	54.88 287	82.21 264

PVSNet_0	68.08 15	71.81 220	68.32 234	82.27 158	84.68 193	62.31 199	88.68 203	90.31 171	75.84 82	57.93 255	80.65 232	37.85 269	94.19 164	69.94 141	29.05 328	90.31 155

PatchFormer-LS_test		83.14 70	81.81 78	87.12 32	92.34 64	69.92 28	88.64 204	93.32 63	82.07 23	74.87 112	91.62 107	68.91 17	96.08 99	66.07 174	78.45 148	95.37 33

OMC-MVS		78.67 142	77.91 130	80.95 193	85.76 185	57.40 261	88.49 205	88.67 225	73.85 116	72.43 137	92.10 99	49.29 204	94.55 144	72.73 115	77.89 150	90.91 149

abl_6		79.82 118	79.20 113	81.70 175	89.85 115	58.34 252	88.47 206	90.07 182	62.56 253	77.71 86	93.08 79	47.65 220	96.78 81	77.94 86	85.45 103	89.99 158

mvs_tets		72.71 215	71.11 213	77.52 246	77.41 285	54.52 276	88.45 207	89.76 190	68.76 204	62.70 233	83.26 193	29.49 302	92.71 212	70.51 139	69.62 202	85.34 233

Test4		76.45 178	73.45 193	85.45 82	76.07 293	67.61 70	88.38 208	90.83 153	76.71 74	53.06 281	79.65 246	31.61 295	94.35 157	78.47 81	86.22 98	94.40 72

Anonymous20231206		67.53 257	65.78 247	72.79 280	74.95 295	47.59 304	88.23 209	87.32 247	61.75 261	58.07 254	77.29 260	37.79 270	87.29 285	42.91 279	63.71 248	83.48 249

v18		71.94 219	69.43 222	79.50 218	80.74 234	66.82 93	88.16 210	86.66 252	68.95 201	55.55 264	72.66 281	55.03 145	90.15 256	64.78 185	52.30 292	81.54 268

ACMH+	65.35 16	67.65 255	64.55 256	76.96 254	84.59 195	57.10 264	88.08 211	80.79 298	58.59 277	53.00 282	81.09 228	26.63 310	92.95 202	46.51 268	61.69 261	80.82 283

F-COLMAP		70.66 233	68.44 232	77.32 251	86.37 175	55.91 269	88.00 212	86.32 261	56.94 284	57.28 260	88.07 145	33.58 287	92.49 219	51.02 252	68.37 212	83.55 246

test_0402		64.54 270	61.09 275	74.92 265	84.10 205	60.75 219	87.95 213	79.71 302	52.03 296	52.41 283	77.20 261	32.21 293	91.64 237	23.14 327	61.03 264	72.36 314

v17		71.77 222	69.20 225	79.46 220	80.62 244	66.81 97	87.93 214	86.63 254	68.71 205	55.25 266	72.49 283	54.72 152	90.11 259	64.50 188	51.97 294	81.47 269

v16		71.81 220	69.26 224	79.47 219	80.66 241	66.81 97	87.93 214	86.63 254	68.70 206	55.35 265	72.51 282	54.75 151	90.12 258	64.51 187	52.28 293	81.47 269

1314		80.70 101	78.95 116	85.94 66	87.77 158	67.56 71	87.91 216	92.55 95	72.17 149	67.44 199	93.09 78	50.27 195	97.04 64	71.68 125	87.64 85	93.23 108

1121		81.25 95	80.05 95	84.87 98	92.30 66	64.31 162	87.91 216	91.39 137	59.44 272	79.94 65	92.91 85	57.09 112	97.01 65	66.63 166	92.81 41	93.29 106

MVS		84.66 51	82.86 66	90.06 1	90.93 100	74.56 5	87.91 216	95.54 11	68.55 208	72.35 139	94.71 50	59.78 91	98.90 7	81.29 67	94.69 17	96.74 7

test2356		64.16 273	63.28 264	66.81 301	69.37 313	39.86 321	87.76 219	86.02 267	59.83 270	53.54 280	73.23 279	34.94 284	80.67 315	39.66 292	65.20 232	79.89 292

ACMH	63.93 17	68.62 248	64.81 254	80.03 204	85.22 188	63.25 182	87.72 220	84.66 276	60.83 264	51.57 287	79.43 248	27.29 308	94.96 130	41.76 284	64.84 239	81.88 266
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
PAPM_NR		82.97 73	81.84 77	86.37 56	94.10 33	66.76 100	87.66 221	92.84 83	69.96 192	74.07 119	93.57 72	63.10 69	97.50 43	70.66 137	90.58 68	94.85 57

IterMVS		72.65 217	70.83 215	78.09 242	82.17 221	62.96 186	87.64 222	86.28 262	71.56 168	60.44 240	78.85 251	45.42 235	86.66 287	63.30 196	61.83 256	84.65 239
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
v15		71.40 224	68.75 227	79.35 221	80.39 248	66.70 105	87.57 223	86.64 253	68.66 207	54.68 268	72.00 290	54.50 154	89.98 261	63.69 193	50.66 299	81.38 273

pmmvs4		73.92 206	71.81 209	80.25 200	79.17 270	65.24 139	87.43 224	87.26 249	67.64 219	63.46 226	83.91 187	48.96 209	91.53 243	62.94 202	65.49 230	83.96 242

V14		71.29 226	68.61 229	79.31 222	80.34 252	66.65 107	87.39 225	86.61 256	68.41 211	54.49 270	71.91 291	54.25 159	89.96 262	63.50 194	50.62 300	81.33 275

WR-MVS_H		70.59 234	69.94 218	72.53 281	81.03 230	51.43 288	87.35 226	92.03 113	67.38 221	60.23 241	80.70 230	55.84 135	83.45 303	46.33 269	58.58 276	82.72 261

CP-MVSNet		70.50 236	69.91 219	72.26 284	80.71 236	51.00 291	87.23 227	90.30 172	67.84 215	59.64 243	82.69 197	50.23 196	82.30 310	51.28 251	59.28 270	83.46 250

V9		71.16 227	68.46 231	79.27 224	80.26 255	66.60 109	87.21 228	86.56 257	68.17 212	54.26 273	71.81 293	54.00 161	89.93 263	63.28 197	50.57 301	81.27 276

PCF-MVS	73.15 9	79.29 127	77.63 133	84.29 112	86.06 179	65.96 127	87.03 229	91.10 147	69.86 193	69.79 164	90.64 114	57.54 110	96.59 86	64.37 190	82.29 123	90.32 154
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
PS-CasMVS		69.86 240	69.13 226	72.07 287	80.35 250	50.57 293	87.02 230	89.75 191	67.27 222	59.19 246	82.28 203	46.58 227	82.24 311	50.69 253	59.02 273	83.39 252

v12		71.02 231	68.29 236	79.22 226	80.18 258	66.53 114	87.01 231	86.54 259	67.90 214	54.00 276	71.70 294	53.66 166	89.91 264	63.09 199	50.51 302	81.21 277

v11		71.05 230	68.32 234	79.23 225	80.34 252	66.57 112	87.01 231	86.55 258	68.11 213	54.40 271	71.66 295	52.94 175	89.91 264	62.71 205	51.12 297	81.21 277

PEN-MVS		69.46 245	68.56 230	72.17 286	79.27 268	49.71 297	86.90 233	89.24 209	67.24 223	59.08 247	82.51 198	47.23 222	83.54 302	48.42 262	57.12 278	83.25 253

mvs_anonymous		81.36 94	79.99 97	85.46 80	90.39 108	68.40 52	86.88 234	90.61 161	74.41 100	70.31 156	84.67 181	63.79 59	92.32 225	73.13 110	85.70 100	95.67 26

v13		70.90 232	68.15 237	79.15 230	80.08 259	66.45 116	86.83 235	86.50 260	67.62 220	53.78 278	71.61 296	53.51 170	89.87 266	62.89 203	50.50 303	81.14 279

v7n		71.31 225	68.65 228	79.28 223	76.40 289	60.77 218	86.71 236	89.45 201	64.17 242	58.77 251	78.24 253	44.59 240	93.54 191	57.76 230	61.75 258	83.52 248

diffmvs		80.18 109	78.55 120	85.07 93	88.56 140	66.93 89	86.70 237	88.62 227	70.42 186	78.69 80	85.26 174	56.93 118	94.77 135	68.68 153	83.09 118	93.51 100

test20.03		63.83 275	62.65 269	67.38 299	70.58 309	39.94 319	86.57 238	84.17 279	63.29 247	51.86 285	77.30 259	37.09 277	82.47 308	38.87 300	54.13 289	79.73 294

UA-Net		80.02 114	79.65 102	81.11 187	89.33 124	57.72 257	86.33 239	89.00 220	77.44 65	81.01 56	89.15 130	59.33 95	95.90 103	61.01 215	84.28 114	89.73 161

v748		70.55 235	67.97 238	78.27 237	75.75 294	58.78 249	86.29 240	89.25 208	65.12 237	56.66 262	77.17 263	45.05 238	92.95 202	58.13 229	58.33 277	83.10 257

DTE-MVSNet		68.46 251	67.33 241	71.87 290	77.94 282	49.00 300	86.16 241	88.58 229	66.36 227	58.19 253	82.21 206	46.36 228	83.87 300	44.97 275	55.17 285	82.73 260

testgi		64.48 271	62.87 268	69.31 294	71.24 304	40.62 318	85.49 242	79.92 301	65.36 234	54.18 274	83.49 191	23.74 314	84.55 293	41.60 285	60.79 267	82.77 259

LS3D		69.17 246	66.40 246	77.50 247	91.92 76	56.12 268	85.12 243	80.37 300	46.96 308	56.50 263	87.51 151	37.25 273	93.71 188	32.52 316	79.40 137	82.68 262

testmvs		7.23 320	9.62 321	0.06 332	0.04 344	0.02 346	84.98 244	0.02 347	0.03 340	0.18 341	1.21 342	0.01 349	0.02 343	0.14 340	0.01 340	0.13 339

testus		59.36 287	57.51 284	64.90 304	66.72 315	37.56 324	84.98 244	81.09 296	57.46 281	47.72 299	72.76 280	11.43 331	78.78 322	36.56 302	58.91 274	78.36 304

HY-MVS	76.49 5	84.28 55	83.36 61	87.02 36	92.22 69	67.74 66	84.65 246	94.50 31	79.15 42	82.23 49	87.93 146	66.88 32	96.94 75	80.53 69	82.20 125	96.39 14

N_pmnet		50.55 298	49.11 300	54.88 315	77.17 286	4.02 344	84.36 247	2.00 345	48.59 304	45.86 304	68.82 303	32.22 292	82.80 307	31.58 318	51.38 296	77.81 305

anonymousdsp		71.14 228	69.37 223	76.45 257	72.95 299	54.71 275	84.19 248	88.88 222	61.92 258	62.15 236	79.77 243	38.14 265	91.44 245	68.90 151	67.45 219	83.21 254

MSDG		69.54 244	65.73 248	80.96 192	85.11 190	63.71 175	84.19 248	83.28 289	56.95 283	54.50 269	84.03 185	31.50 296	96.03 100	42.87 281	69.13 207	83.14 256

COLMAP_ROB	57.96 20	62.98 279	59.65 279	72.98 278	81.44 228	53.00 282	83.75 250	75.53 313	48.34 306	48.81 296	81.40 220	24.14 312	90.30 250	32.95 313	60.52 268	75.65 310
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
testing_2		71.09 229	67.32 242	82.40 154	69.82 310	66.52 115	83.64 251	90.77 155	72.21 146	45.12 307	71.07 300	27.60 307	93.74 187	75.71 97	69.96 199	86.95 199

FMVSNet5		68.04 253	65.66 249	75.18 264	84.43 199	57.89 254	83.54 252	86.26 263	61.83 260	53.64 279	73.30 278	37.15 276	85.08 291	48.99 259	61.77 257	82.56 263

MDA-MVSNet_test_wron		63.78 276	60.16 277	74.64 266	78.15 280	60.41 225	83.49 253	84.03 280	56.17 289	39.17 320	71.59 298	37.22 274	83.24 306	42.87 281	48.73 306	80.26 290

PatchMatch-RL		72.06 218	69.98 217	78.28 236	89.51 123	55.70 270	83.49 253	83.39 288	61.24 262	63.72 224	82.76 196	34.77 285	93.03 200	53.37 247	77.59 153	86.12 212

YYNet1		63.76 277	60.14 278	74.62 267	78.06 281	60.19 231	83.46 255	83.99 284	56.18 288	39.25 319	71.56 299	37.18 275	83.34 304	42.90 280	48.70 307	80.32 289

SixPastTwentyTwo		64.92 268	61.78 274	74.34 270	78.74 275	49.76 296	83.42 256	79.51 303	62.86 251	50.27 292	77.35 258	30.92 300	90.49 249	45.89 271	47.06 309	82.78 258

EU-MVSNet		64.01 274	63.01 266	67.02 300	74.40 297	38.86 323	83.27 257	86.19 264	45.11 314	54.27 272	81.15 227	36.91 279	80.01 316	48.79 261	57.02 279	82.19 265

K. test v3		63.09 278	59.61 280	73.53 274	76.26 290	49.38 299	83.27 257	77.15 306	64.35 241	47.77 298	72.32 288	28.73 303	87.79 283	49.93 257	36.69 323	83.41 251

tpm		78.58 143	77.03 143	83.22 131	85.94 183	64.56 151	83.21 259	91.14 146	78.31 54	73.67 122	79.68 244	64.01 55	92.09 230	66.07 174	71.26 197	93.03 114

MDA-MVSNet-bldmvs		61.54 282	57.70 283	73.05 277	79.53 265	57.00 265	83.08 260	81.23 295	57.57 278	34.91 323	72.45 285	32.79 289	86.26 290	35.81 306	41.95 316	75.89 309

ab-mvs		80.18 109	78.31 122	85.80 70	88.44 145	65.49 137	83.00 261	92.67 89	71.82 159	77.36 92	85.01 177	54.50 154	96.59 86	76.35 95	75.63 167	95.32 37

pmmvs-eth3d		65.53 267	62.32 271	75.19 263	69.39 312	59.59 239	82.80 262	83.43 286	62.52 254	51.30 289	72.49 283	32.86 288	87.16 286	55.32 238	50.73 298	78.83 300

new-patchmatchnet		59.30 288	56.48 288	67.79 297	65.86 316	44.19 309	82.47 263	81.77 293	59.94 269	43.65 313	66.20 307	27.67 306	81.68 313	39.34 293	41.40 317	77.50 306

CostFormer		82.33 81	81.15 84	85.86 67	89.01 133	68.46 51	82.39 264	93.01 77	75.59 84	80.25 63	81.57 217	72.03 12	94.96 130	79.06 78	77.48 157	94.16 79

v52		69.80 241	67.01 244	78.15 240	71.84 303	60.10 232	82.02 265	87.39 244	64.48 239	57.80 256	75.97 270	41.47 251	92.90 207	63.00 200	59.13 272	81.45 271

V4		69.80 241	67.02 243	78.15 240	71.86 302	60.10 232	82.02 265	87.39 244	64.48 239	57.78 257	75.98 269	41.49 250	92.90 207	63.00 200	59.16 271	81.44 272

MTAPA		83.91 61	83.38 60	85.50 78	91.89 78	65.16 141	81.75 267	92.23 102	75.32 91	80.53 60	95.21 34	56.06 131	97.16 59	84.86 42	92.55 44	94.18 76

tpmrst		80.57 102	79.14 115	84.84 99	90.10 111	68.28 57	81.70 268	89.72 196	77.63 62	75.96 102	79.54 247	64.94 51	92.71 212	75.43 98	77.28 160	93.55 99

test123		6.92 321	9.21 322	0.08 331	0.03 345	0.05 345	81.65 269	0.01 348	0.02 341	0.14 342	0.85 343	0.03 348	0.02 343	0.12 341	0.00 342	0.16 338

test1235678		55.73 293	52.74 293	64.68 305	60.16 325	35.56 326	81.65 269	81.46 294	51.27 297	38.93 321	62.82 315	17.44 322	78.58 323	30.87 319	50.09 305	79.89 292

tpmp4_e23		78.85 134	76.55 148	85.77 72	89.25 126	68.39 53	81.63 271	91.38 138	70.40 187	75.21 110	79.22 249	67.37 30	94.79 134	58.98 227	75.51 168	94.13 81

tpm2		79.80 119	77.95 128	85.34 87	88.28 148	68.26 58	81.56 272	91.42 136	70.11 190	77.59 90	80.50 233	67.40 29	94.26 163	67.34 161	77.35 158	93.51 100

UnsupCasMVSNet_eth		65.79 266	63.10 265	73.88 271	70.71 307	50.29 295	81.09 273	89.88 188	72.58 139	49.25 295	74.77 276	32.57 291	87.43 284	55.96 236	41.04 318	83.90 244

Patchmatch-test1		75.00 197	71.80 210	84.58 106	86.63 171	70.08 24	81.06 274	89.19 210	71.60 166	70.01 159	77.16 264	45.53 233	88.63 273	51.79 250	73.27 181	95.02 54

Anonymous20231211		53.57 297	49.43 299	66.00 303	65.01 317	42.08 313	80.95 275	72.60 319	38.46 324	41.65 317	64.48 313	15.72 324	84.23 294	25.78 324	40.24 320	71.68 315

OurMVSNet-221017-0		64.68 269	62.17 272	72.21 285	76.08 292	47.35 305	80.67 276	81.02 297	56.19 287	51.60 286	79.66 245	27.05 309	88.56 276	53.60 245	53.63 290	80.71 285

XVG-OURS-SEG-HR		74.70 200	73.08 196	79.57 215	78.25 279	57.33 262	80.49 277	87.32 247	63.22 248	68.76 181	90.12 125	44.89 239	91.59 238	70.55 138	74.09 177	89.79 159

pmmvs3		55.51 294	51.50 297	67.53 298	57.90 327	50.93 292	80.37 278	73.66 317	40.63 323	44.15 311	64.75 312	16.30 323	78.97 321	44.77 276	40.98 319	72.69 313

XVG-OURS		74.25 203	72.46 204	79.63 213	78.45 278	57.59 260	80.33 279	87.39 244	63.86 244	68.76 181	89.62 129	40.50 255	91.72 236	69.00 149	74.25 175	89.58 162

MDTV_nov1_ep13			72.61 201		89.06 131	68.48 50	80.33 279	90.11 181	71.84 158	71.81 144	75.92 271	53.01 174	93.92 182	48.04 263	73.38 180

EPMVS		78.49 145	75.98 155	86.02 63	91.21 97	69.68 33	80.23 281	91.20 143	75.25 93	72.48 135	78.11 254	54.65 153	93.69 189	57.66 232	83.04 119	94.69 61

AllTest		61.66 280	58.06 281	72.46 282	79.57 263	51.42 289	80.17 282	68.61 326	51.25 298	45.88 302	81.23 222	19.86 320	86.58 288	38.98 294	57.01 280	79.39 296

MDTV_nov1_ep13_2view						59.90 236	80.13 283		67.65 218	72.79 128		54.33 158		59.83 221		92.58 125

LCM-MVSNet-Re		72.93 211	71.84 208	76.18 260	88.49 142	48.02 301	80.07 284	70.17 324	73.96 114	52.25 284	80.09 241	49.98 197	88.24 279	67.35 160	84.23 115	92.28 132

PatchmatchNet		77.46 155	74.63 175	85.96 65	89.55 122	70.35 21	79.97 285	89.55 199	72.23 145	70.94 150	76.91 266	57.03 114	92.79 210	54.27 241	81.17 129	94.74 60
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
dp		75.01 196	72.09 207	83.76 119	89.28 125	66.22 124	79.96 286	89.75 191	71.16 173	67.80 197	77.19 262	51.81 184	92.54 217	50.39 254	71.44 196	92.51 127

1111		56.66 292	54.98 291	61.69 307	61.99 322	31.38 328	79.81 287	83.17 290	45.66 311	41.94 315	65.44 308	41.50 248	79.56 319	27.64 321	47.68 308	74.14 312

.test1245		46.52 302	49.68 298	37.02 324	61.99 322	31.38 328	79.81 287	83.17 290	45.66 311	41.94 315	65.44 308	41.50 248	79.56 319	27.64 321	0.01 340	0.13 339

test_post1							78.95 289				20.70 338	53.05 173	91.50 244	60.43 218

MIMVSNet1		60.16 285	57.33 285	68.67 295	69.71 311	44.13 310	78.92 290	84.21 278	55.05 291	44.63 309	71.85 292	23.91 313	81.54 314	32.63 315	55.03 286	80.35 288

UnsupCasMVSNet_bld		61.60 281	57.71 282	73.29 276	68.73 314	51.64 286	78.61 291	89.05 218	57.20 282	46.11 301	61.96 316	28.70 304	88.60 275	50.08 256	38.90 321	79.63 295

XVG-ACMP-BASELINE		68.04 253	65.53 250	75.56 262	74.06 298	52.37 283	78.43 292	85.88 270	62.03 256	58.91 250	81.21 226	20.38 319	91.15 246	60.69 217	68.18 213	83.16 255

USDC		67.43 259	64.51 257	76.19 259	77.94 282	55.29 272	78.38 293	85.00 274	73.17 129	48.36 297	80.37 235	21.23 318	92.48 220	52.15 249	64.02 246	80.81 284

TinyColmap		60.32 283	56.42 289	72.00 288	78.78 274	53.18 281	78.36 294	75.64 310	52.30 295	41.59 318	75.82 272	14.76 327	88.35 278	35.84 305	54.71 288	74.46 311

tpmvs		72.88 213	69.76 221	82.22 161	90.98 99	67.05 84	78.22 295	88.30 233	63.10 250	64.35 220	74.98 274	55.09 143	94.27 161	43.25 277	69.57 203	85.34 233

tpm cat1		75.30 192	72.21 206	84.58 106	88.52 141	67.77 65	78.16 296	88.02 238	61.88 259	68.45 190	76.37 267	60.65 85	94.03 177	53.77 244	74.11 176	91.93 136

CMPMVS	48.56 21	66.77 261	64.41 259	73.84 272	70.65 308	50.31 294	77.79 297	85.73 272	45.54 313	44.76 308	82.14 207	35.40 282	90.14 257	63.18 198	74.54 174	81.07 281
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
PM-MVS		59.40 286	56.59 287	67.84 296	63.63 318	41.86 315	76.76 298	63.22 332	59.01 274	51.07 290	72.27 289	11.72 329	83.25 305	61.34 213	50.28 304	78.39 303

TDRefinement		55.28 295	51.58 296	66.39 302	59.53 326	46.15 307	76.23 299	72.80 318	44.60 316	42.49 314	76.28 268	15.29 325	82.39 309	33.20 312	43.75 314	70.62 318

RPSCF		64.24 272	61.98 273	71.01 291	76.10 291	45.00 308	75.83 300	75.94 309	46.94 309	58.96 249	84.59 182	31.40 297	82.00 312	47.76 265	60.33 269	86.04 218

GG-mvs-BLEND				86.53 49	91.91 77	69.67 34	75.02 301	94.75 24		78.67 81	90.85 112	77.91 2	94.56 143	72.25 119	93.74 29	95.36 34

testmv		46.98 301	43.53 303	57.35 312	47.75 333	30.41 331	74.99 302	77.69 304	42.84 321	28.03 325	53.36 321	8.18 336	71.18 327	24.36 326	34.55 324	70.46 319

MIMVSNet		71.64 223	68.44 232	81.23 181	81.97 224	64.44 156	73.05 303	88.80 223	69.67 194	64.59 215	74.79 275	32.79 289	87.82 282	53.99 242	76.35 164	91.42 141

gg-mvs-nofinetune		77.18 165	74.31 181	85.80 70	91.42 93	68.36 54	71.78 304	94.72 25	49.61 302	77.12 95	45.92 325	77.41 3	93.98 179	67.62 159	93.16 37	95.05 50

MVS-HIRNet		60.25 284	55.55 290	74.35 269	84.37 200	56.57 266	71.64 305	74.11 316	34.44 326	45.54 306	42.24 328	31.11 299	89.81 267	40.36 291	76.10 165	76.67 308

test12356		47.51 300	44.82 302	55.56 313	52.53 328	21.09 339	71.45 306	76.03 308	44.14 318	30.69 324	58.18 319	9.01 335	76.14 324	26.95 323	34.43 326	69.46 320

CR-MVSNet		73.79 207	70.82 216	82.70 139	83.15 215	67.96 62	70.25 307	84.00 282	73.67 122	69.97 161	72.41 286	57.82 107	89.48 269	52.99 248	73.13 182	90.64 152

RPMNet		69.58 243	65.21 253	82.70 139	83.15 215	67.96 62	70.25 307	86.15 265	46.83 310	69.97 161	65.10 311	56.48 127	89.48 269	35.79 307	73.13 182	90.64 152

Patchmatch-RL test		68.17 252	64.49 258	79.19 227	71.22 305	53.93 278	70.07 309	71.54 323	69.22 198	56.79 261	62.89 314	56.58 125	88.61 274	69.53 145	52.61 291	95.03 53

CHOSEN 280x420		77.35 160	76.95 145	78.55 233	87.07 166	62.68 195	69.71 310	82.95 292	68.80 203	71.48 148	87.27 158	66.03 39	84.00 299	76.47 94	82.81 122	88.95 165

Patchmtry		67.53 257	63.93 261	78.34 234	82.12 222	64.38 159	68.72 311	84.00 282	48.23 307	59.24 245	72.41 286	57.82 107	89.27 271	46.10 270	56.68 282	81.36 274

LF4IMVS		54.01 296	52.12 294	59.69 309	62.41 321	39.91 320	68.59 312	68.28 328	42.96 320	44.55 310	75.18 273	14.09 328	68.39 329	41.36 287	51.68 295	70.78 317

new_pmnet		49.31 299	46.44 301	57.93 310	62.84 320	40.74 317	68.47 313	62.96 333	36.48 325	35.09 322	57.81 320	14.97 326	72.18 326	32.86 314	46.44 310	60.88 325

ADS-MVSNet2		66.90 260	63.44 263	77.26 253	88.06 152	60.70 221	68.01 314	75.56 312	57.57 278	64.48 217	69.87 301	38.68 258	84.10 295	40.87 288	67.89 216	86.97 197

ADS-MVSNet		68.54 250	64.38 260	81.03 191	88.06 152	66.90 90	68.01 314	84.02 281	57.57 278	64.48 217	69.87 301	38.68 258	89.21 272	40.87 288	67.89 216	86.97 197

PatchT		69.11 247	65.37 252	80.32 198	82.07 223	63.68 177	67.96 316	87.62 243	50.86 300	69.37 171	65.18 310	57.09 112	88.53 277	41.59 286	66.60 223	88.74 168

LTVRE_ROB	59.60 19	66.27 263	63.54 262	74.45 268	84.00 206	51.55 287	67.08 317	83.53 285	58.78 275	54.94 267	80.31 236	34.54 286	93.23 197	40.64 290	68.03 214	78.58 302
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
PNet_i23d		32.77 309	29.98 311	41.11 322	48.05 331	29.17 333	65.82 318	50.02 337	21.42 331	14.74 334	37.19 332	1.11 345	55.11 336	19.75 331	11.77 333	39.06 329

FPMVS		45.64 303	43.10 304	53.23 317	51.42 330	36.46 325	64.97 319	71.91 321	29.13 328	27.53 326	61.55 317	9.83 333	65.01 333	16.00 333	55.58 284	58.22 326

DSMNet-mixed		56.78 290	54.44 292	63.79 306	63.21 319	29.44 332	64.43 320	64.10 331	42.12 322	51.32 288	71.60 297	31.76 294	75.04 325	36.23 304	65.20 232	86.87 201

ANet_high		40.27 306	35.20 307	55.47 314	34.74 339	34.47 327	63.84 321	71.56 322	48.42 305	18.80 331	41.08 329	9.52 334	64.45 334	20.18 330	8.66 338	67.49 322

LP		56.71 291	51.64 295	71.91 289	80.08 259	60.33 227	61.72 322	75.61 311	43.87 319	43.76 312	60.30 318	30.46 301	84.05 296	22.94 328	46.06 311	71.34 316

no-one		44.13 304	38.39 305	61.34 308	45.91 335	41.94 314	61.67 323	75.07 315	45.05 315	20.07 329	40.68 331	11.58 330	79.82 317	30.18 320	15.30 331	62.26 324

E-PMN		24.61 313	24.00 314	26.45 327	43.74 336	18.44 341	60.86 324	39.66 339	15.11 334	9.53 337	22.10 335	6.52 338	46.94 338	8.31 337	10.14 334	13.98 335

EMVS		23.76 315	23.20 316	25.46 328	41.52 337	16.90 342	60.56 325	38.79 342	14.62 335	8.99 338	20.24 339	7.35 337	45.82 339	7.25 338	9.46 336	13.64 336

PMMVS2		37.93 307	33.61 308	50.92 318	46.31 334	24.76 337	60.55 326	50.05 336	28.94 329	20.93 328	47.59 323	4.41 342	65.13 332	25.14 325	18.55 330	62.87 323

Patchmatch-test		65.86 265	60.94 276	80.62 195	83.75 207	58.83 248	58.91 327	75.26 314	44.50 317	50.95 291	77.09 265	58.81 101	87.90 281	35.13 308	64.03 245	95.12 48

JIA-IIPM		66.06 264	62.45 270	76.88 255	81.42 229	54.45 277	57.49 328	88.67 225	49.36 303	63.86 222	46.86 324	56.06 131	90.25 251	49.53 258	68.83 208	85.95 219

LCM-MVSNet		40.54 305	35.79 306	54.76 316	36.92 338	30.81 330	51.41 329	69.02 325	22.07 330	24.63 327	45.37 326	4.56 341	65.81 331	33.67 310	34.50 325	67.67 321

PMVS	26.43 22	31.84 310	28.16 312	42.89 321	25.87 342	27.58 335	50.92 330	49.78 338	21.37 332	14.17 335	40.81 330	2.01 343	66.62 330	9.61 336	38.88 322	34.49 332
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
ambc				69.61 293	61.38 324	41.35 316	49.07 331	85.86 271		50.18 294	66.40 306	10.16 332	88.14 280	45.73 272	44.20 313	79.32 298

wuykxyi23d		29.03 312	23.09 317	46.84 319	31.67 341	28.82 334	43.46 332	57.72 335	14.39 336	7.52 339	20.84 337	0.64 346	60.29 335	21.57 329	10.04 335	51.40 328

tmp_tt		22.26 316	23.75 315	17.80 329	5.23 343	12.06 343	35.26 333	39.48 340	2.82 339	18.94 330	44.20 327	22.23 317	24.64 341	36.30 303	9.31 337	16.69 334

testpf		57.17 289	56.93 286	57.88 311	79.13 272	42.40 312	34.23 334	85.97 269	52.64 294	47.66 300	66.50 305	36.33 281	79.65 318	53.60 245	56.31 283	51.60 327

MVE	24.84 23	24.35 314	19.77 318	38.09 323	34.56 340	26.92 336	26.57 335	38.87 341	11.73 337	11.37 336	27.44 333	1.37 344	50.42 337	11.41 335	14.60 332	36.93 330
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
wuyk23d		11.30 318	10.95 319	12.33 330	48.05 331	19.89 340	25.89 336	1.92 346	3.58 338	3.12 340	1.37 341	0.64 346	15.77 342	6.23 339	7.77 339	1.35 337

Gipuma		34.91 308	31.44 310	45.30 320	70.99 306	39.64 322	19.85 337	72.56 320	20.10 333	16.16 333	21.47 336	5.08 340	71.16 328	13.07 334	43.70 315	25.08 333
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
cdsmvs_eth3d_5k		19.86 317	26.47 313	0.00 333	0.00 346	0.00 347	0.00 338	93.45 58	0.00 342	0.00 343	95.27 30	49.56 201	0.00 345	0.00 342	0.00 342	0.00 341

pcd_1.5k_mvsjas		4.46 322	5.95 323	0.00 333	0.00 346	0.00 347	0.00 338	0.00 349	0.00 342	0.00 343	0.00 344	53.55 167	0.00 345	0.00 342	0.00 342	0.00 341

pcd1.5k->3k		31.17 311	31.85 309	29.12 326	81.48 226	0.00 347	0.00 338	91.79 122	0.00 342	0.00 343	0.00 344	41.05 254	0.00 345	0.00 342	72.34 190	87.36 191

sosnet-low-res		0.00 323	0.00 324	0.00 333	0.00 346	0.00 347	0.00 338	0.00 349	0.00 342	0.00 343	0.00 344	0.00 350	0.00 345	0.00 342	0.00 342	0.00 341

sosnet		0.00 323	0.00 324	0.00 333	0.00 346	0.00 347	0.00 338	0.00 349	0.00 342	0.00 343	0.00 344	0.00 350	0.00 345	0.00 342	0.00 342	0.00 341

uncertanet		0.00 323	0.00 324	0.00 333	0.00 346	0.00 347	0.00 338	0.00 349	0.00 342	0.00 343	0.00 344	0.00 350	0.00 345	0.00 342	0.00 342	0.00 341

Regformer		0.00 323	0.00 324	0.00 333	0.00 346	0.00 347	0.00 338	0.00 349	0.00 342	0.00 343	0.00 344	0.00 350	0.00 345	0.00 342	0.00 342	0.00 341

ab-mvs-re		7.91 319	10.55 320	0.00 333	0.00 346	0.00 347	0.00 338	0.00 349	0.00 342	0.00 343	94.95 40	0.00 350	0.00 345	0.00 342	0.00 342	0.00 341

uanet		0.00 323	0.00 324	0.00 333	0.00 346	0.00 347	0.00 338	0.00 349	0.00 342	0.00 343	0.00 344	0.00 350	0.00 345	0.00 342	0.00 342	0.00 341

ESAPD								94.66 27

sam_mvs1												57.85 106

sam_mvs												54.91 150

semantic-postprocess				76.32 258	81.48 226	60.67 222		85.99 268	66.17 228	59.50 244	78.88 250	45.51 234	83.65 301	62.58 207	61.93 255	84.63 240

MTGPA								92.23 102

test_post											23.01 334	56.49 126	92.67 214

patchmatchnet-post											67.62 304	57.62 109	90.25 251

MTMP								32.52 343

gm-plane-assit					88.42 146	67.04 85			78.62 52		91.83 102		97.37 47	76.57 93

test9_res														89.41 10	94.96 8	95.29 38

agg_prior2														86.41 31	94.75 16	95.33 35

agg_prior					94.16 31	66.97 86		93.31 64		84.49 35			96.75 83

TestCases				72.46 282	79.57 263	51.42 289		68.61 326	51.25 298	45.88 302	81.23 222	19.86 320	86.58 288	38.98 294	57.01 280	79.39 296

test_prior				86.42 53	94.71 21	67.35 75		93.10 75					96.84 79			95.05 50

新几何1				84.73 101	92.32 65	64.28 164		91.46 135	59.56 271	79.77 67	92.90 86	56.95 117	96.57 88	63.40 195	92.91 39	93.34 103

旧先验1					91.94 74	60.74 220		91.50 133			94.36 55	65.23 46			91.84 51	94.55 64

原ACMM1				84.42 110	93.21 47	64.27 165		93.40 61	65.39 233	79.51 70	92.50 91	58.11 105	96.69 85	65.27 182	93.96 23	92.32 130

testdata2													96.09 97	61.26 214

segment_acmp												65.94 40

testdata				81.34 179	89.02 132	57.72 257		89.84 189	58.65 276	85.32 29	94.09 64	57.03 114	93.28 196	69.34 147	90.56 69	93.03 114

test12				87.09 34	94.60 23	68.86 44		92.91 81		82.67 48		65.44 45	97.55 41		93.69 31	94.84 58

plane_prior7					86.94 167	61.51 210

plane_prior6					87.23 163	62.32 198						50.66 191

plane_prior5								91.31 140					95.55 120	76.74 91	78.53 146	88.39 174

plane_prior4											89.14 131

plane_prior3						61.95 206			79.09 44	72.53 133

plane_prior1					87.15 164

n2								0.00 349

nn								0.00 349

door-mid								66.01 330

lessismore_v0				73.72 273	72.93 300	47.83 303		61.72 334		45.86 304	73.76 277	28.63 305	89.81 267	47.75 266	31.37 327	83.53 247

LGP-MVS_train				79.56 216	84.31 201	59.37 243		89.73 194	69.49 195	64.86 213	88.42 136	38.65 260	94.30 159	72.56 116	72.76 185	85.01 235

test11								93.01 77

door								66.57 329

HQP5-MVS						63.66 178

BP-MVS														77.63 88

HQP4-MVS										74.18 115			95.61 116			88.63 169

HQP3-MVS								91.70 126							78.90 142

HQP2-MVS												51.63 187

NP-MVS					87.41 162	63.04 185					90.30 120

ACMMP++_ref															71.63 192

ACMMP++															69.72 201

Test By Simon												54.21 160

ITE_SJBPF				70.43 292	74.44 296	47.06 306		77.32 305	60.16 268	54.04 275	83.53 189	23.30 315	84.01 298	43.07 278	61.58 262	80.21 291

DeepMVS_CX				34.71 325	51.45 329	24.73 338		28.48 344	31.46 327	17.49 332	52.75 322	5.80 339	42.60 340	18.18 332	19.42 329	36.81 331

High-resolution multi-view benchmark