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.

MG-MVS		87.11 25	86.27 31	89.62 5	97.79 1	76.27 3	94.96 33	94.49 38	78.74 51	83.87 49	92.94 87	64.34 68	96.94 81	75.19 108	94.09 24	95.66 33

MCST-MVS		91.08 1	91.46 2	89.94 2	97.66 2	73.37 7	97.13 1	95.58 13	89.33 1	85.77 28	96.26 10	72.84 11	99.38 1	92.64 4	95.93 5	97.08 4

DP-MVS Recon		82.73 82	81.65 88	85.98 71	97.31 3	67.06 91	95.15 27	91.99 134	69.08 211	76.50 110	93.89 71	54.48 176	98.20 24	70.76 144	85.66 106	92.69 132

CNVR-MVS		90.32 3	90.89 4	88.61 11	96.76 4	70.65 20	96.47 6	94.83 26	84.83 9	89.07 11	96.80 4	70.86 17	99.06 3	92.64 4	95.71 6	96.12 22

NCCC		89.07 8	89.46 8	87.91 17	96.60 5	69.05 44	96.38 7	94.64 35	84.42 10	86.74 23	96.20 11	66.56 41	98.76 11	89.03 18	94.56 20	95.92 29

AdaColmap		78.94 142	77.00 155	84.76 109	96.34 6	65.86 138	92.66 98	87.97 263	62.18 277	70.56 163	92.37 101	43.53 263	97.35 53	64.50 198	82.86 125	91.05 160

test_part2					96.29 7	68.16 66				90.78 4

v1.0		37.26 332	49.67 324	0.00 357	96.29 7	0.00 372	0.00 363	94.26 45	68.52 221	90.78 4	97.23 3	0.00 374	0.00 369	0.00 366	0.00 366	0.00 367

ESAPD		88.77 9	89.21 9	87.45 30	96.26 9	67.56 78	94.17 39	94.15 47	68.77 215	90.74 6	97.27 2	76.09 4	98.49 16	90.58 10	94.91 11	96.30 16

MAR-MVS		84.18 62	83.43 61	86.44 58	96.25 10	65.93 137	94.28 38	94.27 44	74.41 104	79.16 83	95.61 24	53.99 182	98.88 9	69.62 153	93.26 38	94.50 79
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
API-MVS		82.28 90	80.53 101	87.54 28	96.13 11	70.59 21	93.63 66	91.04 171	65.72 246	75.45 119	92.83 93	56.11 150	98.89 8	64.10 201	89.75 76	93.15 121

APDe-MVS		87.54 19	87.84 16	86.65 48	96.07 12	66.30 128	94.84 35	93.78 53	69.35 205	88.39 14	96.34 9	67.74 32	97.66 38	90.62 9	93.44 36	96.01 26

PAPR		85.15 49	84.47 50	87.18 36	96.02 13	68.29 61	91.85 132	93.00 98	76.59 77	79.03 84	95.00 42	61.59 91	97.61 42	78.16 91	89.00 79	95.63 35

APD-MVS		85.93 41	85.99 35	85.76 81	95.98 14	65.21 150	93.59 68	92.58 113	66.54 238	86.17 24	95.88 17	63.83 72	97.00 73	86.39 35	92.94 40	95.06 56
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
DeepC-MVS_fast	79.48 2	87.95 15	88.00 15	87.79 20	95.86 15	68.32 60	95.74 14	94.11 48	83.82 12	83.49 50	96.19 12	64.53 66	98.44 18	83.42 55	94.88 14	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
DP-MVS		69.90 262	66.48 268	80.14 216	95.36 16	62.93 204	89.56 203	76.11 333	50.27 327	57.69 283	85.23 198	39.68 278	95.73 119	33.35 336	71.05 214	81.78 294

114514_t		79.17 138	77.67 140	83.68 134	95.32 17	65.53 146	92.85 90	91.60 149	63.49 266	67.92 209	90.63 122	46.65 246	95.72 123	67.01 174	83.54 123	89.79 172

Regformer-1		87.24 23	87.60 20	86.15 69	95.14 18	65.83 140	93.95 53	95.12 18	82.11 21	84.25 43	95.73 20	67.88 30	98.35 21	85.60 39	88.64 81	94.26 83

Regformer-2		87.00 27	87.43 22	85.71 84	95.14 18	64.73 162	93.95 53	94.95 23	81.69 26	84.03 47	95.73 20	67.35 35	98.19 25	85.40 41	88.64 81	94.20 85

HPM-MVS++		89.37 7	89.95 7	87.64 23	95.10 20	68.23 65	95.24 24	94.49 38	82.43 17	88.90 12	96.35 8	71.89 16	98.63 13	88.76 20	96.40 2	96.06 23

CSCG		86.87 29	86.26 32	88.72 9	95.05 21	70.79 19	93.83 62	95.33 15	68.48 223	77.63 97	94.35 62	73.04 9	98.45 17	84.92 44	93.71 32	96.92 6

LFMVS		84.34 58	82.73 75	89.18 8	94.76 22	73.25 8	94.99 32	91.89 138	71.90 162	82.16 56	93.49 77	47.98 236	97.05 68	82.55 59	84.82 110	97.25 2

CDPH-MVS		85.71 44	85.46 44	86.46 57	94.75 23	67.19 87	93.89 58	92.83 103	70.90 185	83.09 52	95.28 32	63.62 75	97.36 52	80.63 74	94.18 23	94.84 65

test_prior3		87.38 21	87.70 18	86.42 59	94.71 24	67.35 83	95.10 29	93.10 93	75.40 93	85.25 35	95.61 24	67.94 27	96.84 85	87.47 25	94.77 15	95.05 57

test_prior				86.42 59	94.71 24	67.35 83		93.10 93					96.84 85			95.05 57

test12				87.09 40	94.60 26	68.86 48		92.91 100		82.67 54		65.44 52	97.55 43		93.69 33	94.84 65

0601test		84.28 59	83.16 67	87.64 23	94.52 27	69.24 40	95.78 11	95.09 21	69.19 208	81.09 62	92.88 91	57.00 135	97.44 47	81.11 72	81.76 133	96.23 19

Anonymous20240521		84.28 59	83.16 67	87.64 23	94.52 27	69.24 40	95.78 11	95.09 21	69.19 208	81.09 62	92.88 91	57.00 135	97.44 47	81.11 72	81.76 133	96.23 19

CANet		89.61 6	89.99 6	88.46 13	94.39 29	69.71 34	96.53 5	93.78 53	86.89 4	89.68 8	95.78 18	65.94 46	99.10 2	92.99 1	93.91 27	96.58 11

agg_prior3		86.93 28	87.08 26	86.48 56	94.21 30	66.95 96	94.14 43	93.40 77	71.80 169	84.86 37	95.13 39	66.16 43	97.25 62	89.09 15	94.90 12	95.25 50

test_8					94.19 31	67.19 87	94.15 42	93.42 76	71.87 164	85.38 33	95.35 28	68.19 24	96.95 80

TEST9					94.18 32	67.28 85	94.16 40	93.51 65	71.75 172	85.52 31	95.33 29	68.01 26	97.27 60

train_agg		87.21 24	87.42 23	86.60 50	94.18 32	67.28 85	94.16 40	93.51 65	71.87 164	85.52 31	95.33 29	68.19 24	97.27 60	89.09 15	94.90 12	95.25 50

Regformer-3		85.80 43	85.92 36	85.46 88	94.17 34	65.09 156	92.95 86	95.11 19	81.13 27	81.68 59	95.04 40	65.82 48	98.32 22	83.02 56	84.36 114	92.97 127

Regformer-4		85.45 46	85.69 42	84.73 111	94.17 34	63.23 197	92.95 86	94.83 26	80.66 29	81.29 61	95.04 40	65.12 54	98.08 28	82.74 57	84.36 114	92.88 131

agg_prior1		87.02 26	87.26 25	86.28 66	94.16 36	66.97 94	94.08 46	93.31 81	71.85 166	84.49 41	95.39 27	68.91 20	96.75 89	88.84 19	94.32 22	95.13 54

agg_prior					94.16 36	66.97 94		93.31 81		84.49 41			96.75 89

PAPM_NR		82.97 80	81.84 84	86.37 62	94.10 38	66.76 107	87.66 246	92.84 102	69.96 200	74.07 130	93.57 75	63.10 83	97.50 45	70.66 145	90.58 70	94.85 64

VNet		86.20 38	85.65 43	87.84 19	93.92 39	69.99 28	95.73 16	95.94 12	78.43 53	86.00 26	93.07 84	58.22 121	97.00 73	85.22 42	84.33 117	96.52 13

PVSNet_BlendedMVS		83.38 74	83.43 61	83.22 141	93.76 40	67.53 80	94.06 47	93.61 61	79.13 43	81.00 65	85.14 199	63.19 81	97.29 57	87.08 30	73.91 192	84.83 262

PVSNet_Blended		86.73 33	86.86 29	86.31 65	93.76 40	67.53 80	96.33 8	93.61 61	82.34 18	81.00 65	93.08 82	63.19 81	97.29 57	87.08 30	91.38 61	94.13 91

HFP-MVS		84.73 53	84.40 52	85.72 82	93.75 42	65.01 157	93.50 72	93.19 88	72.19 156	79.22 81	94.93 45	59.04 116	97.67 35	81.55 66	92.21 48	94.49 80

#test#		84.98 51	84.74 49	85.72 82	93.75 42	65.01 157	94.09 45	93.19 88	73.55 130	79.22 81	94.93 45	59.04 116	97.67 35	82.66 58	92.21 48	94.49 80

Anonymous202405211		77.96 163	75.33 183	85.87 74	93.73 44	64.52 164	94.85 34	85.36 297	62.52 275	76.11 111	90.18 129	29.43 327	97.29 57	68.51 163	77.24 171	95.81 31

SD-MVS		87.49 20	87.49 21	87.50 29	93.60 45	68.82 50	93.90 57	92.63 111	76.86 72	87.90 17	95.76 19	66.17 42	97.63 40	89.06 17	91.48 60	96.05 24

ACMMPR		84.37 56	84.06 54	85.28 96	93.56 46	64.37 173	93.50 72	93.15 91	72.19 156	78.85 87	94.86 49	56.69 143	97.45 46	81.55 66	92.20 50	94.02 99

region2R		84.36 57	84.03 55	85.36 94	93.54 47	64.31 175	93.43 75	92.95 99	72.16 159	78.86 86	94.84 50	56.97 137	97.53 44	81.38 69	92.11 52	94.24 84

TSAR-MVS + GP.		87.96 14	88.37 12	86.70 47	93.51 48	65.32 148	95.15 27	93.84 52	78.17 55	85.93 27	94.80 51	75.80 5	98.21 23	89.38 12	88.78 80	96.59 10

PHI-MVS		86.83 31	86.85 30	86.78 46	93.47 49	65.55 145	95.39 22	95.10 20	71.77 171	85.69 30	96.52 6	62.07 88	98.77 10	86.06 37	95.60 7	96.03 25

EPNet		87.84 17	88.38 11	86.23 67	93.30 50	66.05 133	95.26 23	94.84 25	87.09 3	88.06 15	94.53 55	66.79 38	97.34 54	83.89 52	91.68 56	95.29 45
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
XVS		83.87 68	83.47 59	85.05 102	93.22 51	63.78 184	92.92 88	92.66 109	73.99 117	78.18 91	94.31 65	55.25 156	97.41 49	79.16 83	91.58 58	93.95 101

X-MVStestdata		76.86 184	74.13 199	85.05 102	93.22 51	63.78 184	92.92 88	92.66 109	73.99 117	78.18 91	10.19 365	55.25 156	97.41 49	79.16 83	91.58 58	93.95 101

SMA-MVS		88.14 11	88.29 14	87.67 22	93.21 53	68.72 51	93.85 59	94.03 49	74.18 115	91.74 2	96.67 5	65.61 51	98.42 20	89.24 14	96.08 3	95.88 30

原ACMM1				84.42 120	93.21 53	64.27 178		93.40 77	65.39 247	79.51 79	92.50 96	58.11 123	96.69 91	65.27 192	93.96 25	92.32 142

MVS_111021_HR		86.19 39	85.80 39	87.37 32	93.17 55	69.79 32	93.99 51	93.76 56	79.08 45	78.88 85	93.99 69	62.25 87	98.15 26	85.93 38	91.15 64	94.15 90

CP-MVS		83.71 72	83.40 63	84.65 114	93.14 56	63.84 182	94.59 36	92.28 120	71.03 183	77.41 100	94.92 47	55.21 159	96.19 102	81.32 70	90.70 68	93.91 104

DELS-MVS		90.05 4	90.09 5	89.94 2	93.14 56	73.88 6	97.01 2	94.40 42	88.32 2	85.71 29	94.91 48	74.11 8	98.91 6	87.26 28	95.94 4	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
MVS_0304		88.39 10	88.35 13	88.50 12	93.01 58	70.11 25	95.90 10	92.20 127	86.27 6	88.70 13	95.92 16	56.76 139	99.02 4	92.68 3	93.76 30	96.37 15

DeepPCF-MVS	81.17 1	89.72 5	91.38 3	84.72 113	93.00 59	58.16 272	96.72 3	94.41 41	86.50 5	90.25 7	97.83 1	75.46 6	98.67 12	92.78 2	95.49 8	97.32 1

PLC	68.80 14	75.23 209	73.68 206	79.86 225	92.93 60	58.68 270	90.64 179	88.30 256	60.90 285	64.43 244	90.53 123	42.38 267	94.57 155	56.52 245	76.54 175	86.33 231
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
DWT-MVSNet_test		83.95 66	82.80 73	87.41 31	92.90 61	70.07 27	89.12 213	94.42 40	82.15 20	77.64 96	91.77 108	70.81 18	96.22 101	65.03 193	81.36 136	95.94 27

HSP-MVS		90.38 2	91.89 1	85.84 76	92.83 62	64.03 181	93.06 82	94.52 36	82.19 19	93.65 1	96.15 13	85.89 1	97.19 63	91.02 8	97.75 1	96.29 17

mPP-MVS		82.96 81	82.44 78	84.52 118	92.83 62	62.92 206	92.76 91	91.85 140	71.52 178	75.61 117	94.24 66	53.48 191	96.99 76	78.97 86	90.73 67	93.64 110

WTY-MVS		86.32 35	85.81 38	87.85 18	92.82 64	69.37 39	95.20 25	95.25 16	82.71 15	81.91 57	94.73 52	67.93 29	97.63 40	79.55 80	82.25 129	96.54 12

PGM-MVS		83.25 75	82.70 76	84.92 104	92.81 65	64.07 180	90.44 182	92.20 127	71.28 181	77.23 103	94.43 56	55.17 160	97.31 56	79.33 82	91.38 61	93.37 113

EI-MVSNet-Vis-set		83.77 70	83.67 56	84.06 125	92.79 66	63.56 193	91.76 137	94.81 28	79.65 36	77.87 93	94.09 67	63.35 79	97.90 31	79.35 81	79.36 146	90.74 162

MVSTER		82.47 87	82.05 81	83.74 130	92.68 67	69.01 45	91.90 129	93.21 85	79.83 32	72.14 152	85.71 196	74.72 7	94.72 152	75.72 104	72.49 203	87.50 206

MP-MVS		85.02 50	84.97 48	85.17 100	92.60 68	64.27 178	93.24 77	92.27 121	73.13 136	79.63 78	94.43 56	61.90 89	97.17 64	85.00 43	92.56 45	94.06 97
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
thres200		79.66 129	78.33 130	83.66 136	92.54 69	65.82 141	93.06 82	96.31 9	74.90 101	73.30 135	88.66 148	59.67 110	95.61 126	47.84 276	78.67 153	89.56 176

APD-MVS_3200maxsize		81.64 99	81.32 91	82.59 154	92.36 70	58.74 269	91.39 150	91.01 172	63.35 267	79.72 77	94.62 54	51.82 203	96.14 104	79.71 78	87.93 86	92.89 130

PatchFormer-LS_test		83.14 77	81.81 85	87.12 38	92.34 71	69.92 30	88.64 221	93.32 80	82.07 23	74.87 123	91.62 112	68.91 20	96.08 108	66.07 184	78.45 156	95.37 40

新几何1				84.73 111	92.32 72	64.28 177		91.46 155	59.56 295	79.77 76	92.90 89	56.95 138	96.57 94	63.40 206	92.91 41	93.34 114

1121		81.25 104	80.05 104	84.87 107	92.30 73	64.31 175	87.91 235	91.39 157	59.44 296	79.94 74	92.91 88	57.09 131	97.01 71	66.63 176	92.81 43	93.29 117

EI-MVSNet-UG-set		83.14 77	82.96 69	83.67 135	92.28 74	63.19 201	91.38 152	94.68 33	79.22 40	76.60 108	93.75 72	62.64 85	97.76 33	78.07 92	78.01 157	90.05 170

HPM-MVS		83.25 75	82.95 70	84.17 123	92.25 75	62.88 208	90.91 169	91.86 139	70.30 197	77.12 104	93.96 70	56.75 141	96.28 100	82.04 62	91.34 63	93.34 114
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
HY-MVS	76.49 5	84.28 59	83.36 65	87.02 42	92.22 76	67.74 73	84.65 272	94.50 37	79.15 42	82.23 55	87.93 162	66.88 37	96.94 81	80.53 75	82.20 130	96.39 14

tfpn200view9		78.79 146	77.43 146	82.88 145	92.21 77	64.49 165	92.05 116	96.28 10	73.48 131	71.75 157	88.26 156	60.07 107	95.32 135	45.16 285	77.58 162	88.83 180

thres400		78.68 149	77.43 146	82.43 159	92.21 77	64.49 165	92.05 116	96.28 10	73.48 131	71.75 157	88.26 156	60.07 107	95.32 135	45.16 285	77.58 162	87.48 207

PS-MVSNAJ		88.14 11	87.61 19	89.71 4	92.06 79	76.72 1	95.75 13	93.26 83	83.86 11	89.55 9	96.06 14	53.55 187	97.89 32	91.10 6	93.31 37	94.54 76

MSLP-MVS++		86.27 36	85.91 37	87.35 33	92.01 80	68.97 47	95.04 31	92.70 106	79.04 46	81.50 60	96.50 7	58.98 118	96.78 87	83.49 54	93.93 26	96.29 17

旧先验1					91.94 81	60.74 238		91.50 153			94.36 58	65.23 53			91.84 53	94.55 74

thres600view7		78.00 160	76.66 158	82.03 183	91.93 82	63.69 189	91.30 157	96.33 5	72.43 147	70.46 165	87.89 163	60.31 101	94.92 145	42.64 298	76.64 173	87.48 207

LS3D		69.17 269	66.40 269	77.50 272	91.92 83	56.12 294	85.12 269	80.37 326	46.96 334	56.50 288	87.51 171	37.25 295	93.71 203	32.52 341	79.40 145	82.68 288

GG-mvs-BLEND				86.53 55	91.91 84	69.67 36	75.02 326	94.75 30		78.67 89	90.85 118	77.91 2	94.56 156	72.25 127	93.74 31	95.36 41

tfpn111		78.00 160	76.62 159	82.13 177	91.89 85	63.21 198	91.19 163	96.33 5	72.28 151	70.45 166	87.89 163	60.31 101	94.91 146	42.61 299	76.64 173	88.27 192

conf200view11		78.32 157	77.01 153	82.27 170	91.89 85	63.21 198	91.19 163	96.33 5	72.28 151	70.45 166	87.89 163	60.31 101	95.32 135	45.16 285	77.58 162	88.27 192

thres100view900		78.37 155	77.01 153	82.46 155	91.89 85	63.21 198	91.19 163	96.33 5	72.28 151	70.45 166	87.89 163	60.31 101	95.32 135	45.16 285	77.58 162	88.83 180

zzz-MVS		84.73 53	84.47 50	85.50 86	91.89 85	65.16 151	91.55 145	92.23 122	75.32 95	80.53 68	95.21 37	56.06 151	97.16 65	84.86 45	92.55 46	94.18 86

MTAPA		83.91 67	83.38 64	85.50 86	91.89 85	65.16 151	81.75 293	92.23 122	75.32 95	80.53 68	95.21 37	56.06 151	97.16 65	84.86 45	92.55 46	94.18 86

canonicalmvs		86.85 30	86.25 33	88.66 10	91.80 90	71.92 10	93.54 70	91.71 145	80.26 31	87.55 18	95.25 35	63.59 77	96.93 83	88.18 21	84.34 116	97.11 3

TSAR-MVS + MP.		88.11 13	88.64 10	86.54 53	91.73 91	68.04 68	90.36 185	93.55 64	82.89 14	91.29 3	92.89 90	72.27 13	96.03 109	87.99 22	94.77 15	95.54 38

ACMMP		81.49 101	80.67 98	83.93 127	91.71 92	62.90 207	92.13 110	92.22 126	71.79 170	71.68 159	93.49 77	50.32 213	96.96 79	78.47 88	84.22 121	91.93 148
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
BH-RMVSNet		79.46 135	77.65 141	84.89 105	91.68 93	65.66 143	93.55 69	88.09 260	72.93 140	73.37 134	91.12 115	46.20 251	96.12 105	56.28 247	85.61 107	92.91 129

ACMMP_Plus		86.05 40	85.80 39	86.80 45	91.58 94	67.53 80	91.79 134	93.49 67	74.93 100	84.61 38	95.30 31	59.42 112	97.92 30	86.13 36	94.92 10	94.94 63

MVS_Test		84.16 63	83.20 66	87.05 41	91.56 95	69.82 31	89.99 194	92.05 132	77.77 59	82.84 53	86.57 185	63.93 71	96.09 106	74.91 114	89.18 78	95.25 50

HPM-MVS_fast		80.25 117	79.55 115	82.33 167	91.55 96	59.95 253	91.32 156	89.16 234	65.23 250	74.71 124	93.07 84	47.81 238	95.74 118	74.87 116	88.23 83	91.31 158

CPTT-MVS		79.59 131	79.16 123	80.89 209	91.54 97	59.80 255	92.10 112	88.54 253	60.42 288	72.96 137	93.28 79	48.27 232	92.80 224	78.89 87	86.50 100	90.06 169

CNLPA		74.31 224	72.30 227	80.32 213	91.49 98	61.66 225	90.85 170	80.72 325	56.67 310	63.85 248	90.64 120	46.75 244	90.84 270	53.79 255	75.99 178	88.47 188

view600		76.93 180	75.50 179	81.23 195	91.44 99	62.00 219	89.94 195	96.56 1	70.68 189	68.54 200	87.31 174	60.79 95	94.19 178	38.90 313	75.31 181	87.48 207

view800		76.93 180	75.50 179	81.23 195	91.44 99	62.00 219	89.94 195	96.56 1	70.68 189	68.54 200	87.31 174	60.79 95	94.19 178	38.90 313	75.31 181	87.48 207

conf0.05thres1000		76.93 180	75.50 179	81.23 195	91.44 99	62.00 219	89.94 195	96.56 1	70.68 189	68.54 200	87.31 174	60.79 95	94.19 178	38.90 313	75.31 181	87.48 207

tfpn		76.93 180	75.50 179	81.23 195	91.44 99	62.00 219	89.94 195	96.56 1	70.68 189	68.54 200	87.31 174	60.79 95	94.19 178	38.90 313	75.31 181	87.48 207

MP-MVS-pluss		85.24 47	85.13 47	85.56 85	91.42 103	65.59 144	91.54 146	92.51 116	74.56 103	80.62 67	95.64 23	59.15 115	97.00 73	86.94 32	93.80 28	94.07 96
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
gg-mvs-nofinetune		77.18 178	74.31 195	85.80 78	91.42 103	68.36 59	71.78 329	94.72 31	49.61 328	77.12 104	45.92 350	77.41 3	93.98 194	67.62 169	93.16 39	95.05 57

xiu_mvs_v2_base		87.92 16	87.38 24	89.55 7	91.41 105	76.43 2	95.74 14	93.12 92	83.53 13	89.55 9	95.95 15	53.45 192	97.68 34	91.07 7	92.62 44	94.54 76

alignmvs		87.28 22	86.97 27	88.24 15	91.30 106	71.14 18	95.61 18	93.56 63	79.30 38	87.07 22	95.25 35	68.43 22	96.93 83	87.87 23	84.33 117	96.65 8

EPMVS		78.49 154	75.98 167	86.02 70	91.21 107	69.68 35	80.23 306	91.20 163	75.25 97	72.48 147	78.11 278	54.65 173	93.69 204	57.66 244	83.04 124	94.69 68

FMVSNet3		77.73 166	76.04 166	82.80 146	91.20 108	68.99 46	91.87 130	91.99 134	73.35 134	67.04 221	83.19 217	56.62 144	92.14 243	59.80 234	69.34 226	87.28 218

Anonymous20240529		76.84 186	74.15 198	84.88 106	91.02 109	64.95 160	93.84 61	91.09 168	53.57 317	73.00 136	87.42 172	35.91 305	97.32 55	69.14 158	72.41 205	92.36 140

tpmvs		72.88 236	69.76 244	82.22 174	90.98 110	67.05 92	78.22 320	88.30 256	63.10 271	64.35 245	74.98 300	55.09 163	94.27 175	43.25 292	69.57 225	85.34 258

tfpn_ndepth		76.45 192	75.22 185	80.14 216	90.97 111	58.92 266	90.11 190	93.24 84	65.96 243	67.37 219	90.52 124	66.67 39	92.29 241	37.71 319	74.44 187	89.21 178

MVS		84.66 55	82.86 72	90.06 1	90.93 112	74.56 5	87.91 235	95.54 14	68.55 220	72.35 151	94.71 53	59.78 109	98.90 7	81.29 71	94.69 19	96.74 7

PVSNet	73.49 8	80.05 121	78.63 127	84.31 121	90.92 113	64.97 159	92.47 104	91.05 170	79.18 41	72.43 149	90.51 125	37.05 300	94.06 188	68.06 164	86.00 104	93.90 105

3Dnovator+	73.60 7	82.10 95	80.60 100	86.60 50	90.89 114	66.80 106	95.20 25	93.44 75	74.05 116	67.42 216	92.49 97	49.46 222	97.65 39	70.80 143	91.68 56	95.33 42

VDD-MVS		83.06 79	81.81 85	86.81 44	90.86 115	67.70 74	95.40 21	91.50 153	75.46 90	81.78 58	92.34 102	40.09 277	97.13 67	86.85 33	82.04 131	95.60 36

BH-w/o		80.49 114	79.30 120	84.05 126	90.83 116	64.36 174	93.60 67	89.42 225	74.35 109	69.09 190	90.15 130	55.23 158	95.61 126	64.61 196	86.43 101	92.17 146

casdiffmvs1		86.26 37	85.70 41	87.97 16	90.76 117	71.19 15	90.74 175	93.07 95	76.57 78	88.02 16	87.85 167	67.81 31	96.48 97	87.22 29	89.22 77	96.23 19

casdiffmvs		85.23 48	84.38 53	87.79 20	90.73 118	71.38 13	90.71 176	92.52 115	77.08 68	84.58 39	87.18 180	64.43 67	96.34 99	84.32 47	87.86 87	95.65 34

Anonymous20231211		73.08 232	70.39 239	81.13 201	90.62 119	63.33 195	91.40 149	90.06 205	51.84 322	64.46 243	80.67 255	36.49 302	94.07 187	63.83 202	64.17 267	85.98 243

TR-MVS		78.77 147	77.37 149	82.95 144	90.49 120	60.88 233	93.67 65	90.07 203	70.08 199	74.51 125	91.37 113	45.69 252	95.70 124	60.12 232	80.32 141	92.29 143

SteuartSystems-ACMMP		86.82 32	86.90 28	86.58 52	90.42 121	66.38 125	96.09 9	93.87 51	77.73 60	84.01 48	95.66 22	63.39 78	97.94 29	87.40 27	93.55 35	95.42 39
Skip Steuart: Steuart Systems R&D Blog.
TAPA-MVS	70.22 12	74.94 216	73.53 213	79.17 245	90.40 122	52.07 311	89.19 211	89.61 220	62.69 273	70.07 173	92.67 95	48.89 230	94.32 172	38.26 318	79.97 142	91.12 159
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
mvs_anonymous		81.36 103	79.99 106	85.46 88	90.39 123	68.40 57	86.88 261	90.61 182	74.41 104	70.31 171	84.67 204	63.79 73	92.32 240	73.13 118	85.70 105	95.67 32

tfpn1000		75.25 208	74.00 202	79.03 249	90.30 124	57.56 280	88.55 222	93.36 79	64.14 263	65.17 235	89.76 143	67.06 36	91.46 267	34.54 334	73.09 198	88.06 198

CANet_DTU		84.09 64	83.52 57	85.81 77	90.30 124	66.82 100	91.87 130	89.01 241	85.27 7	86.09 25	93.74 73	47.71 239	96.98 77	77.90 94	89.78 75	93.65 109

Fast-Effi-MVS+		81.14 105	80.01 105	84.51 119	90.24 126	65.86 138	94.12 44	89.15 235	73.81 124	75.37 120	88.26 156	57.26 130	94.53 160	66.97 175	84.92 109	93.15 121

tpmrst		80.57 111	79.14 124	84.84 108	90.10 127	68.28 62	81.70 294	89.72 218	77.63 62	75.96 112	79.54 271	64.94 64	92.71 227	75.43 106	77.28 170	93.55 111

PVSNet_Blended_VisFu		83.97 65	83.50 58	85.39 93	90.02 128	66.59 118	93.77 63	91.73 143	77.43 66	77.08 106	89.81 141	63.77 74	96.97 78	79.67 79	88.21 84	92.60 135

UGNet		79.87 125	78.68 126	83.45 140	89.96 129	61.51 227	92.13 110	90.79 175	76.83 73	78.85 87	86.33 188	38.16 286	96.17 103	67.93 166	87.17 91	92.67 133
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
CHOSEN 1792x2688		84.98 51	83.45 60	89.57 6	89.94 130	75.14 4	92.07 115	92.32 119	81.87 25	75.68 114	88.27 155	60.18 106	98.60 14	80.46 76	90.27 73	94.96 62

abl_6		79.82 126	79.20 122	81.70 189	89.85 131	58.34 271	88.47 224	90.07 203	62.56 274	77.71 95	93.08 82	47.65 240	96.78 87	77.94 93	85.45 108	89.99 171

BH-untuned		78.68 149	77.08 151	83.48 139	89.84 132	63.74 186	92.70 94	88.59 251	71.57 176	66.83 224	88.65 149	51.75 205	95.39 133	59.03 237	84.77 111	91.32 157

test222					89.77 133	61.60 226	89.55 204	89.42 225	56.83 309	77.28 102	92.43 99	52.76 196			91.14 65	93.09 123

PMMVS		81.98 97	82.04 82	81.78 185	89.76 134	56.17 293	91.13 166	90.69 178	77.96 57	80.09 73	93.57 75	46.33 249	94.99 141	81.41 68	87.46 90	94.17 88

conf0.01		74.95 214	73.61 207	78.96 250	89.65 135	56.94 286	87.72 239	93.45 68	65.14 251	65.68 227	89.99 134	65.09 55	91.67 253	35.16 326	70.61 215	88.27 192

conf0.002		74.95 214	73.61 207	78.96 250	89.65 135	56.94 286	87.72 239	93.45 68	65.14 251	65.68 227	89.99 134	65.09 55	91.67 253	35.16 326	70.61 215	88.27 192

thresconf0.02		74.92 217	73.61 207	78.85 253	89.65 135	56.94 286	87.72 239	93.45 68	65.14 251	65.68 227	89.99 134	65.09 55	91.67 253	35.16 326	70.61 215	87.94 199

tfpn_n400		74.92 217	73.61 207	78.85 253	89.65 135	56.94 286	87.72 239	93.45 68	65.14 251	65.68 227	89.99 134	65.09 55	91.67 253	35.16 326	70.61 215	87.94 199

tfpnconf		74.92 217	73.61 207	78.85 253	89.65 135	56.94 286	87.72 239	93.45 68	65.14 251	65.68 227	89.99 134	65.09 55	91.67 253	35.16 326	70.61 215	87.94 199

tfpnview11		74.92 217	73.61 207	78.85 253	89.65 135	56.94 286	87.72 239	93.45 68	65.14 251	65.68 227	89.99 134	65.09 55	91.67 253	35.16 326	70.61 215	87.94 199

QAPM		79.95 124	77.39 148	87.64 23	89.63 141	71.41 12	93.30 76	93.70 58	65.34 249	67.39 218	91.75 110	47.83 237	98.96 5	57.71 243	89.81 74	92.54 137

3Dnovator	73.91 6	82.69 85	80.82 96	88.31 14	89.57 142	71.26 14	92.60 99	94.39 43	78.84 48	67.89 211	92.48 98	48.42 231	98.52 15	68.80 162	94.40 21	95.15 53

Effi-MVS+		83.82 69	82.76 74	86.99 43	89.56 143	69.40 38	91.35 154	86.12 289	72.59 144	83.22 51	92.81 94	59.60 111	96.01 111	81.76 64	87.80 88	95.56 37

PatchmatchNet		77.46 168	74.63 189	85.96 72	89.55 144	70.35 23	79.97 310	89.55 221	72.23 154	70.94 162	76.91 290	57.03 133	92.79 225	54.27 253	81.17 137	94.74 67
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
PatchMatch-RL		72.06 241	69.98 240	78.28 261	89.51 145	55.70 296	83.49 279	83.39 313	61.24 284	63.72 249	82.76 219	34.77 309	93.03 215	53.37 259	77.59 161	86.12 236

thisisatest0515		83.41 73	82.49 77	86.16 68	89.46 146	68.26 63	93.54 70	94.70 32	74.31 110	75.75 113	90.92 116	72.62 12	96.52 96	69.64 151	81.50 135	93.71 107

UA-Net		80.02 122	79.65 111	81.11 202	89.33 147	57.72 276	86.33 265	89.00 242	77.44 65	81.01 64	89.15 145	59.33 113	95.90 112	61.01 227	84.28 119	89.73 174

dp		75.01 212	72.09 229	83.76 129	89.28 148	66.22 131	79.96 311	89.75 213	71.16 182	67.80 213	77.19 286	51.81 204	92.54 232	50.39 266	71.44 212	92.51 138

tpmp4_e23		78.85 143	76.55 160	85.77 80	89.25 149	68.39 58	81.63 297	91.38 158	70.40 195	75.21 121	79.22 273	67.37 34	94.79 147	58.98 239	75.51 180	94.13 91

sss		82.71 84	82.38 79	83.73 132	89.25 149	59.58 258	92.24 108	94.89 24	77.96 57	79.86 75	92.38 100	56.70 142	97.05 68	77.26 98	80.86 140	94.55 74

MVSFormer		83.75 71	82.88 71	86.37 62	89.24 151	71.18 16	89.07 214	90.69 178	65.80 244	87.13 20	94.34 63	64.99 62	92.67 229	72.83 121	91.80 54	95.27 47

lupinMVS		87.74 18	87.77 17	87.63 27	89.24 151	71.18 16	96.57 4	92.90 101	82.70 16	87.13 20	95.27 33	64.99 62	95.80 115	89.34 13	91.80 54	95.93 28

IB-MVS	77.80 4	82.18 91	80.46 102	87.35 33	89.14 153	70.28 24	95.59 19	95.17 17	78.85 47	70.19 172	85.82 193	70.66 19	97.67 35	72.19 130	66.52 246	94.09 94
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
MDTV_nov1_ep13			72.61 223		89.06 154	68.48 55	80.33 304	90.11 202	71.84 167	71.81 156	75.92 297	53.01 194	93.92 197	48.04 275	73.38 194

testdata				81.34 193	89.02 155	57.72 276		89.84 211	58.65 300	85.32 34	94.09 67	57.03 133	93.28 211	69.34 156	90.56 71	93.03 125

CostFormer		82.33 89	81.15 92	85.86 75	89.01 156	68.46 56	82.39 290	93.01 96	75.59 88	80.25 72	81.57 240	72.03 15	94.96 142	79.06 85	77.48 167	94.16 89

GBi-Net		75.65 202	73.83 204	81.10 203	88.85 157	65.11 153	90.01 191	90.32 189	70.84 186	67.04 221	80.25 262	48.03 233	91.54 262	59.80 234	69.34 226	86.64 227

test1		75.65 202	73.83 204	81.10 203	88.85 157	65.11 153	90.01 191	90.32 189	70.84 186	67.04 221	80.25 262	48.03 233	91.54 262	59.80 234	69.34 226	86.64 227

FMVSNet2		76.07 196	74.01 201	82.26 173	88.85 157	67.66 75	91.33 155	91.61 148	70.84 186	65.98 226	82.25 227	48.03 233	92.00 248	58.46 240	68.73 232	87.10 220

DeepC-MVS	77.85 3	85.52 45	85.24 46	86.37 62	88.80 160	66.64 115	92.15 109	93.68 59	81.07 28	76.91 107	93.64 74	62.59 86	98.44 18	85.50 40	92.84 42	94.03 98
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
EPP-MVSNet		81.79 98	81.52 89	82.61 153	88.77 161	60.21 248	93.02 84	93.66 60	68.52 221	72.90 139	90.39 126	72.19 14	94.96 142	74.93 113	79.29 148	92.67 133

1112_ss		80.56 112	79.83 109	82.77 147	88.65 162	60.78 235	92.29 106	88.36 255	72.58 145	72.46 148	94.95 43	65.09 55	93.42 210	66.38 180	77.71 159	94.10 93

tpm cat1		75.30 207	72.21 228	84.58 116	88.52 163	67.77 72	78.16 321	88.02 261	61.88 281	68.45 205	76.37 291	60.65 99	94.03 192	53.77 256	74.11 189	91.93 148

LCM-MVSNet-Re		72.93 234	71.84 230	76.18 285	88.49 164	48.02 327	80.07 309	70.17 349	73.96 120	52.25 311	80.09 265	49.98 217	88.24 304	67.35 170	84.23 120	92.28 144

Vis-MVSNet		80.92 109	79.98 107	83.74 130	88.48 165	61.80 224	93.44 74	88.26 259	73.96 120	77.73 94	91.76 109	49.94 218	94.76 149	65.84 187	90.37 72	94.65 71
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
Vis-MVSNet (Re-imp)		79.24 137	79.57 112	78.24 264	88.46 166	52.29 310	90.41 184	89.12 236	74.24 111	69.13 189	91.91 106	65.77 49	90.09 284	59.00 238	88.09 85	92.33 141

ab-mvs		80.18 118	78.31 131	85.80 78	88.44 167	65.49 147	83.00 287	92.67 108	71.82 168	77.36 101	85.01 200	54.50 174	96.59 92	76.35 103	75.63 179	95.32 44

gm-plane-assit					88.42 168	67.04 93			78.62 52		91.83 107		97.37 51	76.57 101

MVS_111021_LR		82.02 96	81.52 89	83.51 138	88.42 168	62.88 208	89.77 201	88.93 243	76.78 74	75.55 118	93.10 80	50.31 214	95.38 134	83.82 53	87.02 92	92.26 145

tpm2		79.80 127	77.95 137	85.34 95	88.28 170	68.26 63	81.56 298	91.42 156	70.11 198	77.59 99	80.50 257	67.40 33	94.26 177	67.34 171	77.35 168	93.51 112

Test_1112_low_res		79.56 132	78.60 128	82.43 159	88.24 171	60.39 244	92.09 113	87.99 262	72.10 160	71.84 155	87.42 172	64.62 65	93.04 214	65.80 188	77.30 169	93.85 106

PAPM		85.89 42	85.46 44	87.18 36	88.20 172	72.42 9	92.41 105	92.77 104	82.11 21	80.34 71	93.07 84	68.27 23	95.02 140	78.39 90	93.59 34	94.09 94

TESTMET0.1,1		82.41 88	81.98 83	83.72 133	88.08 173	63.74 186	92.70 94	93.77 55	79.30 38	77.61 98	87.57 170	58.19 122	94.08 186	73.91 117	86.68 96	93.33 116

diffmvs1		82.57 86	81.71 87	85.15 101	88.07 174	66.09 132	87.52 249	88.92 244	76.45 82	80.41 70	87.04 181	60.29 105	94.77 148	80.30 77	86.36 102	94.59 72

ADS-MVSNet2		66.90 285	63.44 288	77.26 278	88.06 175	60.70 239	68.01 339	75.56 338	57.57 302	64.48 241	69.87 327	38.68 280	84.10 319	40.87 304	67.89 238	86.97 221

ADS-MVSNet		68.54 273	64.38 284	81.03 206	88.06 175	66.90 97	68.01 339	84.02 306	57.57 302	64.48 241	69.87 327	38.68 280	89.21 297	40.87 304	67.89 238	86.97 221

EPNet_dtu		78.80 145	79.26 121	77.43 274	88.06 175	49.71 323	91.96 122	91.95 137	77.67 61	76.56 109	91.28 114	58.51 120	90.20 279	56.37 246	80.95 139	92.39 139
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
diffmvs		81.52 100	80.44 103	84.76 109	87.98 178	65.79 142	86.97 259	88.84 246	76.57 78	78.24 90	85.79 195	58.10 124	94.55 157	77.40 97	84.11 122	93.95 101

IS-MVSNet		80.14 119	79.41 117	82.33 167	87.91 179	60.08 252	91.97 121	88.27 258	72.90 141	71.44 161	91.73 111	61.44 92	93.66 205	62.47 220	86.53 99	93.24 118

CLD-MVS		82.73 82	82.35 80	83.86 128	87.90 180	67.65 76	95.45 20	92.18 130	85.06 8	72.58 144	92.27 103	52.46 200	95.78 116	84.18 48	79.06 149	88.16 196
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
HyFIR lowres test		81.03 107	79.56 113	85.43 91	87.81 181	68.11 67	90.18 189	90.01 207	70.65 193	72.95 138	86.06 191	63.61 76	94.50 161	75.01 112	79.75 144	93.67 108

1314		80.70 110	78.95 125	85.94 73	87.77 182	67.56 78	87.91 235	92.55 114	72.17 158	67.44 215	93.09 81	50.27 215	97.04 70	71.68 133	87.64 89	93.23 119

HQP-NCC					87.54 183		94.06 47		79.80 33	74.18 126

ACMP_Plane					87.54 183		94.06 47		79.80 33	74.18 126

HQP-MVS		81.14 105	80.64 99	82.64 152	87.54 183	63.66 191	94.06 47	91.70 146	79.80 33	74.18 126	90.30 127	51.63 207	95.61 126	77.63 95	78.90 150	88.63 184

NP-MVS					87.41 186	63.04 202					90.30 127

plane_prior6					87.23 187	62.32 215						50.66 211

tttt0517		79.50 133	78.53 129	82.41 165	87.22 188	61.43 229	89.75 202	94.76 29	69.29 206	67.91 210	88.06 161	72.92 10	95.63 125	62.91 214	73.90 193	90.16 168

plane_prior1					87.15 189

cascas		78.18 158	75.77 170	85.41 92	87.14 190	69.11 43	92.96 85	91.15 165	66.71 237	70.47 164	86.07 190	37.49 294	96.48 97	70.15 148	79.80 143	90.65 163

CHOSEN 280x420		77.35 173	76.95 156	78.55 258	87.07 191	62.68 212	69.71 335	82.95 317	68.80 214	71.48 160	87.27 179	66.03 45	84.00 323	76.47 102	82.81 127	88.95 179

HQP_MVS		80.34 116	79.75 110	82.12 178	86.94 192	62.42 213	93.13 80	91.31 160	78.81 49	72.53 145	89.14 146	50.66 211	95.55 130	76.74 99	78.53 154	88.39 189

plane_prior7					86.94 192	61.51 227

test-LLR		80.10 120	79.56 113	81.72 187	86.93 194	61.17 230	92.70 94	91.54 150	71.51 179	75.62 115	86.94 182	53.83 183	92.38 237	72.21 128	84.76 112	91.60 151

test-mter		79.96 123	79.38 119	81.72 187	86.93 194	61.17 230	92.70 94	91.54 150	73.85 122	75.62 115	86.94 182	49.84 220	92.38 237	72.21 128	84.76 112	91.60 151

Patchmatch-test1		75.00 213	71.80 232	84.58 116	86.63 196	70.08 26	81.06 300	89.19 232	71.60 175	70.01 174	77.16 288	45.53 253	88.63 298	51.79 262	73.27 195	95.02 61

xiu_mvs_v1_base_debu		82.16 92	81.12 93	85.26 97	86.42 197	68.72 51	92.59 101	90.44 183	73.12 137	84.20 44	94.36 58	38.04 288	95.73 119	84.12 49	86.81 93	91.33 154

xiu_mvs_v1_base		82.16 92	81.12 93	85.26 97	86.42 197	68.72 51	92.59 101	90.44 183	73.12 137	84.20 44	94.36 58	38.04 288	95.73 119	84.12 49	86.81 93	91.33 154

xiu_mvs_v1_base_debi		82.16 92	81.12 93	85.26 97	86.42 197	68.72 51	92.59 101	90.44 183	73.12 137	84.20 44	94.36 58	38.04 288	95.73 119	84.12 49	86.81 93	91.33 154

F-COLMAP		70.66 256	68.44 255	77.32 276	86.37 200	55.91 295	88.00 231	86.32 284	56.94 308	57.28 285	88.07 160	33.58 311	92.49 234	51.02 264	68.37 234	83.55 271

CDS-MVSNet		81.43 102	80.74 97	83.52 137	86.26 201	64.45 168	92.09 113	90.65 181	75.83 87	73.95 132	89.81 141	63.97 70	92.91 221	71.27 137	82.82 126	93.20 120
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
VDDNet		80.50 113	78.26 132	87.21 35	86.19 202	69.79 32	94.48 37	91.31 160	60.42 288	79.34 80	90.91 117	38.48 284	96.56 95	82.16 60	81.05 138	95.27 47

jason		86.40 34	86.17 34	87.11 39	86.16 203	70.54 22	95.71 17	92.19 129	82.00 24	84.58 39	94.34 63	61.86 90	95.53 132	87.76 24	90.89 66	95.27 47
jason: jason.
PCF-MVS	73.15 9	79.29 136	77.63 142	84.29 122	86.06 204	65.96 136	87.03 255	91.10 167	69.86 201	69.79 179	90.64 120	57.54 129	96.59 92	64.37 200	82.29 128	90.32 166
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
MS-PatchMatch		77.90 165	76.50 161	82.12 178	85.99 205	69.95 29	91.75 139	92.70 106	73.97 119	62.58 259	84.44 207	41.11 273	95.78 116	63.76 203	92.17 51	80.62 313

FIs		79.47 134	79.41 117	79.67 229	85.95 206	59.40 260	91.68 141	93.94 50	78.06 56	68.96 193	88.28 154	66.61 40	91.77 251	66.20 183	74.99 185	87.82 203

VPA-MVSNet		79.03 139	78.00 136	82.11 181	85.95 206	64.48 167	93.22 79	94.66 34	75.05 99	74.04 131	84.95 201	52.17 202	93.52 207	74.90 115	67.04 242	88.32 191

tpm		78.58 152	77.03 152	83.22 141	85.94 208	64.56 163	83.21 285	91.14 166	78.31 54	73.67 133	79.68 268	64.01 69	92.09 246	66.07 184	71.26 213	93.03 125

OpenMVS	70.45 11	78.54 153	75.92 168	86.41 61	85.93 209	71.68 11	92.74 92	92.51 116	66.49 239	64.56 240	91.96 105	43.88 262	98.10 27	54.61 251	90.65 69	89.44 177

OMC-MVS		78.67 151	77.91 139	80.95 208	85.76 210	57.40 281	88.49 223	88.67 249	73.85 122	72.43 149	92.10 104	49.29 224	94.55 157	72.73 123	77.89 158	90.91 161

EI-MVSNet		78.97 141	78.22 133	81.25 194	85.33 211	62.73 211	89.53 206	93.21 85	72.39 149	72.14 152	90.13 131	60.99 93	94.72 152	67.73 168	72.49 203	86.29 232

CVMVSNet		74.04 226	74.27 196	73.33 300	85.33 211	43.94 337	89.53 206	88.39 254	54.33 316	70.37 169	90.13 131	49.17 226	84.05 320	61.83 224	79.36 146	91.99 147

ACMH	63.93 17	68.62 271	64.81 277	80.03 220	85.22 213	63.25 196	87.72 239	84.66 301	60.83 286	51.57 314	79.43 272	27.29 333	94.96 142	41.76 300	64.84 261	81.88 293
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
TAMVS		80.37 115	79.45 116	83.13 143	85.14 214	63.37 194	91.23 159	90.76 177	74.81 102	72.65 142	88.49 150	60.63 100	92.95 217	69.41 155	81.95 132	93.08 124

MSDG		69.54 267	65.73 271	80.96 207	85.11 215	63.71 188	84.19 274	83.28 314	56.95 307	54.50 295	84.03 208	31.50 320	96.03 109	42.87 296	69.13 229	83.14 281

ACMP	71.68 10	75.58 205	74.23 197	79.62 231	84.97 216	59.64 256	90.80 172	89.07 239	70.39 196	62.95 255	87.30 178	38.28 285	93.87 199	72.89 120	71.45 211	85.36 257
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
FC-MVSNet-test		77.99 162	78.08 135	77.70 269	84.89 217	55.51 297	90.27 187	93.75 57	76.87 71	66.80 225	87.59 169	65.71 50	90.23 278	62.89 215	73.94 191	87.37 214

PVSNet_0	68.08 15	71.81 243	68.32 257	82.27 170	84.68 218	62.31 216	88.68 219	90.31 192	75.84 86	57.93 280	80.65 256	37.85 291	94.19 178	69.94 149	29.05 352	90.31 167

WR-MVS		76.76 188	75.74 171	79.82 226	84.60 219	62.27 217	92.60 99	92.51 116	76.06 84	67.87 212	85.34 197	56.76 139	90.24 277	62.20 221	63.69 272	86.94 224

ACMH+	65.35 16	67.65 280	64.55 280	76.96 279	84.59 220	57.10 284	88.08 230	80.79 324	58.59 301	53.00 308	81.09 251	26.63 335	92.95 217	46.51 280	61.69 284	80.82 310

VPNet		78.82 144	77.53 144	82.70 149	84.52 221	66.44 124	93.93 55	92.23 122	80.46 30	72.60 143	88.38 153	49.18 225	93.13 213	72.47 126	63.97 270	88.55 186

IterMVS-LS		76.49 190	75.18 186	80.43 212	84.49 222	62.74 210	90.64 179	88.80 247	72.40 148	65.16 236	81.72 239	60.98 94	92.27 242	67.74 167	64.65 264	86.29 232
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
UniMVSNet_NR-MVSNet		78.15 159	77.55 143	79.98 221	84.46 223	60.26 246	92.25 107	93.20 87	77.50 64	68.88 194	86.61 184	66.10 44	92.13 244	66.38 180	62.55 273	87.54 205

FMVSNet5		68.04 277	65.66 272	75.18 289	84.43 224	57.89 273	83.54 278	86.26 286	61.83 282	53.64 305	73.30 304	37.15 298	85.08 316	48.99 271	61.77 280	82.56 290

MVS-HIRNet		60.25 309	55.55 315	74.35 294	84.37 225	56.57 292	71.64 330	74.11 342	34.44 351	45.54 333	42.24 353	31.11 323	89.81 291	40.36 307	76.10 177	76.67 335

LPG-MVS_test		75.82 201	74.58 191	79.56 233	84.31 226	59.37 261	90.44 182	89.73 216	69.49 203	64.86 237	88.42 151	38.65 282	94.30 173	72.56 124	72.76 200	85.01 260

LGP-MVS_train				79.56 233	84.31 226	59.37 261		89.73 216	69.49 203	64.86 237	88.42 151	38.65 282	94.30 173	72.56 124	72.76 200	85.01 260

ACMM	69.62 13	74.34 223	72.73 221	79.17 245	84.25 228	57.87 274	90.36 185	89.93 209	63.17 270	65.64 233	86.04 192	37.79 292	94.10 184	65.89 186	71.52 210	85.55 254
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
UniMVSNet (Re)		77.58 167	76.78 157	79.98 221	84.11 229	60.80 234	91.76 137	93.17 90	76.56 80	69.93 178	84.78 203	63.32 80	92.36 239	64.89 194	62.51 275	86.78 226

test_0402		64.54 295	61.09 300	74.92 290	84.10 230	60.75 237	87.95 232	79.71 328	52.03 321	52.41 310	77.20 285	32.21 317	91.64 259	23.14 351	61.03 287	72.36 341

LTVRE_ROB	59.60 19	66.27 288	63.54 287	74.45 293	84.00 231	51.55 313	67.08 342	83.53 310	58.78 299	54.94 293	80.31 260	34.54 310	93.23 212	40.64 306	68.03 236	78.58 329
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
Patchmatch-test		65.86 290	60.94 301	80.62 210	83.75 232	58.83 267	58.91 352	75.26 340	44.50 343	50.95 318	77.09 289	58.81 119	87.90 306	35.13 332	64.03 268	95.12 55

nrg030		80.93 108	79.86 108	84.13 124	83.69 233	68.83 49	93.23 78	91.20 163	75.55 89	75.06 122	88.22 159	63.04 84	94.74 151	81.88 63	66.88 243	88.82 182

GA-MVS		78.33 156	76.23 164	84.65 114	83.65 234	66.30 128	91.44 147	90.14 201	76.01 85	70.32 170	84.02 209	42.50 266	94.72 152	70.98 141	77.00 172	92.94 128

FMVSNet1		72.71 238	69.91 242	81.10 203	83.60 235	65.11 153	90.01 191	90.32 189	63.92 264	63.56 250	80.25 262	36.35 303	91.54 262	54.46 252	66.75 244	86.64 227

OPM-MVS		79.00 140	78.09 134	81.73 186	83.52 236	63.83 183	91.64 144	90.30 193	76.36 83	71.97 154	89.93 140	46.30 250	95.17 139	75.10 109	77.70 160	86.19 234

tfpnnormal		70.10 260	67.36 263	78.32 260	83.45 237	60.97 232	88.85 216	92.77 104	64.85 258	60.83 264	78.53 276	43.52 264	93.48 208	31.73 342	61.70 283	80.52 314

Effi-MVS+-dtu		76.14 195	75.28 184	78.72 257	83.22 238	55.17 299	89.87 199	87.78 264	75.42 91	67.98 208	81.43 241	45.08 256	92.52 233	75.08 110	71.63 208	88.48 187

mvs-test1		78.74 148	77.95 137	81.14 200	83.22 238	57.13 283	93.96 52	87.78 264	75.42 91	72.68 141	90.80 119	45.08 256	94.54 159	75.08 110	77.49 166	91.74 150

CR-MVSNet		73.79 229	70.82 238	82.70 149	83.15 240	67.96 69	70.25 332	84.00 307	73.67 128	69.97 176	72.41 312	57.82 126	89.48 294	52.99 260	73.13 196	90.64 164

RPMNet		69.58 266	65.21 276	82.70 149	83.15 240	67.96 69	70.25 332	86.15 288	46.83 336	69.97 176	65.10 337	56.48 147	89.48 294	35.79 325	73.13 196	90.64 164

DU-MVS		76.86 184	75.84 169	79.91 223	82.96 242	60.26 246	91.26 158	91.54 150	76.46 81	68.88 194	86.35 186	56.16 148	92.13 244	66.38 180	62.55 273	87.35 216

NR-MVSNet		76.05 197	74.59 190	80.44 211	82.96 242	62.18 218	90.83 171	91.73 143	77.12 67	60.96 263	86.35 186	59.28 114	91.80 250	60.74 228	61.34 286	87.35 216

XXY-MVS		77.94 164	76.44 162	82.43 159	82.60 244	64.44 169	92.01 118	91.83 141	73.59 129	70.00 175	85.82 193	54.43 177	94.76 149	69.63 152	68.02 237	88.10 197

TranMVSNet+NR-MVSNet		75.86 200	74.52 193	79.89 224	82.44 245	60.64 241	91.37 153	91.37 159	76.63 76	67.65 214	86.21 189	52.37 201	91.55 261	61.84 223	60.81 289	87.48 207

IterMVS		72.65 240	70.83 237	78.09 267	82.17 246	62.96 203	87.64 247	86.28 285	71.56 177	60.44 265	78.85 275	45.42 255	86.66 312	63.30 207	61.83 279	84.65 264
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
Patchmtry		67.53 282	63.93 285	78.34 259	82.12 247	64.38 172	68.72 336	84.00 307	48.23 333	59.24 270	72.41 312	57.82 126	89.27 296	46.10 282	56.68 305	81.36 301

PatchT		69.11 270	65.37 275	80.32 213	82.07 248	63.68 190	67.96 341	87.62 266	50.86 326	69.37 186	65.18 336	57.09 131	88.53 302	41.59 302	66.60 245	88.74 183

MIMVSNet		71.64 246	68.44 255	81.23 195	81.97 249	64.44 169	73.05 328	88.80 247	69.67 202	64.59 239	74.79 301	32.79 313	87.82 307	53.99 254	76.35 176	91.42 153

MVP-Stereo		77.12 179	76.23 164	79.79 227	81.72 250	66.34 127	89.29 208	90.88 173	70.56 194	62.01 262	82.88 218	49.34 223	94.13 183	65.55 190	93.80 28	78.88 326
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
semantic-postprocess				76.32 283	81.48 251	60.67 240		85.99 291	66.17 241	59.50 269	78.88 274	45.51 254	83.65 325	62.58 219	61.93 278	84.63 265

pcd1.5k->3k		31.17 336	31.85 334	29.12 350	81.48 251	0.00 372	0.00 363	91.79 142	0.00 367	0.00 369	0.00 369	41.05 274	0.00 369	0.00 366	72.34 206	87.36 215

COLMAP_ROB	57.96 20	62.98 304	59.65 304	72.98 303	81.44 253	53.00 308	83.75 276	75.53 339	48.34 332	48.81 323	81.40 243	24.14 337	90.30 274	32.95 338	60.52 291	75.65 337
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
JIA-IIPM		66.06 289	62.45 295	76.88 280	81.42 254	54.45 303	57.49 353	88.67 249	49.36 329	63.86 247	46.86 349	56.06 151	90.25 275	49.53 270	68.83 230	85.95 244

WR-MVS_H		70.59 257	69.94 241	72.53 306	81.03 255	51.43 314	87.35 252	92.03 133	67.38 234	60.23 266	80.70 253	55.84 155	83.45 327	46.33 281	58.58 299	82.72 286

DI_MVS_plusplus_test		79.78 128	77.50 145	86.62 49	80.90 256	69.46 37	90.69 177	91.97 136	77.00 69	59.07 273	82.34 225	46.82 243	95.88 113	82.14 61	86.59 98	94.53 78

Fast-Effi-MVS+-dtu		75.04 211	73.37 216	80.07 219	80.86 257	59.52 259	91.20 162	85.38 296	71.90 162	65.20 234	84.84 202	41.46 272	92.97 216	66.50 179	72.96 199	87.73 204

Baseline_NR-MVSNet		73.99 227	72.83 220	77.48 273	80.78 258	59.29 263	91.79 134	84.55 302	68.85 213	68.99 192	80.70 253	56.16 148	92.04 247	62.67 218	60.98 288	81.11 307

v18		71.94 242	69.43 245	79.50 235	80.74 259	66.82 100	88.16 229	86.66 275	68.95 212	55.55 289	72.66 307	55.03 165	90.15 280	64.78 195	52.30 317	81.54 295

test_normal		79.66 129	77.36 150	86.54 53	80.72 260	69.21 42	90.68 178	92.16 131	76.99 70	58.63 277	82.03 234	46.70 245	95.86 114	81.74 65	86.63 97	94.56 73

CP-MVSNet		70.50 259	69.91 242	72.26 309	80.71 261	51.00 317	87.23 253	90.30 193	67.84 228	59.64 268	82.69 220	50.23 216	82.30 334	51.28 263	59.28 293	83.46 275

v1neww		77.39 170	75.71 172	82.44 156	80.69 262	66.83 98	91.94 126	90.18 198	74.19 112	69.60 180	82.51 221	54.99 167	94.44 162	71.68 133	65.60 249	86.05 239

v7new		77.39 170	75.71 172	82.44 156	80.69 262	66.83 98	91.94 126	90.18 198	74.19 112	69.60 180	82.51 221	54.99 167	94.44 162	71.68 133	65.60 249	86.05 239

v8		75.35 206	73.26 217	81.61 190	80.67 264	66.82 100	89.54 205	89.27 229	71.65 173	63.30 253	80.30 261	54.99 167	94.06 188	67.33 172	62.33 276	83.94 268

v6		77.39 170	75.71 172	82.44 156	80.67 264	66.82 100	91.94 126	90.18 198	74.19 112	69.60 180	82.50 224	55.00 166	94.44 162	71.68 133	65.60 249	86.05 239

v16		71.81 243	69.26 247	79.47 236	80.66 266	66.81 104	87.93 233	86.63 277	68.70 218	55.35 291	72.51 308	54.75 171	90.12 282	64.51 197	52.28 318	81.47 296

PS-MVSNAJss		77.26 177	76.31 163	80.13 218	80.64 267	59.16 264	90.63 181	91.06 169	72.80 142	68.58 199	84.57 206	53.55 187	93.96 195	72.97 119	71.96 207	87.27 219

v1141		77.28 175	75.57 176	82.42 162	80.63 268	66.73 108	91.96 122	90.42 186	74.41 104	69.46 183	82.12 231	55.09 163	94.40 167	70.99 140	65.05 256	86.12 236

v17		71.77 245	69.20 248	79.46 237	80.62 269	66.81 104	87.93 233	86.63 277	68.71 217	55.25 292	72.49 309	54.72 172	90.11 283	64.50 198	51.97 319	81.47 296

divwei89l23v2f112		77.28 175	75.57 176	82.42 162	80.62 269	66.72 110	91.96 122	90.42 186	74.41 104	69.46 183	82.12 231	55.11 162	94.40 167	71.00 138	65.04 257	86.12 236

TransMVSNet (Re)		70.07 261	67.66 262	77.31 277	80.62 269	59.13 265	91.78 136	84.94 300	65.97 242	60.08 267	80.44 258	50.78 210	91.87 249	48.84 272	45.46 337	80.94 309

v1		77.29 174	75.57 176	82.42 162	80.61 272	66.73 108	91.96 122	90.42 186	74.41 104	69.46 183	82.12 231	55.14 161	94.40 167	71.00 138	65.04 257	86.13 235

v15		71.40 247	68.75 250	79.35 238	80.39 273	66.70 112	87.57 248	86.64 276	68.66 219	54.68 294	72.00 316	54.50 174	89.98 285	63.69 204	50.66 324	81.38 300

v2v482		77.42 169	75.65 175	82.73 148	80.38 274	67.13 90	91.85 132	90.23 195	75.09 98	69.37 186	83.39 215	53.79 185	94.44 162	71.77 131	65.00 260	86.63 230

v7		76.83 187	75.01 187	82.29 169	80.35 275	66.70 112	91.68 141	89.97 208	73.47 133	69.22 188	82.22 228	52.52 198	94.43 166	69.73 150	65.96 248	85.74 251

PS-CasMVS		69.86 263	69.13 249	72.07 312	80.35 275	50.57 319	87.02 256	89.75 213	67.27 235	59.19 271	82.28 226	46.58 247	82.24 335	50.69 265	59.02 296	83.39 277

v11		71.05 253	68.32 257	79.23 242	80.34 277	66.57 119	87.01 257	86.55 281	68.11 226	54.40 297	71.66 321	52.94 195	89.91 288	62.71 217	51.12 322	81.21 304

V14		71.29 249	68.61 252	79.31 239	80.34 277	66.65 114	87.39 251	86.61 279	68.41 224	54.49 296	71.91 317	54.25 179	89.96 286	63.50 205	50.62 325	81.33 302

v10		74.77 221	72.54 225	81.46 191	80.33 279	66.71 111	89.15 212	89.08 238	70.94 184	63.08 254	79.86 266	52.52 198	94.04 191	65.70 189	62.17 277	83.64 270

V9		71.16 250	68.46 254	79.27 241	80.26 280	66.60 116	87.21 254	86.56 280	68.17 225	54.26 299	71.81 319	54.00 181	89.93 287	63.28 208	50.57 326	81.27 303

test0.0.03 1		72.76 237	72.71 222	72.88 304	80.25 281	47.99 328	91.22 160	89.45 223	71.51 179	62.51 260	87.66 168	53.83 183	85.06 317	50.16 267	67.84 240	85.58 252

v1144		76.73 189	74.88 188	82.27 170	80.23 282	66.60 116	91.68 141	90.21 197	73.69 126	69.06 191	81.89 236	52.73 197	94.40 167	69.21 157	65.23 253	85.80 247

v12		71.02 254	68.29 259	79.22 243	80.18 283	66.53 121	87.01 257	86.54 282	67.90 227	54.00 302	71.70 320	53.66 186	89.91 288	63.09 210	50.51 327	81.21 304

v13		70.90 255	68.15 260	79.15 247	80.08 284	66.45 123	86.83 262	86.50 283	67.62 233	53.78 304	71.61 322	53.51 190	89.87 290	62.89 215	50.50 328	81.14 306

LP		56.71 316	51.64 320	71.91 314	80.08 284	60.33 245	61.72 347	75.61 337	43.87 345	43.76 339	60.30 343	30.46 325	84.05 320	22.94 352	46.06 336	71.34 342

v148		76.19 194	74.47 194	81.36 192	80.05 286	64.44 169	91.75 139	90.23 195	73.68 127	67.13 220	80.84 252	55.92 154	93.86 201	68.95 160	61.73 282	85.76 250

v1192		75.98 199	73.92 203	82.15 176	79.73 287	66.24 130	91.22 160	89.75 213	72.67 143	68.49 204	81.42 242	49.86 219	94.27 175	67.08 173	65.02 259	85.95 244

AllTest		61.66 305	58.06 306	72.46 307	79.57 288	51.42 315	80.17 307	68.61 351	51.25 324	45.88 329	81.23 245	19.86 345	86.58 313	38.98 311	57.01 303	79.39 323

TestCases				72.46 307	79.57 288	51.42 315		68.61 351	51.25 324	45.88 329	81.23 245	19.86 345	86.58 313	38.98 311	57.01 303	79.39 323

MDA-MVSNet-bldmvs		61.54 307	57.70 308	73.05 302	79.53 290	57.00 285	83.08 286	81.23 321	57.57 302	34.91 349	72.45 311	32.79 313	86.26 315	35.81 324	41.95 341	75.89 336

v144192		76.05 197	74.03 200	82.12 178	79.50 291	66.55 120	91.39 150	89.71 219	72.30 150	68.17 206	81.33 244	51.75 205	94.03 192	67.94 165	64.19 266	85.77 248

v1921920		75.63 204	73.49 214	82.06 182	79.38 292	66.35 126	91.07 168	89.48 222	71.98 161	67.99 207	81.22 247	49.16 227	93.90 198	66.56 178	64.56 265	85.92 246

PEN-MVS		69.46 268	68.56 253	72.17 311	79.27 293	49.71 323	86.90 260	89.24 231	67.24 236	59.08 272	82.51 221	47.23 242	83.54 326	48.42 274	57.12 301	83.25 278

v1240		75.21 210	72.98 219	81.88 184	79.20 294	66.00 135	90.75 174	89.11 237	71.63 174	67.41 217	81.22 247	47.36 241	93.87 199	65.46 191	64.72 263	85.77 248

pmmvs4		73.92 228	71.81 231	80.25 215	79.17 295	65.24 149	87.43 250	87.26 272	67.64 232	63.46 251	83.91 210	48.96 229	91.53 265	62.94 213	65.49 252	83.96 267

V42		76.46 191	74.55 192	82.19 175	79.14 296	67.82 71	90.26 188	89.42 225	73.75 125	68.63 198	81.89 236	51.31 209	94.09 185	71.69 132	64.84 261	84.66 263

testpf		57.17 314	56.93 311	57.88 335	79.13 297	42.40 338	34.23 359	85.97 292	52.64 319	47.66 327	66.50 331	36.33 304	79.65 342	53.60 257	56.31 306	51.60 353

pm-mvs1		72.89 235	71.09 236	78.26 263	79.10 298	57.62 278	90.80 172	89.30 228	67.66 230	62.91 256	81.78 238	49.11 228	92.95 217	60.29 231	58.89 298	84.22 266

our_test_3		68.29 275	64.69 279	79.11 248	78.92 299	64.85 161	88.40 226	85.06 298	60.32 290	52.68 309	76.12 293	40.81 275	89.80 293	44.25 291	55.65 307	82.67 289

ppachtmachnet_test		67.72 279	63.70 286	79.77 228	78.92 299	66.04 134	88.68 219	82.90 318	60.11 292	55.45 290	75.96 296	39.19 279	90.55 271	39.53 309	52.55 316	82.71 287

TinyColmap		60.32 308	56.42 314	72.00 313	78.78 301	53.18 307	78.36 319	75.64 336	52.30 320	41.59 344	75.82 298	14.76 351	88.35 303	35.84 323	54.71 312	74.46 338

SixPastTwentyTwo		64.92 293	61.78 299	74.34 295	78.74 302	49.76 322	83.42 282	79.51 329	62.86 272	50.27 319	77.35 282	30.92 324	90.49 273	45.89 283	47.06 334	82.78 283

EG-PatchMatch MVS		68.55 272	65.41 274	77.96 268	78.69 303	62.93 204	89.86 200	89.17 233	60.55 287	50.27 319	77.73 281	22.60 341	94.06 188	47.18 279	72.65 202	76.88 334

pmmvs5		73.35 231	71.52 233	78.86 252	78.64 304	60.61 242	91.08 167	86.90 273	67.69 229	63.32 252	83.64 211	44.33 261	90.53 272	62.04 222	66.02 247	85.46 255

XVG-OURS		74.25 225	72.46 226	79.63 230	78.45 305	57.59 279	80.33 304	87.39 267	63.86 265	68.76 196	89.62 144	40.50 276	91.72 252	69.00 159	74.25 188	89.58 175

XVG-OURS-SEG-HR		74.70 222	73.08 218	79.57 232	78.25 306	57.33 282	80.49 302	87.32 270	63.22 269	68.76 196	90.12 133	44.89 259	91.59 260	70.55 146	74.09 190	89.79 172

MDA-MVSNet_test_wron		63.78 301	60.16 302	74.64 291	78.15 307	60.41 243	83.49 279	84.03 305	56.17 313	39.17 346	71.59 324	37.22 296	83.24 330	42.87 296	48.73 331	80.26 317

YYNet1		63.76 302	60.14 303	74.62 292	78.06 308	60.19 249	83.46 281	83.99 309	56.18 312	39.25 345	71.56 325	37.18 297	83.34 328	42.90 295	48.70 332	80.32 316

DTE-MVSNet		68.46 274	67.33 264	71.87 315	77.94 309	49.00 326	86.16 267	88.58 252	66.36 240	58.19 278	82.21 229	46.36 248	83.87 324	44.97 289	55.17 309	82.73 285

USDC		67.43 284	64.51 281	76.19 284	77.94 309	55.29 298	78.38 318	85.00 299	73.17 135	48.36 324	80.37 259	21.23 343	92.48 235	52.15 261	64.02 269	80.81 311

jajsoiax		73.05 233	71.51 234	77.67 270	77.46 311	54.83 300	88.81 217	90.04 206	69.13 210	62.85 257	83.51 213	31.16 322	92.75 226	70.83 142	69.80 222	85.43 256

mvs_tets		72.71 238	71.11 235	77.52 271	77.41 312	54.52 302	88.45 225	89.76 212	68.76 216	62.70 258	83.26 216	29.49 326	92.71 227	70.51 147	69.62 224	85.34 258

N_pmnet		50.55 322	49.11 325	54.88 339	77.17 313	4.02 369	84.36 273	2.00 370	48.59 330	45.86 331	68.82 329	32.22 316	82.80 331	31.58 343	51.38 321	77.81 332

test_djsdf		73.76 230	72.56 224	77.39 275	77.00 314	53.93 304	89.07 214	90.69 178	65.80 244	63.92 246	82.03 234	43.14 265	92.67 229	72.83 121	68.53 233	85.57 253

OpenMVS_ROB	61.12 18	66.39 287	62.92 292	76.80 281	76.51 315	57.77 275	89.22 209	83.41 312	55.48 314	53.86 303	77.84 280	26.28 336	93.95 196	34.90 333	68.76 231	78.68 328

v7n		71.31 248	68.65 251	79.28 240	76.40 316	60.77 236	86.71 263	89.45 223	64.17 262	58.77 276	78.24 277	44.59 260	93.54 206	57.76 242	61.75 281	83.52 273

K. test v3		63.09 303	59.61 305	73.53 299	76.26 317	49.38 325	83.27 283	77.15 332	64.35 261	47.77 325	72.32 314	28.73 328	87.79 308	49.93 269	36.69 347	83.41 276

RPSCF		64.24 297	61.98 298	71.01 316	76.10 318	45.00 334	75.83 325	75.94 335	46.94 335	58.96 274	84.59 205	31.40 321	82.00 336	47.76 277	60.33 292	86.04 242

OurMVSNet-221017-0		64.68 294	62.17 297	72.21 310	76.08 319	47.35 331	80.67 301	81.02 323	56.19 311	51.60 313	79.66 269	27.05 334	88.56 301	53.60 257	53.63 314	80.71 312

Test4		76.45 192	73.45 215	85.45 90	76.07 320	67.61 77	88.38 227	90.83 174	76.71 75	53.06 307	79.65 270	31.61 319	94.35 171	78.47 88	86.22 103	94.40 82

v748		70.55 258	67.97 261	78.27 262	75.75 321	58.78 268	86.29 266	89.25 230	65.12 257	56.66 287	77.17 287	45.05 258	92.95 217	58.13 241	58.33 300	83.10 282

Anonymous20231206		67.53 282	65.78 270	72.79 305	74.95 322	47.59 330	88.23 228	87.32 270	61.75 283	58.07 279	77.29 284	37.79 292	87.29 310	42.91 294	63.71 271	83.48 274

ITE_SJBPF				70.43 317	74.44 323	47.06 332		77.32 331	60.16 291	54.04 301	83.53 212	23.30 340	84.01 322	43.07 293	61.58 285	80.21 318

EU-MVSNet		64.01 299	63.01 291	67.02 325	74.40 324	38.86 348	83.27 283	86.19 287	45.11 340	54.27 298	81.15 250	36.91 301	80.01 340	48.79 273	57.02 302	82.19 292

XVG-ACMP-BASELINE		68.04 277	65.53 273	75.56 287	74.06 325	52.37 309	78.43 317	85.88 293	62.03 278	58.91 275	81.21 249	20.38 344	91.15 269	60.69 229	68.18 235	83.16 280

anonymousdsp		71.14 251	69.37 246	76.45 282	72.95 326	54.71 301	84.19 274	88.88 245	61.92 280	62.15 261	79.77 267	38.14 287	91.44 268	68.90 161	67.45 241	83.21 279

lessismore_v0				73.72 298	72.93 327	47.83 329		61.72 359		45.86 331	73.76 303	28.63 330	89.81 291	47.75 278	31.37 351	83.53 272

pmmvs6		67.57 281	64.76 278	76.00 286	72.82 328	53.37 306	88.71 218	86.78 274	53.19 318	57.58 284	78.03 279	35.33 307	92.41 236	55.56 249	54.88 311	82.21 291

V4		69.80 264	67.02 266	78.15 265	71.86 329	60.10 250	82.02 291	87.39 267	64.48 259	57.78 282	75.98 294	41.49 270	92.90 222	63.00 211	59.16 294	81.44 299

v52		69.80 264	67.01 267	78.15 265	71.84 330	60.10 250	82.02 291	87.39 267	64.48 259	57.80 281	75.97 295	41.47 271	92.90 222	63.00 211	59.13 295	81.45 298

testgi		64.48 296	62.87 293	69.31 319	71.24 331	40.62 343	85.49 268	79.92 327	65.36 248	54.18 300	83.49 214	23.74 339	84.55 318	41.60 301	60.79 290	82.77 284

Patchmatch-RL test		68.17 276	64.49 282	79.19 244	71.22 332	53.93 304	70.07 334	71.54 348	69.22 207	56.79 286	62.89 339	56.58 145	88.61 299	69.53 154	52.61 315	95.03 60

Gipuma		34.91 333	31.44 335	45.30 344	70.99 333	39.64 347	19.85 362	72.56 345	20.10 358	16.16 359	21.47 361	5.08 364	71.16 352	13.07 358	43.70 340	25.08 359
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
UnsupCasMVSNet_eth		65.79 291	63.10 290	73.88 296	70.71 334	50.29 321	81.09 299	89.88 210	72.58 145	49.25 322	74.77 302	32.57 315	87.43 309	55.96 248	41.04 343	83.90 269

CMPMVS	48.56 21	66.77 286	64.41 283	73.84 297	70.65 335	50.31 320	77.79 322	85.73 295	45.54 339	44.76 335	82.14 230	35.40 306	90.14 281	63.18 209	74.54 186	81.07 308
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
test20.03		63.83 300	62.65 294	67.38 324	70.58 336	39.94 344	86.57 264	84.17 304	63.29 268	51.86 312	77.30 283	37.09 299	82.47 332	38.87 317	54.13 313	79.73 321

testing_2		71.09 252	67.32 265	82.40 166	69.82 337	66.52 122	83.64 277	90.77 176	72.21 155	45.12 334	71.07 326	27.60 332	93.74 202	75.71 105	69.96 221	86.95 223

MIMVSNet1		60.16 310	57.33 310	68.67 320	69.71 338	44.13 336	78.92 315	84.21 303	55.05 315	44.63 336	71.85 318	23.91 338	81.54 338	32.63 340	55.03 310	80.35 315

pmmvs-eth3d		65.53 292	62.32 296	75.19 288	69.39 339	59.59 257	82.80 288	83.43 311	62.52 275	51.30 316	72.49 309	32.86 312	87.16 311	55.32 250	50.73 323	78.83 327

test2356		64.16 298	63.28 289	66.81 326	69.37 340	39.86 346	87.76 238	86.02 290	59.83 294	53.54 306	73.23 305	34.94 308	80.67 339	39.66 308	65.20 254	79.89 319

UnsupCasMVSNet_bld		61.60 306	57.71 307	73.29 301	68.73 341	51.64 312	78.61 316	89.05 240	57.20 306	46.11 328	61.96 341	28.70 329	88.60 300	50.08 268	38.90 345	79.63 322

testus		59.36 312	57.51 309	64.90 328	66.72 342	37.56 349	84.98 270	81.09 322	57.46 305	47.72 326	72.76 306	11.43 355	78.78 346	36.56 320	58.91 297	78.36 331

new-patchmatchnet		59.30 313	56.48 313	67.79 322	65.86 343	44.19 335	82.47 289	81.77 319	59.94 293	43.65 340	66.20 333	27.67 331	81.68 337	39.34 310	41.40 342	77.50 333

PM-MVS		59.40 311	56.59 312	67.84 321	63.63 344	41.86 340	76.76 323	63.22 357	59.01 298	51.07 317	72.27 315	11.72 353	83.25 329	61.34 225	50.28 329	78.39 330

DSMNet-mixed		56.78 315	54.44 317	63.79 330	63.21 345	29.44 357	64.43 345	64.10 356	42.12 348	51.32 315	71.60 323	31.76 318	75.04 349	36.23 322	65.20 254	86.87 225

new_pmnet		49.31 323	46.44 326	57.93 334	62.84 346	40.74 342	68.47 338	62.96 358	36.48 350	35.09 348	57.81 345	14.97 350	72.18 350	32.86 339	46.44 335	60.88 351

LF4IMVS		54.01 321	52.12 319	59.69 333	62.41 347	39.91 345	68.59 337	68.28 353	42.96 346	44.55 337	75.18 299	14.09 352	68.39 353	41.36 303	51.68 320	70.78 343

1111		56.66 317	54.98 316	61.69 331	61.99 348	31.38 353	79.81 312	83.17 315	45.66 337	41.94 342	65.44 334	41.50 268	79.56 343	27.64 346	47.68 333	74.14 339

.test1245		46.52 326	49.68 323	37.02 348	61.99 348	31.38 353	79.81 312	83.17 315	45.66 337	41.94 342	65.44 334	41.50 268	79.56 343	27.64 346	0.01 364	0.13 365

ambc				69.61 318	61.38 350	41.35 341	49.07 356	85.86 294		50.18 321	66.40 332	10.16 356	88.14 305	45.73 284	44.20 338	79.32 325

test1235678		55.73 318	52.74 318	64.68 329	60.16 351	35.56 351	81.65 295	81.46 320	51.27 323	38.93 347	62.82 340	17.44 347	78.58 347	30.87 344	50.09 330	79.89 319

TDRefinement		55.28 320	51.58 321	66.39 327	59.53 352	46.15 333	76.23 324	72.80 344	44.60 342	42.49 341	76.28 292	15.29 349	82.39 333	33.20 337	43.75 339	70.62 344

pmmvs3		55.51 319	51.50 322	67.53 323	57.90 353	50.93 318	80.37 303	73.66 343	40.63 349	44.15 338	64.75 338	16.30 348	78.97 345	44.77 290	40.98 344	72.69 340

test12356		47.51 324	44.82 327	55.56 337	52.53 354	21.09 364	71.45 331	76.03 334	44.14 344	30.69 350	58.18 344	9.01 359	76.14 348	26.95 348	34.43 350	69.46 346

DeepMVS_CX				34.71 349	51.45 355	24.73 363		28.48 369	31.46 352	17.49 358	52.75 347	5.80 363	42.60 364	18.18 356	19.42 353	36.81 357

FPMVS		45.64 327	43.10 329	53.23 341	51.42 356	36.46 350	64.97 344	71.91 346	29.13 353	27.53 352	61.55 342	9.83 357	65.01 357	16.00 357	55.58 308	58.22 352

PNet_i23d		32.77 334	29.98 336	41.11 346	48.05 357	29.17 358	65.82 343	50.02 362	21.42 356	14.74 360	37.19 357	1.11 369	55.11 360	19.75 355	11.77 357	39.06 355

wuyk23d		11.30 343	10.95 344	12.33 354	48.05 357	19.89 365	25.89 361	1.92 371	3.58 363	3.12 366	1.37 366	0.64 370	15.77 366	6.23 363	7.77 363	1.35 363

testmv		46.98 325	43.53 328	57.35 336	47.75 359	30.41 356	74.99 327	77.69 330	42.84 347	28.03 351	53.36 346	8.18 360	71.18 351	24.36 350	34.55 348	70.46 345

PMMVS2		37.93 331	33.61 333	50.92 342	46.31 360	24.76 362	60.55 351	50.05 361	28.94 354	20.93 354	47.59 348	4.41 366	65.13 356	25.14 349	18.55 354	62.87 349

no-one		44.13 328	38.39 330	61.34 332	45.91 361	41.94 339	61.67 348	75.07 341	45.05 341	20.07 355	40.68 356	11.58 354	79.82 341	30.18 345	15.30 355	62.26 350

E-PMN		24.61 338	24.00 339	26.45 351	43.74 362	18.44 366	60.86 349	39.66 364	15.11 359	9.53 363	22.10 360	6.52 362	46.94 362	8.31 361	10.14 358	13.98 361

EMVS		23.76 340	23.20 341	25.46 352	41.52 363	16.90 367	60.56 350	38.79 367	14.62 360	8.99 364	20.24 364	7.35 361	45.82 363	7.25 362	9.46 360	13.64 362

LCM-MVSNet		40.54 329	35.79 331	54.76 340	36.92 364	30.81 355	51.41 354	69.02 350	22.07 355	24.63 353	45.37 351	4.56 365	65.81 355	33.67 335	34.50 349	67.67 347

ANet_high		40.27 330	35.20 332	55.47 338	34.74 365	34.47 352	63.84 346	71.56 347	48.42 331	18.80 357	41.08 354	9.52 358	64.45 358	20.18 354	8.66 362	67.49 348

MVE	24.84 23	24.35 339	19.77 343	38.09 347	34.56 366	26.92 361	26.57 360	38.87 366	11.73 362	11.37 362	27.44 358	1.37 368	50.42 361	11.41 359	14.60 356	36.93 356
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
wuykxyi23d		29.03 337	23.09 342	46.84 343	31.67 367	28.82 359	43.46 357	57.72 360	14.39 361	7.52 365	20.84 362	0.64 370	60.29 359	21.57 353	10.04 359	51.40 354

PMVS	26.43 22	31.84 335	28.16 337	42.89 345	25.87 368	27.58 360	50.92 355	49.78 363	21.37 357	14.17 361	40.81 355	2.01 367	66.62 354	9.61 360	38.88 346	34.49 358
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
tmp_tt		22.26 341	23.75 340	17.80 353	5.23 369	12.06 368	35.26 358	39.48 365	2.82 364	18.94 356	44.20 352	22.23 342	24.64 365	36.30 321	9.31 361	16.69 360

testmvs		7.23 345	9.62 346	0.06 356	0.04 370	0.02 371	84.98 270	0.02 372	0.03 365	0.18 367	1.21 367	0.01 373	0.02 367	0.14 364	0.01 364	0.13 365

test123		6.92 346	9.21 347	0.08 355	0.03 371	0.05 370	81.65 295	0.01 373	0.02 366	0.14 368	0.85 368	0.03 372	0.02 367	0.12 365	0.00 366	0.16 364

cdsmvs_eth3d_5k		19.86 342	26.47 338	0.00 357	0.00 372	0.00 372	0.00 363	93.45 68	0.00 367	0.00 369	95.27 33	49.56 221	0.00 369	0.00 366	0.00 366	0.00 367

pcd_1.5k_mvsjas		4.46 347	5.95 348	0.00 357	0.00 372	0.00 372	0.00 363	0.00 374	0.00 367	0.00 369	0.00 369	53.55 187	0.00 369	0.00 366	0.00 366	0.00 367

sosnet-low-res		0.00 348	0.00 349	0.00 357	0.00 372	0.00 372	0.00 363	0.00 374	0.00 367	0.00 369	0.00 369	0.00 374	0.00 369	0.00 366	0.00 366	0.00 367

sosnet		0.00 348	0.00 349	0.00 357	0.00 372	0.00 372	0.00 363	0.00 374	0.00 367	0.00 369	0.00 369	0.00 374	0.00 369	0.00 366	0.00 366	0.00 367

uncertanet		0.00 348	0.00 349	0.00 357	0.00 372	0.00 372	0.00 363	0.00 374	0.00 367	0.00 369	0.00 369	0.00 374	0.00 369	0.00 366	0.00 366	0.00 367

Regformer		0.00 348	0.00 349	0.00 357	0.00 372	0.00 372	0.00 363	0.00 374	0.00 367	0.00 369	0.00 369	0.00 374	0.00 369	0.00 366	0.00 366	0.00 367

ab-mvs-re		7.91 344	10.55 345	0.00 357	0.00 372	0.00 372	0.00 363	0.00 374	0.00 367	0.00 369	94.95 43	0.00 374	0.00 369	0.00 366	0.00 366	0.00 367

uanet		0.00 348	0.00 349	0.00 357	0.00 372	0.00 372	0.00 363	0.00 374	0.00 367	0.00 369	0.00 369	0.00 374	0.00 369	0.00 366	0.00 366	0.00 367

GSMVS																94.68 69

test_part1				0.00 357		0.00 372	0.00 363	94.26 45				0.00 374	0.00 369	0.00 366	0.00 366	0.00 367

sam_mvs1												57.85 125				94.68 69

sam_mvs												54.91 170

MTGPA								92.23 122

test_post1							78.95 314				20.70 363	53.05 193	91.50 266	60.43 230

test_post											23.01 359	56.49 146	92.67 229

patchmatchnet-post											67.62 330	57.62 128	90.25 275

MTMP							93.77 63	32.52 368

test9_res														89.41 11	94.96 9	95.29 45

agg_prior2														86.41 34	94.75 18	95.33 42

test_prior4						67.18 89	93.92 56

test_prior2							95.10 29		75.40 93	85.25 35	95.61 24	67.94 27		87.47 25	94.77 15

旧先验2							92.00 120		59.37 297	87.54 19			93.47 209	75.39 107

新几何2							91.41 148

无先验							92.71 93	92.61 112	62.03 278				97.01 71	66.63 176		93.97 100

原ACMM2							92.01 118

testdata2													96.09 106	61.26 226

segment_acmp												65.94 46

testdata1							89.21 210		77.55 63

plane_prior5								91.31 160					95.55 130	76.74 99	78.53 154	88.39 189

plane_prior4											89.14 146

plane_prior3						61.95 223			79.09 44	72.53 145

plane_prior2							93.13 80		78.81 49

plane_prior						62.42 213	93.85 59		79.38 37						78.80 152

n2								0.00 374

nn								0.00 374

door-mid								66.01 355

test11								93.01 96

door								66.57 354

HQP5-MVS						63.66 191

BP-MVS														77.63 95

HQP4-MVS										74.18 126			95.61 126			88.63 184

HQP3-MVS								91.70 146							78.90 150

HQP2-MVS												51.63 207

MDTV_nov1_ep13_2view						59.90 254	80.13 308		67.65 231	72.79 140		54.33 178		59.83 233		92.58 136

ACMMP++_ref															71.63 208

ACMMP++															69.72 223

Test By Simon												54.21 180

High-resolution multi-view benchmark