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.

xxxxxxxxxxxxxcwj		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

SF-MVS		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

ETH3D cwj APD-0.16		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

ETH3 D test6400		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

ETH3D-3000-0.1		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

train_agg		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

agg_prior1		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

HFP-MVS		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

region2R		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

#test#		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

test_prior3		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

1314		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

1121		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

MVS		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

abl_6		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

QAPM		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

hse-mvs3		0.30 17	0.30 18	0.30 22	0.30 29	0.30 29	0.30 29	0.30 30	0.30 29	0.30 28	0.30 26	0.30 28	0.30 29	0.30 27	0.30 27	0.30 27

hse-mvs2		0.30 17	0.30 18	0.30 22	0.30 29	0.30 29	0.30 29	0.30 30	0.30 29	0.30 28	0.30 26	0.30 28	0.30 29	0.30 27	0.30 27	0.30 27

CL-MVSNet_2432*1600		0.30 17	0.30 18	0.30 22	0.30 29	0.30 29	0.30 29	0.30 30	0.30 29	0.30 28	0.30 26	0.30 28	0.30 29	0.30 27	0.30 27	0.30 27

AUN-MVS		0.30 17	0.30 18	0.30 22	0.30 29	0.30 29	0.30 29	0.30 30	0.30 29	0.30 28	0.30 26	0.30 28	0.30 29	0.30 27	0.30 27	0.30 27

LCM-MVSNet		0.37 21	0.36 22	0.37 26	0.37 33	0.37 33	0.37 33	0.32 34	0.37 33	0.37 32	0.37 30	0.37 32	0.37 33	0.37 31	0.37 31	0.37 31

v144192		0.40 22	0.40 23	0.40 27	0.40 34	0.40 34	0.40 34	0.40 36	0.40 34	0.40 33	0.40 31	0.40 33	0.40 34	0.40 32	0.40 32	0.40 32

v1921920		0.40 22	0.40 23	0.40 27	0.40 34	0.40 34	0.40 34	0.40 36	0.40 34	0.40 33	0.40 31	0.40 33	0.40 34	0.40 32	0.40 32	0.40 32

v1192		0.40 22	0.40 23	0.40 27	0.40 34	0.40 34	0.40 34	0.40 36	0.40 34	0.40 33	0.40 31	0.40 33	0.40 34	0.40 32	0.40 32	0.40 32

v1144		0.40 22	0.40 23	0.40 27	0.40 34	0.40 34	0.40 34	0.40 36	0.40 34	0.40 33	0.40 31	0.40 33	0.40 34	0.40 32	0.40 32	0.40 32

v148		0.40 22	0.40 23	0.40 27	0.40 34	0.40 34	0.40 34	0.40 36	0.40 34	0.40 33	0.40 31	0.40 33	0.40 34	0.40 32	0.40 32	0.40 32

v7n		0.40 22	0.40 23	0.40 27	0.40 34	0.40 34	0.40 34	0.40 36	0.40 34	0.40 33	0.40 31	0.40 33	0.40 34	0.40 32	0.40 32	0.40 32

v1240		0.40 22	0.40 23	0.40 27	0.40 34	0.40 34	0.40 34	0.40 36	0.40 34	0.40 33	0.40 31	0.40 33	0.40 34	0.40 32	0.40 32	0.40 32

v8		0.40 22	0.40 23	0.40 27	0.40 34	0.40 34	0.40 34	0.40 36	0.40 34	0.40 33	0.40 31	0.40 33	0.40 34	0.40 32	0.40 32	0.40 32

v10		0.40 22	0.40 23	0.40 27	0.40 34	0.40 34	0.40 34	0.40 36	0.40 34	0.40 33	0.40 31	0.40 33	0.40 34	0.40 32	0.40 32	0.40 32

v2v482		0.40 22	0.40 23	0.40 27	0.40 34	0.40 34	0.40 34	0.40 36	0.40 34	0.40 33	0.40 31	0.40 33	0.40 34	0.40 32	0.40 32	0.40 32

V42		0.40 22	0.40 23	0.40 27	0.40 34	0.40 34	0.40 34	0.40 36	0.40 34	0.40 33	0.40 31	0.40 33	0.40 34	0.40 32	0.40 32	0.40 32

GA-MVS		0.40 22	0.40 23	0.40 27	0.40 34	0.40 34	0.40 34	0.40 36	0.40 34	0.40 33	0.40 31	0.40 33	0.40 34	0.40 32	0.40 32	0.40 32

Fast-Effi-MVS+		0.41 34	0.40 23	0.41 39	0.41 46	0.41 46	0.41 46	0.35 35	0.41 46	0.41 45	0.41 43	0.41 45	0.41 46	0.41 44	0.41 44	0.41 44

Fast-Effi-MVS+-dtu		0.44 35	0.44 36	0.44 40	0.44 47	0.44 47	0.44 47	0.44 48	0.44 47	0.44 46	0.44 44	0.44 46	0.44 47	0.44 45	0.44 45	0.44 45

Effi-MVS+		0.58 36	0.56 37	0.62 43	0.53 48	0.62 50	0.53 48	0.53 49	0.53 48	0.62 49	0.62 47	0.53 47	0.62 50	0.62 47	0.53 46	0.62 48

Effi-MVS+-dtu		0.59 37	0.61 39	0.53 41	0.68 55	0.53 48	0.53 48	0.68 56	0.68 55	0.53 47	0.53 45	0.68 54	0.53 48	0.68 53	0.53 46	0.53 46

DIV-MVS_2432*1600		0.60 38	0.60 38	0.60 42	0.60 49	0.60 49	0.60 50	0.60 50	0.60 49	0.60 48	0.60 46	0.60 48	0.60 49	0.60 46	0.60 48	0.60 47

EIA-MVS		0.62 39	0.62 40	0.62 43	0.62 50	0.62 50	0.62 51	0.62 51	0.62 50	0.62 49	0.62 47	0.62 49	0.62 50	0.62 47	0.62 49	0.62 48

ETV-MVS		0.62 39	0.62 40	0.62 43	0.62 50	0.62 50	0.62 51	0.62 51	0.62 50	0.62 49	0.62 47	0.62 49	0.62 50	0.62 47	0.62 49	0.62 48

CS-MVS		0.62 39	0.62 40	0.62 43	0.62 50	0.62 50	0.62 51	0.62 51	0.62 50	0.62 49	0.62 47	0.62 49	0.62 50	0.62 47	0.62 49	0.62 48

CS-MVS-test		0.62 39	0.62 40	0.62 43	0.62 50	0.62 50	0.62 51	0.62 51	0.62 50	0.62 49	0.62 47	0.62 49	0.62 50	0.62 47	0.62 49	0.62 48

DROMVSNet		0.62 39	0.62 40	0.62 43	0.62 50	0.62 50	0.62 51	0.62 51	0.62 50	0.62 49	0.62 47	0.62 49	0.62 50	0.62 47	0.62 49	0.62 48

mvs-test1		0.68 44	0.68 45	0.68 49	0.68 55	0.68 56	0.68 56	0.68 56	0.68 55	0.68 55	0.68 53	0.68 54	0.68 56	0.68 53	0.68 54	0.68 54

CDS-MVSNet		0.88 45	0.88 46	0.88 50	0.88 57	0.88 57	0.88 57	0.88 58	0.88 57	0.88 56	0.88 54	0.88 56	0.88 57	0.88 55	0.88 55	0.88 55
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
TAMVS		0.88 45	0.88 46	0.88 50	0.88 57	0.88 57	0.88 57	0.88 58	0.88 57	0.88 56	0.88 54	0.88 56	0.88 57	0.88 55	0.88 55	0.88 55

LCM-MVSNet-Re		0.89 47	0.89 48	0.89 52	0.89 59	0.89 59	0.89 59	0.89 60	0.89 59	0.89 58	0.89 56	0.89 58	0.89 59	0.89 57	0.89 57	0.89 57

MDA-MVSNet-bldmvs		1.20 48	1.20 49	1.20 54	1.20 61	1.20 62	1.20 60	1.20 63	1.20 61	1.20 60	1.20 58	1.20 60	1.20 61	1.20 59	1.20 59	1.20 59

YYNet1		1.20 48	1.20 49	1.20 54	1.20 61	1.20 62	1.20 60	1.20 63	1.20 61	1.20 60	1.20 58	1.20 60	1.20 61	1.20 59	1.20 59	1.20 59

MDA-MVSNet_test_wron		1.20 48	1.20 49	1.20 54	1.20 61	1.20 62	1.20 60	1.20 63	1.20 61	1.20 60	1.20 58	1.20 60	1.20 61	1.20 59	1.20 59	1.20 59

KD-MVS_2432*1600		1.30 51	1.30 52	1.30 57	1.30 64	1.30 65	1.30 63	1.30 66	1.30 64	1.30 63	1.30 61	1.30 63	1.30 64	1.30 62	1.30 62	1.30 62

miper_refine_blended		1.30 51	1.30 52	1.30 57	1.30 64	1.30 65	1.30 63	1.30 66	1.30 64	1.30 63	1.30 61	1.30 63	1.30 64	1.30 62	1.30 62	1.30 62

EI-MVSNet-UG-set		1.42 53	1.42 54	1.42 59	1.42 66	1.42 67	1.42 65	1.42 68	1.42 66	1.42 65	1.42 63	1.42 65	1.42 66	1.42 64	1.42 64	1.42 64

EI-MVSNet-Vis-set		1.42 53	1.42 54	1.42 59	1.42 66	1.42 67	1.42 65	1.42 68	1.42 66	1.42 65	1.42 63	1.42 65	1.42 66	1.42 64	1.42 64	1.42 64

Regformer-3		1.42 53	1.42 54	1.42 59	1.42 66	1.42 67	1.42 65	1.42 68	1.42 66	1.42 65	1.42 63	1.42 65	1.42 66	1.42 64	1.42 64	1.42 64

Regformer-4		1.42 53	1.42 54	1.42 59	1.42 66	1.42 67	1.42 65	1.42 68	1.42 66	1.42 65	1.42 63	1.42 65	1.42 66	1.42 64	1.42 64	1.42 64

Regformer-1		1.42 53	1.42 54	1.42 59	1.42 66	1.42 67	1.42 65	1.42 68	1.42 66	1.42 65	1.42 63	1.42 65	1.42 66	1.42 64	1.42 64	1.42 64

Regformer-2		1.42 53	1.42 54	1.42 59	1.42 66	1.42 67	1.42 65	1.42 68	1.42 66	1.42 65	1.42 63	1.42 65	1.42 66	1.42 64	1.42 64	1.42 64

EI-MVSNet		1.42 53	1.42 54	1.42 59	1.42 66	1.42 67	1.42 65	1.42 68	1.42 66	1.42 65	1.42 63	1.42 65	1.42 66	1.42 64	1.42 64	1.42 64

Regformer		1.42 53	1.42 54	1.42 59	1.42 66	1.42 67	1.42 65	1.42 68	1.42 66	1.42 65	1.42 63	1.42 65	1.42 66	1.42 64	1.42 64	1.42 64

CVMVSNet		1.42 53	1.42 54	1.42 59	1.42 66	1.42 67	1.42 65	1.42 68	1.42 66	1.42 65	1.42 63	1.42 65	1.42 66	1.42 64	1.42 64	1.42 64

EU-MVSNet		1.42 53	1.42 54	1.42 59	1.42 66	1.42 67	1.42 65	1.42 68	1.42 66	1.42 65	1.42 63	1.42 65	1.42 66	1.42 64	1.42 64	1.42 64

PS-CasMVS		1.42 53	1.42 54	1.42 59	1.42 66	1.42 67	1.42 65	1.42 68	1.42 66	1.42 65	1.42 63	1.42 65	1.42 66	1.42 64	1.42 64	1.42 64

UniMVSNet_NR-MVSNet		1.42 53	1.42 54	1.42 59	1.42 66	1.42 67	1.42 65	1.42 68	1.42 66	1.42 65	1.42 63	1.42 65	1.42 66	1.42 64	1.42 64	1.42 64

PEN-MVS		1.42 53	1.42 54	1.42 59	1.42 66	1.42 67	1.42 65	1.42 68	1.42 66	1.42 65	1.42 63	1.42 65	1.42 66	1.42 64	1.42 64	1.42 64

TransMVSNet (Re)		1.42 53	1.42 54	1.42 59	1.42 66	1.42 67	1.42 65	1.42 68	1.42 66	1.42 65	1.42 63	1.42 65	1.42 66	1.42 64	1.42 64	1.42 64

DTE-MVSNet		1.42 53	1.42 54	1.42 59	1.42 66	1.42 67	1.42 65	1.42 68	1.42 66	1.42 65	1.42 63	1.42 65	1.42 66	1.42 64	1.42 64	1.42 64

DU-MVS		1.42 53	1.42 54	1.42 59	1.42 66	1.42 67	1.42 65	1.42 68	1.42 66	1.42 65	1.42 63	1.42 65	1.42 66	1.42 64	1.42 64	1.42 64

UniMVSNet (Re)		1.42 53	1.42 54	1.42 59	1.42 66	1.42 67	1.42 65	1.42 68	1.42 66	1.42 65	1.42 63	1.42 65	1.42 66	1.42 64	1.42 64	1.42 64

CP-MVSNet		1.42 53	1.42 54	1.42 59	1.42 66	1.42 67	1.42 65	1.42 68	1.42 66	1.42 65	1.42 63	1.42 65	1.42 66	1.42 64	1.42 64	1.42 64

WR-MVS_H		1.42 53	1.42 54	1.42 59	1.42 66	1.42 67	1.42 65	1.42 68	1.42 66	1.42 65	1.42 63	1.42 65	1.42 66	1.42 64	1.42 64	1.42 64

WR-MVS		1.42 53	1.42 54	1.42 59	1.42 66	1.42 67	1.42 65	1.42 68	1.42 66	1.42 65	1.42 63	1.42 65	1.42 66	1.42 64	1.42 64	1.42 64

NR-MVSNet		1.42 53	1.42 54	1.42 59	1.42 66	1.42 67	1.42 65	1.42 68	1.42 66	1.42 65	1.42 63	1.42 65	1.42 66	1.42 64	1.42 64	1.42 64

Baseline_NR-MVSNet		1.42 53	1.42 54	1.42 59	1.42 66	1.42 67	1.42 65	1.42 68	1.42 66	1.42 65	1.42 63	1.42 65	1.42 66	1.42 64	1.42 64	1.42 64

TranMVSNet+NR-MVSNet		1.42 53	1.42 54	1.42 59	1.42 66	1.42 67	1.42 65	1.42 68	1.42 66	1.42 65	1.42 63	1.42 65	1.42 66	1.42 64	1.42 64	1.42 64

MVSFormer		1.42 53	1.42 54	1.42 59	1.42 66	1.42 67	1.42 65	1.42 68	1.42 66	1.42 65	1.42 63	1.42 65	1.42 66	1.42 64	1.42 64	1.42 64

jason		1.42 53	1.42 54	1.42 59	1.42 66	1.42 67	1.42 65	1.42 68	1.42 66	1.42 65	1.42 63	1.42 65	1.42 66	1.42 64	1.42 64	1.42 64
jason: jason.
lupinMVS		1.42 53	1.42 54	1.42 59	1.42 66	1.42 67	1.42 65	1.42 68	1.42 66	1.42 65	1.42 63	1.42 65	1.42 66	1.42 64	1.42 64	1.42 64

test_djsdf		1.42 53	1.42 54	1.42 59	1.42 66	1.42 67	1.42 65	1.42 68	1.42 66	1.42 65	1.42 63	1.42 65	1.42 66	1.42 64	1.42 64	1.42 64

alignmvs		2.00 80	2.00 81	2.00 86	2.00 94	2.00 94	2.00 92	2.00 97	2.00 93	2.00 92	2.00 90	2.00 92	2.00 93	2.00 91	2.00 91	2.00 91

nrg030		2.00 80	2.00 81	2.00 86	2.00 94	2.00 94	2.00 92	2.00 97	2.00 93	2.00 92	2.00 90	2.00 92	2.00 93	2.00 91	2.00 91	2.00 91

LFMVS		2.00 80	2.00 81	2.00 86	2.00 94	2.00 94	2.00 92	2.00 97	2.00 93	2.00 92	2.00 90	2.00 92	2.00 93	2.00 91	2.00 91	2.00 91

VDD-MVS		2.00 80	2.00 81	2.00 86	2.00 94	2.00 94	2.00 92	2.00 97	2.00 93	2.00 92	2.00 90	2.00 92	2.00 93	2.00 91	2.00 91	2.00 91

VDDNet		2.00 80	2.00 81	2.00 86	2.00 94	2.00 94	2.00 92	2.00 97	2.00 93	2.00 92	2.00 90	2.00 92	2.00 93	2.00 91	2.00 91	2.00 91

VPNet		2.00 80	2.00 81	2.00 86	2.00 94	2.00 94	2.00 92	2.00 97	2.00 93	2.00 92	2.00 90	2.00 92	2.00 93	2.00 91	2.00 91	2.00 91

VNet		2.00 80	2.00 81	2.00 86	2.00 94	2.00 94	2.00 92	2.00 97	2.00 93	2.00 92	2.00 90	2.00 92	2.00 93	2.00 91	2.00 91	2.00 91

VPA-MVSNet		2.00 80	2.00 81	2.00 86	2.00 94	2.00 94	2.00 92	2.00 97	2.00 93	2.00 92	2.00 90	2.00 92	2.00 93	2.00 91	2.00 91	2.00 91

cascas		2.00 80	2.00 81	2.00 86	2.00 94	2.00 94	2.00 92	2.00 97	2.00 93	2.00 92	2.00 90	2.00 92	2.00 93	2.00 91	2.00 91	2.00 91

UnsupCasMVSNet_eth		5.90 89	5.90 90	5.90 95	5.90 103	5.90 103	5.90 102	5.90 109	5.90 103	5.90 101	5.90 99	5.90 103	5.90 102	5.90 100	5.90 103	5.90 103

UnsupCasMVSNet_bld		5.90 89	5.90 90	5.90 95	5.90 103	5.90 103	5.90 102	5.90 109	5.90 103	5.90 101	5.90 99	5.90 103	5.90 102	5.90 100	5.90 103	5.90 103

WTY-MVS		5.90 89	5.90 90	5.90 95	5.90 103	5.90 103	5.90 102	5.90 109	5.90 103	5.90 101	5.90 99	5.90 103	5.90 102	5.90 100	5.90 103	5.90 103

HY-MVS	5.90 1	5.90 89	5.90 90	5.90 95	5.90 103	5.90 103	5.90 102	5.90 109	5.90 103	5.90 101	5.90 99	5.90 103	5.90 102	5.90 100	5.90 103	5.90 103

sss		5.90 89	5.90 90	5.90 95	5.90 103	5.90 103	5.90 102	5.90 109	5.90 103	5.90 101	5.90 99	5.90 103	5.90 102	5.90 100	5.90 103	5.90 103

Test_1112_low_res		5.90 89	5.90 90	5.90 95	5.90 103	5.90 103	5.90 102	5.90 109	5.90 103	5.90 101	5.90 99	5.90 103	5.90 102	5.90 100	5.90 103	5.90 103

1112_ss		5.90 89	5.90 90	5.90 95	5.90 103	5.90 103	5.90 102	5.90 109	5.90 103	5.90 101	5.90 99	5.90 103	5.90 102	5.90 100	5.90 103	5.90 103

ab-mvs-re		5.90 89	5.90 90	5.90 95	5.90 103	5.90 103	5.90 102	5.90 109	5.90 103	5.90 101	5.90 99	5.90 103	5.90 102	5.90 100	5.90 103	5.90 103

ab-mvs		5.90 89	5.90 90	5.90 95	5.90 103	5.90 103	5.90 102	5.90 109	5.90 103	5.90 101	5.90 99	5.90 103	5.90 102	5.90 100	5.90 103	5.90 103

CDPH-MVS		6.66 98	6.66 99	6.66 104	6.66 112	6.66 112	6.66 111	6.66 118	6.66 112	6.66 110	6.66 108	6.66 112	6.66 111	6.66 109	6.66 112	6.66 112

xiu_mvs_v1_base_debu		10.28 99	10.28 101	10.28 106	10.28 114	10.28 116	10.28 114	10.28 121	10.28 115	10.28 114	10.28 110	10.28 116	10.28 114	10.28 112	10.28 115	10.28 114

xiu_mvs_v2_base		10.28 99	10.28 101	10.28 106	10.28 114	10.28 116	10.28 114	10.28 121	10.28 115	10.28 114	10.28 110	10.28 116	10.28 114	10.28 112	10.28 115	10.28 114

xiu_mvs_v1_base		10.28 99	10.28 101	10.28 106	10.28 114	10.28 116	10.28 114	10.28 121	10.28 115	10.28 114	10.28 110	10.28 116	10.28 114	10.28 112	10.28 115	10.28 114

xiu_mvs_v1_base_debi		10.28 99	10.28 101	10.28 106	10.28 114	10.28 116	10.28 114	10.28 121	10.28 115	10.28 114	10.28 110	10.28 116	10.28 114	10.28 112	10.28 115	10.28 114

cdsmvs_eth3d_5k		10.28 99	10.28 101	10.28 106	10.28 114	10.28 116	10.28 114	10.28 121	10.28 115	10.28 114	10.28 110	10.28 116	10.28 114	10.28 112	10.28 115	10.28 114

pcd_1.5k_mvsjas		10.28 99	10.28 101	10.28 106	10.28 114	10.28 116	10.28 114	10.28 121	10.28 115	10.28 114	10.28 110	10.28 116	10.28 114	10.28 112	10.28 115	10.28 114

PS-MVSNAJss		10.28 99	10.28 101	10.28 106	10.28 114	10.28 116	10.28 114	10.28 121	10.28 115	10.28 114	10.28 110	10.28 116	10.28 114	10.28 112	10.28 115	10.28 114

PS-MVSNAJ		10.28 99	10.28 101	10.28 106	10.28 114	10.28 116	10.28 114	10.28 121	10.28 115	10.28 114	10.28 110	10.28 116	10.28 114	10.28 112	10.28 115	10.28 114

jajsoiax		10.28 99	10.28 101	10.28 106	10.28 114	10.28 116	10.28 114	10.28 121	10.28 115	10.28 114	10.28 110	10.28 116	10.28 114	10.28 112	10.28 115	10.28 114

mvs_tets		10.28 99	10.28 101	10.28 106	10.28 114	10.28 116	10.28 114	10.28 121	10.28 115	10.28 114	10.28 110	10.28 116	10.28 114	10.28 112	10.28 115	10.28 114

SR-MVS-dyc-post		11.55 109	11.55 111	11.55 118	11.55 125	11.55 127	11.55 124	11.55 133	11.55 125	11.55 125	11.55 120	11.55 127	11.55 124	11.55 122	11.55 125	11.55 124

XXY-MVS		15.00 110	15.00 112	15.00 119	15.00 126	15.00 129	15.00 125	15.00 135	15.00 126	15.00 127	15.00 121	15.00 132	15.00 126	15.00 124	15.00 127	15.00 126

test_method		18.29 111	20.89 113	10.50 116	15.00 126	13.00 128	55.00 132	3.00 107	34.00 128	11.50 124	32.50 122	5.00 102	13.50 125	27.00 126	5.00 102	5.00 102

GeoE		19.41 112	22.09 114	11.37 117	17.21 128	11.30 126	50.50 131	4.30 108	33.60 127	11.70 126	44.50 127	7.30 113	18.90 127	22.60 125	7.10 113	3.90 100

BH-w/o		40.00 113	40.00 115	40.00 121	40.00 129	40.00 130	40.00 127	40.00 152	40.00 129	40.00 129	40.00 123	40.00 150	40.00 129	40.00 127	40.00 143	40.00 138

BH-untuned		40.00 113	40.00 115	40.00 121	40.00 129	40.00 130	40.00 127	40.00 152	40.00 129	40.00 129	40.00 123	40.00 150	40.00 129	40.00 127	40.00 143	40.00 138

BH-RMVSNet		40.00 113	40.00 115	40.00 121	40.00 129	40.00 130	40.00 127	40.00 152	40.00 129	40.00 129	40.00 123	40.00 150	40.00 129	40.00 127	40.00 143	40.00 138

TR-MVS		40.00 113	40.00 115	40.00 121	40.00 129	40.00 130	40.00 127	40.00 152	40.00 129	40.00 129	40.00 123	40.00 150	40.00 129	40.00 127	40.00 143	40.00 138

GBi-Net		44.67 117	49.24 119	30.96 120	47.53 133	47.57 134	126.09 133	8.00 119	76.99 133	26.09 128	73.50 129	11.27 126	30.55 128	61.12 131	12.58 126	14.75 125

dp		87.20 118	113.80 122	7.42 105	10.50 124	8.88 113	298.82 141	2.70 106	510.35 157	7.79 111	172.93 132	3.37 101	9.16 112	14.00 123	3.71 101	4.23 101

new_pmnet		88.14 119	98.62 120	56.70 125	98.14 142	56.07 135	246.79 135	15.37 136	148.06 134	50.77 133	143.13 130	23.35 133	62.65 133	93.26 132	68.71 150	51.38 149

N_pmnet		88.14 119	98.62 120	56.70 125	98.14 142	56.07 135	246.79 135	15.37 136	148.06 134	50.77 133	143.13 130	23.35 133	62.65 133	93.26 132	68.71 150	51.38 149

CANet		110.62 121	124.04 123	70.34 129	82.03 138	74.27 141	325.54 142	25.25 138	207.16 137	69.28 139	194.38 133	27.53 135	95.79 143	147.76 136	37.43 132	40.97 142

CANet_DTU		110.62 121	124.04 123	70.34 129	82.03 138	74.27 141	325.54 142	25.25 138	207.16 137	69.28 139	194.38 133	27.53 135	95.79 143	147.76 136	37.43 132	40.97 142

MVS_0304		110.62 121	124.04 123	70.34 129	82.03 138	74.27 141	325.54 142	25.25 138	207.16 137	69.28 139	194.38 133	27.53 135	95.79 143	147.76 136	37.43 132	40.97 142

UGNet		110.62 121	124.04 123	70.34 129	82.03 138	74.27 141	325.54 142	25.25 138	207.16 137	69.28 139	194.38 133	27.53 135	95.79 143	147.76 136	37.43 132	40.97 142
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_NAP		118.81 125	133.18 127	75.70 133	74.28 136	73.29 139	284.50 137	11.35 131	238.58 143	65.86 137	255.35 150	14.55 130	115.69 153	222.18 152	31.94 130	38.12 136

FMVSNet5		124.76 126	140.93 128	76.26 135	107.44 145	100.17 149	329.88 146	27.12 145	259.44 148	74.30 143	204.34 137	30.74 139	92.41 136	196.98 140	38.15 136	36.19 129

test1		124.76 126	140.93 128	76.26 135	107.44 145	100.17 149	329.88 146	27.12 145	259.44 148	74.30 143	204.34 137	30.74 139	92.41 136	196.98 140	38.15 136	36.19 129

FMVSNet3		124.76 126	140.93 128	76.26 135	107.44 145	100.17 149	329.88 146	27.12 145	259.44 148	74.30 143	204.34 137	30.74 139	92.41 136	196.98 140	38.15 136	36.19 129

FMVSNet2		124.76 126	140.93 128	76.26 135	107.44 145	100.17 149	329.88 146	27.12 145	259.44 148	74.30 143	204.34 137	30.74 139	92.41 136	196.98 140	38.15 136	36.19 129

FMVSNet1		124.76 126	140.93 128	76.26 135	107.44 145	100.17 149	329.88 146	27.12 145	259.44 148	74.30 143	204.34 137	30.74 139	92.41 136	196.98 140	38.15 136	36.19 129

MIMVSNet1		124.76 126	140.93 128	76.26 135	107.44 145	100.17 149	329.88 146	27.12 145	259.44 148	74.30 143	204.34 137	30.74 139	92.41 136	196.98 140	38.15 136	36.19 129

MIMVSNet		124.76 126	140.93 128	76.26 135	107.44 145	100.17 149	329.88 146	27.12 145	259.44 148	74.30 143	204.34 137	30.74 139	92.41 136	196.98 140	38.15 136	36.19 129

DSMNet-mixed		131.33 133	143.00 135	96.33 146	99.00 144	81.00 145	201.00 134	45.00 156	335.00 155	99.00 153	251.00 149	38.00 149	110.00 152	120.00 135	99.00 153	98.00 152

PVSNet_Blended_VisFu		136.90 134	155.40 136	81.40 142	111.00 152	96.20 146	407.00 153	25.90 142	251.60 145	85.10 150	240.50 146	37.00 146	99.90 147	199.80 147	40.70 147	48.10 146

PVSNet_BlendedMVS		136.90 134	155.40 136	81.40 142	111.00 152	96.20 146	407.00 153	25.90 142	251.60 145	85.10 150	240.50 146	37.00 146	99.90 147	199.80 147	40.70 147	48.10 146

PVSNet_Blended		136.90 134	155.40 136	81.40 142	111.00 152	96.20 146	407.00 153	25.90 142	251.60 145	85.10 150	240.50 146	37.00 146	99.90 147	199.80 147	40.70 147	48.10 146

test1172		216.26 137	257.16 139	93.57 145	310.10 159	111.10 156	31.10 126	45.10 157	192.73 136	176.39 154	512.31 153	66.33 156	78.35 135	891.20 177	89.18 152	91.27 151

DP-MVS		264.78 138	296.02 140	171.04 147	191.70 155	183.96 157	827.10 164	78.36 158	438.24 156	176.64 155	435.12 152	65.04 155	230.52 157	334.02 153	117.96 154	98.64 153

tmp_tt		371.08 139	412.78 141	246.00 149	231.00 156	197.00 158	1293.00 176	376.00 211	756.00 166	609.00 190	71.00 128	106.00 165	195.00 155	102.00 134	171.00 163	346.00 186

RPSCF		394.81 140	445.63 142	242.35 148	276.55 158	253.63 159	1207.27 174	90.69 163	715.56 164	241.57 157	684.87 161	111.96 166	320.02 158	548.38 160	133.81 155	153.39 155

EG-PatchMatch MVS		437.03 141	493.12 145	268.77 150	264.80 157	260.20 160	1491.80 179	98.00 167	723.20 165	238.80 156	722.40 162	63.10 154	382.00 161	629.00 164	207.00 170	164.10 158

ADS-MVSNet2		443.33 142	482.84 143	324.79 157	434.94 170	387.73 167	1110.57 172	87.69 161	887.02 170	282.92 158	779.29 163	98.57 163	422.76 166	502.40 154	162.19 161	163.87 156

ADS-MVSNet		443.33 142	482.84 143	324.79 157	434.94 170	387.73 167	1110.57 172	87.69 161	887.02 170	282.92 158	779.29 163	98.57 163	422.76 166	502.40 154	162.19 161	163.87 156

MVP-Stereo		473.58 144	533.67 146	293.33 151	376.00 163	318.00 161	1461.00 177	96.00 164	835.00 168	290.00 161	804.00 166	97.00 161	383.00 163	688.00 171	156.00 156	179.00 160
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
MS-PatchMatch		473.58 144	533.67 146	293.33 151	376.00 163	318.00 161	1461.00 177	96.00 164	835.00 168	290.00 161	804.00 166	97.00 161	383.00 163	688.00 171	156.00 156	179.00 160

PatchmatchNet		492.52 146	551.22 148	316.40 155	400.20 166	357.90 165	1277.10 175	115.80 172	1034.60 180	315.90 163	874.00 169	155.10 171	402.20 165	629.50 165	158.80 158	189.10 162
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
tpmvs		501.65 147	567.42 149	304.33 154	395.39 165	356.32 164	1512.04 180	216.53 198	994.15 173	350.16 166	804.16 168	119.38 167	380.98 160	555.14 161	159.87 159	175.69 159

DELS-MVS		514.57 148	587.73 151	295.12 153	343.03 160	328.09 163	1540.48 181	116.22 173	988.59 172	325.44 164	906.22 170	119.86 168	365.72 159	788.60 173	161.09 160	191.55 163
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
DP-MVS Recon		516.25 149	581.17 150	321.48 156	361.02 161	429.00 171	1995.36 185	78.48 159	796.20 167	283.32 160	796.02 165	96.78 160	382.98 162	636.72 166	186.66 167	152.46 154

gg-mvs-nofinetune		594.69 150	605.37 152	562.67 177	617.29 186	500.33 175	772.30 160	413.12 219	579.21 158	552.71 184	567.40 154	662.54 238	531.67 170	503.93 156	779.80 217	656.02 201

SR-MVS		610.10 151	610.10 153	610.10 182	610.10 180	610.10 191	610.10 158	610.10 243	610.10 162	610.10 191	610.10 159	610.10 226	610.10 185	610.10 162	610.10 200	610.10 198

CR-MVSNet		612.36 152	617.81 155	596.01 180	611.29 182	600.33 188	790.30 161	513.12 234	579.21 158	552.71 184	567.40 154	662.54 238	531.67 170	503.93 156	779.80 217	656.02 201

IterMVS		615.05 153	691.66 156	385.23 161	516.40 173	454.80 172	1863.80 183	102.10 169	1142.20 182	364.10 167	1093.20 184	135.00 169	480.40 169	826.90 174	181.20 164	220.50 165
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
IB-MVS	872.44 4	616.41 154	700.96 157	362.78 159	426.10 169	409.25 169	1822.69 182	124.42 181	1186.23 183	366.85 168	1079.42 182	190.60 184	451.78 168	930.72 179	181.59 165	227.30 166
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
ACMH+	729.97 2	661.38 155	754.00 158	383.51 160	368.96 162	376.38 166	2483.74 197	82.42 160	1089.25 181	333.39 165	1219.68 185	66.53 157	573.60 182	957.86 180	184.14 166	200.56 164

Gipuma		689.75 156	767.00 159	458.00 169	613.00 185	549.00 186	1943.00 184	187.00 195	1230.00 184	518.00 181	1092.00 183	203.00 190	564.00 175	892.00 178	225.00 179	261.00 173
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
IterMVS-LS		758.94 157	856.56 162	466.10 170	606.60 178	546.80 184	2309.90 187	122.20 180	1402.80 188	463.50 172	1348.20 187	192.60 185	574.60 183	1028.60 190	234.60 181	276.90 175
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
new-patchmatchnet		766.12 158	859.03 163	487.38 173	595.68 175	536.14 177	2346.27 188	142.51 186	1488.08 190	422.43 169	1361.32 189	163.65 174	628.60 187	1003.74 189	207.61 171	297.41 179

SixPastTwentyTwo		773.62 159	869.37 165	486.35 172	603.45 177	547.15 185	2532.14 198	106.92 171	1434.95 189	428.08 170	1360.56 188	165.15 175	628.96 188	984.09 181	209.01 172	282.94 176

mvs_anonymous		774.90 160	882.28 166	452.77 163	636.50 187	537.20 178	2348.80 189	120.30 174	1504.30 191	474.40 173	1371.10 190	186.90 177	564.70 176	1078.90 192	219.30 173	256.40 167

casdiffmvs		774.90 160	882.28 166	452.77 163	636.50 187	537.20 178	2348.80 189	120.30 174	1504.30 191	474.40 173	1371.10 190	186.90 177	564.70 176	1078.90 192	219.30 173	256.40 167

diffmvs		774.90 160	882.28 166	452.77 163	636.50 187	537.20 178	2348.80 189	120.30 174	1504.30 191	474.40 173	1371.10 190	186.90 177	564.70 176	1078.90 192	219.30 173	256.40 167

baseline2		774.90 160	882.28 166	452.77 163	636.50 187	537.20 178	2348.80 189	120.30 174	1504.30 191	474.40 173	1371.10 190	186.90 177	564.70 176	1078.90 192	219.30 173	256.40 167

baseline1		774.90 160	882.28 166	452.77 163	636.50 187	537.20 178	2348.80 189	120.30 174	1504.30 191	474.40 173	1371.10 190	186.90 177	564.70 176	1078.90 192	219.30 173	256.40 167

baseline		774.90 160	882.28 166	452.77 163	636.50 187	537.20 178	2348.80 189	120.30 174	1504.30 191	474.40 173	1371.10 190	186.90 177	564.70 176	1078.90 192	219.30 173	256.40 167

RPMNet		787.26 166	829.13 160	661.63 186	885.90 201	895.90 208	455.98 156	610.10 243	1297.17 185	1002.26 213	1001.67 180	655.98 236	611.10 186	667.90 168	885.21 229	477.90 195

JIA-IIPM		804.30 167	835.64 161	710.26 191	885.90 201	895.90 208	455.98 156	668.73 247	1297.17 185	1002.26 213	1001.67 180	655.98 236	756.98 192	667.90 168	885.21 229	477.90 195

CSCG		826.03 168	963.29 173	414.24 162	421.52 168	426.11 170	2230.35 186	179.52 194	1827.44 202	733.43 201	933.12 172	281.25 197	545.23 174	1800.35 208	262.64 183	271.38 174

PVSNet	1207.94 6	829.56 169	937.18 172	506.69 174	645.55 193	585.72 187	2477.98 196	130.52 182	1578.29 198	509.50 180	1460.01 196	194.90 186	637.19 189	1170.78 199	267.07 185	297.17 178

PatchT		856.34 170	860.99 164	842.38 196	1290.90 216	880.90 206	790.30 161	1267.30 265	579.21 158	923.90 203	567.40 154	662.54 238	990.23 200	887.56 176	779.80 217	656.02 201

K. test v3		877.74 171	980.16 174	570.46 179	1316.85 218	813.15 203	2565.52 199	103.78 170	1509.49 197	548.33 183	1258.90 186	219.93 195	587.82 184	1102.37 198	196.30 168	310.42 181

MVSTER		890.06 172	1005.91 181	542.52 175	736.13 198	653.90 195	2616.56 200	145.22 188	1692.10 201	555.69 187	1554.72 198	266.25 196	660.02 190	1219.66 200	266.84 184	313.64 182

PMVS	863.65 3	957.08 173	1054.11 182	666.00 188	401.00 167	495.00 174	3790.00 205	279.00 200	1607.00 200	521.00 182	1745.00 200	90.00 158	1105.00 211	639.00 167	415.00 196	398.00 193
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
ACMH	993.80 5	967.92 174	1106.11 184	553.33 176	494.00 172	534.00 176	3581.00 203	136.00 183	1585.00 199	478.00 179	1871.00 202	90.00 158	839.00 194	1460.00 202	260.00 182	287.00 177
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
PVSNet_0	1661.03 9	968.54 175	1066.82 183	673.70 189	706.94 196	695.69 196	2669.02 201	153.52 190	2108.17 207	605.54 189	1679.14 199	213.26 194	886.75 197	1236.76 201	229.01 180	438.67 194

OurMVSNet-221017-0		999.00 176	999.00 175	999.00 197	999.00 206	999.00 210	999.00 165	999.00 258	999.00 174	999.00 206	999.00 173	999.00 251	999.00 202	999.00 182	999.00 235	999.00 232

EPMVS		999.00 176	999.00 175	999.00 197	999.00 206	999.00 210	999.00 165	999.00 258	999.00 174	999.00 206	999.00 173	999.00 251	999.00 202	999.00 182	999.00 235	999.00 232

uanet_test		1000.00 178	1000.00 177	1000.00 200	1000.00 209	1000.00 213	1000.00 168	1000.00 261	1000.00 176	1000.00 209	1000.00 176	1000.00 254	1000.00 205	1000.00 185	1000.00 238	1000.00 235

sosnet		1000.00 178	1000.00 177	1000.00 200	1000.00 209	1000.00 213	1000.00 168	1000.00 261	1000.00 176	1000.00 209	1000.00 176	1000.00 254	1000.00 205	1000.00 185	1000.00 238	1000.00 235

USDC		1000.00 178	1000.00 177	1000.00 200	1000.00 209	1000.00 213	1000.00 168	1000.00 261	1000.00 176	1000.00 209	1000.00 176	1000.00 254	1000.00 205	1000.00 185	1000.00 238	1000.00 235

TinyColmap		1000.00 178	1000.00 177	1000.00 200	1000.00 209	1000.00 213	1000.00 168	1000.00 261	1000.00 176	1000.00 209	1000.00 176	1000.00 254	1000.00 205	1000.00 185	1000.00 238	1000.00 235

ACMP	1246.57 7	1086.24 182	1235.17 186	639.45 183	596.53 176	639.91 193	3904.24 206	152.04 189	1851.54 203	566.58 188	1997.95 204	138.50 170	938.30 198	1605.46 204	303.70 191	340.14 184
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
Patchmtry		1090.75 183	1198.88 185	766.38 195	1290.90 216	485.90 173	2423.98 195	1267.30 265	1297.17 185	923.90 203	923.40 171	1215.54 259	990.23 200	667.90 168	779.80 217	823.02 215

test_0402		1110.00 184	1260.00 187	660.00 185	900.00 204	780.00 202	3300.00 202	210.00 197	2040.00 206	690.00 196	1950.00 203	300.00 200	810.00 193	1620.00 205	330.00 192	390.00 192

MVS_111021_LR		1136.45 185	1298.72 188	649.64 184	756.17 199	726.26 199	3785.94 204	138.15 185	2190.64 208	629.63 194	2064.39 205	165.45 176	874.83 196	1678.43 207	279.70 186	347.82 187

ACMM	1311.08 8	1165.06 186	1332.72 189	662.07 187	584.90 174	715.99 198	4373.59 210	153.99 191	1880.27 204	709.02 198	2316.97 206	188.63 183	939.89 199	1484.30 203	302.78 190	330.34 183
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
MSLP-MVS++		1242.93 187	1411.08 190	738.48 193	712.71 197	712.68 197	4168.17 208	136.50 184	2276.40 209	613.28 193	2368.60 209	161.61 173	1130.38 212	1964.54 211	297.88 188	372.39 189

MG-MVS		1256.50 188	1432.00 191	730.00 192	610.00 179	760.00 200	4720.00 211	169.00 192	1920.00 205	723.00 200	2510.00 212	201.00 188	1050.00 209	1645.00 206	390.00 195	380.00 190

ACMMPR		1296.60 189	1480.82 192	743.96 194	899.25 203	763.47 201	4305.47 209	143.90 187	2530.94 212	683.99 195	2346.34 208	201.65 189	1098.25 210	1920.59 210	295.21 187	370.16 188

TSAR-MVS + GP.		1386.84 190	1622.84 194	678.81 190	952.13 205	840.17 205	5358.21 214	170.75 193	2650.47 213	713.54 199	2394.28 210	209.42 193	855.56 195	1854.36 209	302.42 189	340.71 185

FPMVS		1407.00 191	1495.59 193	1141.23 205	648.01 194	893.85 207	4124.00 207	503.81 233	3219.04 215	742.72 202	2498.84 211	157.98 172	1727.83 218	832.93 175	732.98 216	802.00 210

DeepC-MVS_fast	2190.19 12	1535.59 192	1886.82 196	481.89 171	847.73 200	830.16 204	7943.84 230	189.23 196	2398.83 210	691.73 197	2341.13 207	209.16 192	230.25 156	1999.25 212	360.46 193	385.25 191
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
COLMAP_ROB	2144.59 11	1658.33 193	1869.33 195	1025.33 204	1030.00 213	1023.00 217	5311.00 213	359.00 209	3044.00 214	937.00 205	2892.00 213	332.00 204	1440.00 215	2312.00 214	607.00 199	613.00 200
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
F-COLMAP		1878.17 194	2113.11 197	1173.33 208	1231.00 214	1174.00 218	6297.00 216	392.00 214	3356.00 217	1087.00 215	3082.00 214	361.00 208	1670.00 217	2523.00 216	689.00 206	676.00 205

OpenMVS_ROB	1936.51 10	1959.51 195	2224.88 199	1163.39 207	1253.91 215	1434.22 221	7065.71 220	272.76 199	2472.29 211	1647.54 244	3538.72 217	200.37 187	1496.48 216	2575.17 217	997.45 234	559.48 197

CMPMVS	2623.62 15	1983.08 196	2156.14 198	1463.89 218	1414.80 220	1517.00 223	5239.20 212	867.40 252	3310.30 216	1128.70 217	3489.90 216	366.75 209	2030.20 229	2427.60 215	1160.60 247	844.46 218
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
MVS-HIRNet		2125.39 197	2452.68 200	1143.53 206	2938.33 261	1446.92 222	6083.19 215	391.74 213	3801.71 220	1202.10 219	3439.72 215	492.73 218	1304.35 214	3048.25 220	676.32 205	679.32 206

PLC	2858.82 16	2192.92 198	2474.00 201	1349.67 210	1407.00 219	1356.00 220	7164.00 221	475.00 226	3970.00 221	1237.00 222	3765.00 220	451.00 215	1891.00 223	3006.00 219	791.00 222	802.00 210
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
OpenMVS	2352.88 13	2263.08 199	2530.89 202	1459.67 217	1767.00 231	1591.00 226	7932.00 229	399.00 215	3643.00 218	1176.00 218	3569.00 218	297.00 199	1927.00 225	3302.00 221	693.00 211	861.00 219

PCF-MVS	4335.85 20	2272.23 200	2597.03 203	1297.84 209	1701.20 223	1332.37 219	8105.11 231	451.45 222	4031.84 222	1099.10 216	3966.50 221	467.45 216	1734.05 219	2701.68 218	848.94 226	827.11 216
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
CHOSEN 280x420		2340.81 201	2643.03 204	1434.14 211	2025.55 240	1629.36 230	6542.40 217	412.49 216	4219.70 223	1547.02 233	4328.52 223	650.74 233	1798.26 220	3333.17 222	727.72 213	874.79 220

CHOSEN 1792x2688		2340.81 201	2643.03 204	1434.14 211	2025.55 240	1629.36 230	6542.40 217	412.49 216	4219.70 223	1547.02 233	4328.52 223	650.74 233	1798.26 220	3333.17 222	727.72 213	874.79 220

HyFIR lowres test		2340.81 201	2643.03 204	1434.14 211	2025.55 240	1629.36 230	6542.40 217	412.49 216	4219.70 223	1547.02 233	4328.52 223	650.74 233	1798.26 220	3333.17 222	727.72 213	874.79 220

3Dnovator	2482.06 14	2531.17 204	2839.56 207	1606.00 219	1732.00 227	1557.00 225	8375.00 233	483.00 227	4370.00 226	1371.00 228	4200.00 222	350.00 206	2207.00 230	3877.00 228	798.00 223	1054.00 239

tpmrst		2557.50 205	2847.12 208	1688.66 222	1784.08 232	1778.25 240	7445.50 227	342.14 206	4471.54 227	1534.55 232	4382.10 226	530.10 222	2361.21 233	4142.81 232	991.22 233	926.51 225

AdaColmap		2570.77 206	2948.61 209	1437.24 214	1873.64 233	1526.60 224	7819.77 228	373.97 210	4970.45 230	1479.29 230	4648.46 228	525.80 221	1904.97 224	4150.42 233	695.69 212	880.14 223

SD-MVS		2654.53 207	3055.56 212	1451.45 215	1725.60 224	1598.35 227	9203.30 237	315.86 203	5016.02 232	1363.85 225	4894.28 230	387.23 210	2023.43 226	3973.88 229	620.04 202	732.56 207
Zhenlong Yuan, Jiakai Cao, Zhaoxin Li, Hao Jiang and Zhaoqi Wang: SD-MVS: Segmentation-driven Deformation Multi-View Stereo with Spherical Refinement and EM optimization. AAAI2024
DeepPCF-MVS	3452.42 18	2670.71 208	3021.57 210	1618.12 220	2377.67 247	1751.39 239	8915.70 236	567.44 241	4569.74 228	1236.84 221	4615.63 227	513.23 219	2291.32 231	3515.48 225	882.39 228	811.66 212

LF4IMVS		2699.50 209	3049.67 211	1649.00 221	1755.00 228	1689.00 234	8330.00 232	464.00 224	4997.00 231	1528.00 231	4763.00 229	568.00 224	2296.00 232	4215.00 234	827.00 225	962.00 229

Vis-MVSNet		2877.42 210	3170.00 213	1999.67 232	1673.00 222	2042.00 249	8593.00 234	474.00 225	6452.00 245	1268.00 223	5125.00 233	339.00 205	3004.00 246	4222.00 235	384.00 194	953.00 228
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
SteuartSystems-ACMMP		2891.50 211	3284.78 214	1711.67 223	1954.00 234	1655.00 233	10117.00 246	445.00 221	5102.00 235	1375.00 229	5126.00 234	351.00 207	2638.00 243	4402.00 236	691.00 209	842.00 217
Skip Steuart: Steuart Systems R&D Blog.
3Dnovator+	3414.41 17	3146.67 212	3537.00 215	1975.67 230	2310.00 245	2005.00 248	10100.00 245	626.00 246	5753.00 236	1803.00 247	5179.00 235	487.00 217	2622.00 241	4550.00 237	1025.00 242	1300.00 246

DeepC-MVS	3917.13 19	3155.06 213	3601.83 216	1814.72 228	2515.52 250	1941.53 244	10432.50 247	589.42 242	4789.45 229	1298.65 224	7677.31 251	578.35 225	2589.53 237	3611.78 227	923.52 231	913.10 224
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
DPM-MVS		3268.00 214	3762.89 217	1783.33 226	1756.00 229	1806.00 241	12319.00 249	307.00 201	6319.00 243	1557.00 236	5763.00 236	302.00 201	2609.00 239	5061.00 240	482.00 197	935.00 226

OPM-MVS		3268.00 214	3762.89 217	1783.33 226	1756.00 229	1806.00 241	12319.00 249	307.00 201	6319.00 243	1557.00 236	5763.00 236	302.00 201	2609.00 239	5061.00 240	482.00 197	935.00 226
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
TAPA-MVS	6309.84 21	3374.90 216	3806.99 219	2078.63 234	2535.47 251	2499.25 258	8816.16 235	456.05 223	6255.60 242	1664.52 245	6704.88 241	629.95 231	2768.38 244	6343.93 254	856.35 227	968.25 230
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
TSAR-MVS + MP.		3528.01 217	4065.89 224	1914.35 229	2349.10 246	2141.30 250	12362.70 251	417.60 220	6717.80 249	1759.40 246	6497.50 239	518.18 220	2629.38 242	5164.32 242	806.40 224	972.38 231
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
tpm2		3617.85 218	4007.23 220	2449.73 239	2012.71 236	1698.05 235	7351.19 223	869.29 253	6132.06 238	1588.28 238	8007.42 254	1281.09 260	3888.11 258	7472.04 258	1351.00 249	1763.02 255

tpm cat1		3617.85 218	4007.23 220	2449.73 239	2012.71 236	1698.05 235	7351.19 223	869.29 253	6132.06 238	1588.28 238	8007.42 254	1281.09 260	3888.11 258	7472.04 258	1351.00 249	1763.02 255

CostFormer		3617.85 218	4007.23 220	2449.73 239	2012.71 236	1698.05 235	7351.19 223	869.29 253	6132.06 238	1588.28 238	8007.42 254	1281.09 260	3888.11 258	7472.04 258	1351.00 249	1763.02 255

tpm		3617.85 218	4007.23 220	2449.73 239	2012.71 236	1698.05 235	7351.19 223	869.29 253	6132.06 238	1588.28 238	8007.42 254	1281.09 260	3888.11 258	7472.04 258	1351.00 249	1763.02 255

MVS_111021_HR		3742.80 222	4330.34 225	1980.20 231	2484.31 249	2259.52 251	14973.80 256	515.90 240	6500.13 246	1949.21 249	6146.89 238	535.66 223	2593.66 238	4880.76 239	986.37 232	1087.43 240

MAR-MVS		3973.16 223	4387.92 226	2728.86 245	3345.27 262	3341.39 265	11403.90 248	798.76 250	6555.62 248	2569.29 259	6514.86 240	834.97 245	3237.43 255	5891.08 245	1577.54 254	1607.76 247
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
DVP-MVS++.		3981.10 224	4731.32 229	1730.42 224	2191.51 243	1949.98 245	16473.90 258	355.33 207	7172.90 254	1622.98 242	7879.79 252	434.33 213	2428.11 235	5762.12 243	689.04 207	813.18 213

DVP-MVS		3981.10 224	4731.32 229	1730.42 224	2191.51 243	1949.98 245	16473.90 258	355.33 207	7172.90 254	1622.98 242	7879.79 252	434.33 213	2428.11 235	5762.12 243	689.04 207	813.18 213
Zhenlong Yuan, Jinguo Luo, Fei Shen, Zhaoxin Li, Cong Liu, Tianlu Mao, Zhaoqi Wang: DVP-MVS: Synergize Depth-Edge and Visibility Prior for Multi-View Stereo. AAAI2025
GST-MVS		4000.00 226	4533.33 227	2400.00 238	2400.00 248	2400.00 252	7200.00 222	2400.00 269	7200.00 256	2400.00 258	7200.00 246	2400.00 264	2400.00 234	7200.00 256	2400.00 261	2400.00 260

SED-MVS		4062.74 227	4671.13 228	2237.56 235	2643.17 252	2465.14 253	13996.40 253	493.26 228	7619.38 257	2107.24 250	7416.93 248	610.24 228	3088.29 251	6075.14 250	1078.39 243	1159.26 241

MSP-MVS		4296.20 228	4911.12 232	2451.45 243	2725.60 257	2598.35 259	16203.30 257	515.86 236	7016.02 250	2363.85 254	6894.28 242	887.23 246	3023.43 247	5973.88 246	1620.04 255	1732.56 251
Zhenlong Yuan, Cong Liu, Fei Shen, Zhaoxin Li, Jingguo luo, Tianlu Mao and Zhaoqi Wang: MSP-MVS: Multi-granularity Segmentation Prior Guided Multi-View Stereo. AAAI2025
API-MVS		4380.83 229	4906.56 231	2803.67 246	3844.00 263	3116.00 264	13454.00 252	901.00 257	6511.00 247	2794.00 260	7365.00 247	754.00 242	3634.00 256	6622.00 255	1914.00 260	1661.00 250

OMC-MVS		5022.26 230	5748.82 233	2842.58 247	4905.27 265	3101.27 263	14933.60 255	812.24 251	9278.40 261	2959.29 261	8800.17 258	1092.24 258	3806.30 257	7568.54 262	1389.60 253	1620.18 249

CLD-MVS		7338.25 231	8341.00 234	4330.00 248	4902.00 264	4991.00 266	23318.00 261	728.00 249	14437.00 268	4378.00 263	13379.00 263	824.00 244	5708.00 262	11429.00 268	1674.00 259	2291.00 259
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
LS3D		7684.71 232	8776.23 235	4410.16 249	5298.55 266	5631.53 267	34329.90 263	1504.57 267	11554.00 267	3896.41 262	15111.00 264	812.19 243	5985.63 263	3516.20 226	2963.23 262	1613.31 248

ZNCC-MVS		9999.00 233	9999.00 236	9999.00 251	9999.00 269	9999.00 270	9999.00 241	9999.00 273	9999.00 262	9999.00 266	9999.00 259	9999.00 267	9999.00 264	9999.00 263	9999.00 265	9999.00 263

UA-Net		10000.00 234	10000.00 237	10000.00 252	10000.00 270	10000.00 271	10000.00 242	10000.00 274	10000.00 263	10000.00 267	10000.00 260	10000.00 268	10000.00 265	10000.00 264	10000.00 266	10000.00 264

uncertanet		10000.00 234	10000.00 237	10000.00 252	10000.00 270	10000.00 271	10000.00 242	10000.00 274	10000.00 263	10000.00 267	10000.00 260	10000.00 268	10000.00 265	10000.00 264	10000.00 266	10000.00 264

uanet		10000.00 234	10000.00 237	10000.00 252	10000.00 270	10000.00 271	10000.00 242	10000.00 274	10000.00 263	10000.00 267	10000.00 260	10000.00 268	10000.00 265	10000.00 264	10000.00 266	10000.00 264

MVE	10021.00 22	10550.67 237	10002.44 240	12195.33 255	6242.00 267	8768.00 269	30896.00 262	4451.00 270	10331.00 266	6247.00 264	18296.00 265	283.00 198	21484.00 269	7364.00 257	5912.00 264	6334.00 262
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
CNLPA		10738.67 238	11772.44 241	7637.33 250	9120.00 268	8206.00 268	22252.00 260	2010.00 268	24984.00 269	7458.00 265	22596.00 266	2940.00 265	10260.00 268	11100.00 267	3492.00 263	4446.00 261

LTVRE_ROB	20565.47 23	23378.08 239	22805.00 242	25097.33 256	15500.00 273	19201.00 274	42712.00 264	6055.00 271	38388.00 270	16926.00 270	38534.00 267	7071.00 266	35653.00 270	29475.00 269	10584.00 269	20438.00 268
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
MSDG		32606.17 240	34443.44 243	27094.33 257	29249.00 274	25246.00 275	51144.00 265	6705.00 272	42886.00 271	22888.00 271	48534.00 268	13263.00 271	37507.00 271	79298.00 270	16024.00 270	18530.00 267

114514_t		99999.00 241	99999.00 244	99999.00 258	99999.00 275	99999.00 276	99999.00 266	99999.00 277	99999.00 272	99999.00 272	99999.00 269	99999.00 272	99999.00 272	99999.00 271	99999.00 271	99999.00 269

PHI-MVS		99999.00 241	99999.00 244	99999.00 258	99999.00 275	99999.00 276	99999.00 266	99999.00 277	99999.00 272	99999.00 272	99999.00 269	99999.00 272	99999.00 272	99999.00 271	99999.00 271	99999.00 269

MP-MVS-pluss		833433.63 243	1111219.60 249	75.70 133	74.28 136	73.29 139	284.50 137	11.35 131	238.58 143	65.86 137	255.35 150	14.55 130	115.69 153	10000000.00 276	31.94 130	38.12 136
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
zzz-MVS		833442.10 244	1111233.77 250	67.09 127	65.59 134	64.81 137	284.50 137	10000000.00 282	219.97 141	59.62 135	229.89 144	12.72 128	103.00 150	203.67 150	27.93 128	33.46 127

MTAPA		833442.10 244	1111233.77 250	67.09 127	65.59 134	64.81 137	284.50 137	10000000.00 282	219.97 141	59.62 135	229.89 144	12.72 128	103.00 150	203.67 150	27.93 128	33.46 127

XVG-OURS-SEG-HR		999999.00 246	999999.00 246	999999.00 260	999999.00 277	999999.00 278	999999.00 268	999999.00 279	999999.00 274	999999.00 274	999999.00 271	999999.00 274	999999.00 274	999999.00 273	999999.00 273	999999.00 271

XVG-OURS		999999.00 246	999999.00 246	999999.00 260	999999.00 277	999999.00 278	999999.00 268	999999.00 279	999999.00 274	999999.00 274	999999.00 271	999999.00 274	999999.00 274	999999.00 273	999999.00 273	999999.00 271

XVG-ACMP-BASELINE		999999.00 246	999999.00 246	999999.00 260	999999.00 277	999999.00 278	999999.00 268	999999.00 279	999999.00 274	999999.00 274	999999.00 271	999999.00 274	999999.00 274	999999.00 273	999999.00 273	999999.00 271

Anonymous20240521		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

cl-mvsnet2		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

miper_ehance_all_eth		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

miper_enhance_ethall		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

cl-mvsnet____		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

cl-mvsnet1		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

eth_miper_zixun_eth		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

testtj		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

ET-MVSNet_ETH3D		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

UniMVSNet_ETH3D		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

miper_lstm_enhance		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

D2MVS		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

test_yl		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

thisisatest0530		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

Anonymous20240529		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

Anonymous202405211		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

DCV-MVSNet		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

tttt0517		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

our_test_3		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

thisisatest0515		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

ppachtmachnet_test		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

SMA-MVS		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274
Yufeng Yin; Xiaoyan Liu; Zichao Zhang: SMA-MVS: Segmentation-Guided Multi-Scale Anchor Deformation Patch Multi-View Stereo. IEEE Transactions on Circuits and Systems for Video Technology
DPE-MVS		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
test_part1		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

thres100view900		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

tfpnnormal		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

tfpn200view9		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

cl_fuxian		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

IterMVS-SCA-FT		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

pmmvs6		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

pmmvs5		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

Anonymous20231211		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

pmmvs-eth3d		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

Anonymous20231206		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

SCA		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

Patchmatch-test		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

Patchmatch-RL test		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

canonicalmvs		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

anonymousdsp		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

FIs		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

FC-MVSNet-test		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

sosnet-low-res		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

AllTest		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

bset_n11_16_dypcd		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

RRT_MVS		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

HPM-MVS++		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

XVS		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

pm-mvs1		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

X-MVStestdata		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

APDe-MVS		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

APD-MVS_3200maxsize		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

pmmvs4		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

test-LLR		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

TESTMET0.1,1		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

test-mter		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

testgi		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

test20.03		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

thres600view7		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

MP-MVS		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
testmvs		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

thres400		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

test123		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

thres200		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

test0.0.03 1		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

pmmvs3		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

EMVS		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

E-PMN		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

PGM-MVS		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

MCST-MVS		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

MVS_Test		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

PMMVS2		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

PM-MVS		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

HQP_MVS		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

mPP-MVS		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

DWT-MVSNet_test		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

HPM-MVS_fast		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

RRT_test8_iter05		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

HPM-MVS		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
LPG-MVS_test		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

EPNet_dtu		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
EPNet		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CNVR-MVS		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

NCCC		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

CP-MVS		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

CPTT-MVS		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

HQP-MVS		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

IS-MVSNet		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

PAPM_NR		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

PAPR		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

Vis-MVSNet (Re-imp)		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

PatchMatch-RL		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

TDRefinement		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

EPP-MVSNet		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

PMMVS		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

PAPM		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

ACMMP		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274
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
ANet_high		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

wuyk23d		10000000.00 249	10000000.00 252	10000000.00 263	10000000.00 280	10000000.00 281	10000000.00 271	10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

APD-MVS		1000000000.00 347	1000000000.00 350	1000000000.00 363	1000000000.00 388	1000000000.00 387	1000000000.00 374	1000000000.00 388	1000000000.00 381	1000000000.00 382	1000000000.00 379	1000000000.00 384	1000000000.00 382	1000000000.00 380	1000000000.00 380	1000000000.00 378
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
FOURS1					2643.17 252	2465.14 253	13996.40 253	493.26 228	7619.38 257	2107.24 250

MSC_two_6792asdad				2237.56 235	2643.17 252	2465.14 253		493.26 228					3088.29 251	6075.14 250	1078.39 243	1159.26 241

PC_three_1452									7619.38 257	2107.24 250	7416.93 248	610.24 228	3088.29 251	6075.14 250	1078.39 243	1159.26 241

No_MVS				2237.56 235	2643.17 252	2465.14 253		493.26 228					3088.29 251	6075.14 250	1078.39 243	1159.26 241

test_one_0601					2643.17 252	2465.14 253		493.26 228	7619.38 257	2107.24 250	7416.93 248	610.24 228

eth-test2					1.42 66

eth-test					10000000.00 280

ZD-MVS					1584.00 221	1821.00 243		378.00 212	3721.00 219	1231.00 220	1833.00 201	321.00 203	1224.00 213	2103.00 213	692.00 210

RE-MVS-def			610.10 153		610.10 180	610.10 191	610.10 158	610.10 243	610.10 162	610.10 191	610.10 159	610.10 226		610.10 162	610.10 200	610.10 198

IU-MVS					2725.60 257	2598.35 259		515.86 236	7016.02 250	2363.85 254				5973.88 246	1620.04 255	1732.56 251

OPU-MVS				2451.45 243	2725.60 257	2598.35 259	9203.30 237				6894.28 242	887.23 246	3023.43 247	5973.88 246	1620.04 255	1732.56 251

test_241102_TWO								515.86 236	7016.02 250	2363.85 254	6894.28 242	887.23 246	3023.43 247	5973.88 246	1620.04 255	1732.56 251

test_241102_ONE					2725.60 257	2598.35 259		515.86 236	7016.02 250	2363.85 254	6894.28 242	887.23 246	3023.43 247

9.14			0.00 1		0.00 1		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

save fliter					0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

test_0728_THIRD									5016.02 232	1363.85 225	4894.28 230	387.23 210	2023.43 226	3973.88 229	620.04 202	732.56 207

test_0728_SECOND				1451.45 215	1725.60 224	1598.35 227	9203.30 237	315.86 203					2023.43 226	3973.88 229	620.04 202	732.56 207

test0726					1725.60 224	1598.35 227	9203.30 237	315.86 203	5016.02 232	1363.85 225	4894.28 230	387.23 210

GSMVS																10000000.00 274

test_part2					10000000.00 280	10000000.00 281				10000000.00 277

sam_mvs1												10000000.00 277				10000000.00 274

sam_mvs												10000000.00 277

ambc				999.00 197	999.00 206	999.00 210	999.00 165	999.00 258		999.00 206	999.00 173	999.00 251	999.00 202	999.00 182	999.00 235	999.00 232

MTGPA								10000000.00 282

test_post1							10000000.00 271				10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276

test_post											10000000.00 274	10000000.00 277	10000000.00 277

patchmatchnet-post											10000000.00 274	10000000.00 277	10000000.00 277

GG-mvs-BLEND				596.01 180	611.29 182	600.33 188	790.30 161	513.12 234		552.71 184	567.40 154	662.54 238	531.67 170	503.93 156	779.80 217	656.02 201

MTMP							10000000.00 271	10000000.00 282

gm-plane-assit					611.29 182	600.33 188			579.21 158		567.40 154		531.67 170	503.93 156

test9_res														0.00 1	0.00 1	0.00 1

TEST9					0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

test_8					0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

agg_prior2														0.00 1	0.00 1	0.00 1

agg_prior					0.00 1	0.00 1		0.00 1		0.00 1			0.00 1

TestCases				10000000.00 263	10000000.00 280	10000000.00 281		10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

test_prior4						0.00 1	0.00 1

test_prior2							0.00 1		0.00 1	0.00 1	0.00 1	0.00 1		0.00 1	0.00 1

test_prior				0.00 1	0.00 1	0.00 1		0.00 1					0.00 1			0.00 1

旧先验2							0.00 1		0.00 1	0.00 1			0.00 1	0.00 1

新几何2							0.00 1

新几何1				0.00 1	0.00 1	0.00 1		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

旧先验1					0.00 1	0.00 1		0.00 1			0.00 1	0.00 1			0.00 1	0.00 1

无先验							0.00 1	0.00 1	0.00 1				0.00 1	0.00 1		0.00 1

原ACMM2							0.00 1

原ACMM1				0.00 1	0.00 1	0.00 1		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

test222					0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1			0.00 1	0.00 1

testdata2													0.00 1	0.00 1

segment_acmp												0.00 1

testdata				0.00 1	0.00 1	0.00 1		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

testdata1							0.00 1		0.00 1

test12				0.00 1	0.00 1	0.00 1		0.00 1		0.00 1		0.00 1	0.00 1		0.00 1	0.00 1

plane_prior7					10000000.00 280	10000000.00 281

plane_prior6					10000000.00 280	10000000.00 281						10000000.00 277

plane_prior5								10000000.00 282					10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

plane_prior4											10000000.00 274

plane_prior3						10000000.00 281			10000000.00 277	10000000.00 277

plane_prior2							10000000.00 271		10000000.00 277

plane_prior1					10000000.00 280

plane_prior						1.00 60	2.00 92		2.00 93						2.00 91

n2								14.20 134

nn								1.42 68

door-mid								1.42 68

lessismore_v0				569.20 178	667.25 195	644.68 194		96.45 166		428.86 171	1514.17 197	204.21 191	756.58 191	1061.60 191	197.79 169	306.34 180

LGP-MVS_train				10000000.00 263	10000000.00 280	10000000.00 281		10000000.00 282	10000000.00 277	10000000.00 277	10000000.00 274	10000000.00 277	10000000.00 277	10000000.00 276	10000000.00 276	10000000.00 274

test11								1.00 61

door								99.00 168

HQP5-MVS						10000000.00 281

HQP-NCC					10000000.00 280		10000000.00 271		10000000.00 277	10000000.00 277

ACMP_Plane					10000000.00 280		10000000.00 271		10000000.00 277	10000000.00 277

BP-MVS														10000000.00 276

HQP4-MVS										10000000.00 277			10000000.00 277			10000000.00 274

HQP3-MVS								10000000.00 282							10000000.00 276

HQP2-MVS												10000000.00 277

NP-MVS					10000000.00 280	10000000.00 281					10000000.00 274

MDTV_nov1_ep13_2view						9.99 114	9.99 112		9.99 113	9.99 112		9.99 114		9.99 110		9.99 113

MDTV_nov1_ep13			9.99 100		9.99 113	9.99 114	9.99 112	9.99 120	9.99 113	9.99 112	9.99 109	9.99 114	9.99 113	9.99 110	9.99 114

ACMMP++_ref															10000000.00 276

ACMMP++															10000000.00 276

Test By Simon												990.00 250

ITE_SJBPF				2014.00 233	1998.00 235	1992.00 247		701.00 248	5989.00 237	1812.00 248	3612.00 219	650.00 232	2852.00 245	4601.00 238	1195.00 248	1198.00 245

DeepMVS_CX				1.00 53	1.00 60	1.00 60		1.00 61	1.00 60	1.00 59	1.00 57	1.00 59	1.00 60	1.00 58	1.00 58	1.00 58

High-resolution multi-view benchmark