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

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

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

h-mvs33		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_self_test		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

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

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+-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

KD-MVS_self_test		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

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

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

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

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	40.00 153	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	40.00 153	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	40.00 153	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	40.00 153	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

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	68.71 151	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	68.71 151	51.38 149

dp		87.20 118	113.80 122	7.42 105	10.50 124	8.88 113	298.82 141	2.70 106	510.35 159	7.79 111	172.93 132	3.37 101	9.16 112	14.00 123	3.71 101	4.23 101

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	45.00 158	335.00 155	99.00 153	251.00 149	38.00 149	110.00 152	120.00 135	99.00 155	98.00 154

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

FE-MVS		207.10 137	234.26 139	125.61 147	180.34 155	153.23 157	635.64 160	30.05 152	378.38 156	127.68 154	377.08 152	48.95 154	154.43 155	266.67 153	63.56 150	69.18 151

test1172		216.26 138	257.16 140	93.57 145	310.10 161	111.10 156	31.10 126	45.10 159	192.73 136	176.39 156	512.31 155	66.33 158	78.35 135	891.20 179	89.18 154	91.27 153

FA-MVS(test-final)		261.15 139	293.29 141	164.72 148	236.23 158	199.99 160	800.05 165	42.35 157	475.87 158	155.47 155	470.67 154	58.49 155	205.24 157	319.44 154	81.03 153	88.93 152

DP-MVS		264.78 140	296.02 142	171.04 149	191.70 156	183.96 158	827.10 166	78.36 160	438.24 157	176.64 157	435.12 153	65.04 157	230.52 159	334.02 155	117.96 156	98.64 155

tmp_tt		371.08 141	412.78 143	246.00 151	231.00 157	197.00 159	1293.00 178	376.00 213	756.00 168	609.00 192	71.00 128	106.00 167	195.00 156	102.00 134	171.00 165	346.00 188

RPSCF		394.81 142	445.63 144	242.35 150	276.55 160	253.63 161	1207.27 176	90.69 165	715.56 166	241.57 159	684.87 163	111.96 168	320.02 160	548.38 162	133.81 157	153.39 157

ADS-MVSNet2		443.33 144	482.84 145	324.79 159	434.94 172	387.73 169	1110.57 174	87.69 163	887.02 172	282.92 160	779.29 165	98.57 165	422.76 168	502.40 156	162.19 163	163.87 158

ADS-MVSNet		443.33 144	482.84 145	324.79 159	434.94 172	387.73 169	1110.57 174	87.69 163	887.02 172	282.92 160	779.29 165	98.57 165	422.76 168	502.40 156	162.19 163	163.87 158

EG-PatchMatch MVS		437.03 143	493.12 147	268.77 152	264.80 159	260.20 162	1491.80 181	98.00 169	723.20 167	238.80 158	722.40 164	63.10 156	382.00 163	629.00 166	207.00 172	164.10 160

MVP-Stereo		473.58 146	533.67 148	293.33 153	376.00 165	318.00 163	1461.00 179	96.00 166	835.00 170	290.00 163	804.00 168	97.00 163	383.00 165	688.00 173	156.00 158	179.00 162
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
MS-PatchMatch		473.58 146	533.67 148	293.33 153	376.00 165	318.00 163	1461.00 179	96.00 166	835.00 170	290.00 163	804.00 168	97.00 163	383.00 165	688.00 173	156.00 158	179.00 162

PatchmatchNet		492.52 148	551.22 150	316.40 157	400.20 168	357.90 167	1277.10 177	115.80 174	1034.60 182	315.90 165	874.00 171	155.10 173	402.20 167	629.50 167	158.80 160	189.10 164
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
tpmvs		501.65 149	567.42 151	304.33 156	395.39 167	356.32 166	1512.04 182	216.53 200	994.15 175	350.16 168	804.16 170	119.38 169	380.98 162	555.14 163	159.87 161	175.69 161

DP-MVS Recon		516.25 151	581.17 152	321.48 158	361.02 163	429.00 173	1995.36 187	78.48 161	796.20 169	283.32 162	796.02 167	96.78 162	382.98 164	636.72 168	186.66 169	152.46 156

DELS-MVS		514.57 150	587.73 153	295.12 155	343.03 162	328.09 165	1540.48 183	116.22 175	988.59 174	325.44 166	906.22 172	119.86 170	365.72 161	788.60 175	161.09 162	191.55 165
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
gg-mvs-nofinetune		594.69 152	605.37 154	562.67 179	617.29 188	500.33 177	772.30 161	413.12 221	579.21 160	552.71 186	567.40 156	662.54 241	531.67 172	503.93 158	779.80 219	656.02 203

RE-MVS-def			610.10 155		610.10 182	610.10 193	610.10 158	610.10 245	610.10 164	610.10 193	610.10 161	610.10 229		610.10 164	610.10 202	610.10 200

SR-MVS		610.10 153	610.10 155	610.10 184	610.10 182	610.10 193	610.10 158	610.10 245	610.10 164	610.10 193	610.10 161	610.10 229	610.10 187	610.10 164	610.10 202	610.10 200

CR-MVSNet		612.36 154	617.81 157	596.01 182	611.29 184	600.33 190	790.30 162	513.12 236	579.21 160	552.71 186	567.40 156	662.54 241	531.67 172	503.93 158	779.80 219	656.02 203

IterMVS		615.05 155	691.66 158	385.23 163	516.40 175	454.80 174	1863.80 185	102.10 171	1142.20 184	364.10 169	1093.20 186	135.00 171	480.40 171	826.90 176	181.20 166	220.50 167
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
IB-MVS	872.44 4	616.41 156	700.96 159	362.78 161	426.10 171	409.25 171	1822.69 184	124.42 183	1186.23 185	366.85 170	1079.42 184	190.60 186	451.78 170	930.72 181	181.59 167	227.30 168
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	661.38 157	754.00 160	383.51 162	368.96 164	376.38 168	2483.74 199	82.42 162	1089.25 183	333.39 167	1219.68 187	66.53 159	573.60 184	957.86 182	184.14 168	200.56 166

Gipuma		689.75 158	767.00 161	458.00 171	613.00 187	549.00 188	1943.00 186	187.00 197	1230.00 186	518.00 183	1092.00 185	203.00 192	564.00 177	892.00 180	225.00 181	261.00 175
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
RPMNet		787.26 168	829.13 162	661.63 188	885.90 203	895.90 210	455.98 156	610.10 245	1297.17 187	1002.26 215	1001.67 182	655.98 239	611.10 188	667.90 170	885.21 231	477.90 197

JIA-IIPM		804.30 169	835.64 163	710.26 193	885.90 203	895.90 210	455.98 156	668.73 250	1297.17 187	1002.26 215	1001.67 182	655.98 239	756.98 194	667.90 170	885.21 231	477.90 197

IterMVS-LS		758.94 159	856.56 164	466.10 172	606.60 180	546.80 186	2309.90 189	122.20 182	1402.80 190	463.50 174	1348.20 189	192.60 187	574.60 185	1028.60 192	234.60 183	276.90 177
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
new-patchmatchnet		766.12 160	859.03 165	487.38 175	595.68 177	536.14 179	2346.27 190	142.51 188	1488.08 192	422.43 171	1361.32 191	163.65 176	628.60 189	1003.74 191	207.61 173	297.41 181

PatchT		856.34 172	860.99 166	842.38 198	1290.90 218	880.90 208	790.30 162	1267.30 268	579.21 160	923.90 205	567.40 156	662.54 241	990.23 202	887.56 178	779.80 219	656.02 203

SixPastTwentyTwo		773.62 161	869.37 167	486.35 174	603.45 179	547.15 187	2532.14 200	106.92 173	1434.95 191	428.08 172	1360.56 190	165.15 177	628.96 190	984.09 183	209.01 174	282.94 178

mvs_anonymous		774.90 162	882.28 168	452.77 165	636.50 189	537.20 180	2348.80 191	120.30 176	1504.30 193	474.40 175	1371.10 192	186.90 179	564.70 178	1078.90 194	219.30 175	256.40 169

casdiffmvs		774.90 162	882.28 168	452.77 165	636.50 189	537.20 180	2348.80 191	120.30 176	1504.30 193	474.40 175	1371.10 192	186.90 179	564.70 178	1078.90 194	219.30 175	256.40 169

diffmvs		774.90 162	882.28 168	452.77 165	636.50 189	537.20 180	2348.80 191	120.30 176	1504.30 193	474.40 175	1371.10 192	186.90 179	564.70 178	1078.90 194	219.30 175	256.40 169

baseline2		774.90 162	882.28 168	452.77 165	636.50 189	537.20 180	2348.80 191	120.30 176	1504.30 193	474.40 175	1371.10 192	186.90 179	564.70 178	1078.90 194	219.30 175	256.40 169

baseline1		774.90 162	882.28 168	452.77 165	636.50 189	537.20 180	2348.80 191	120.30 176	1504.30 193	474.40 175	1371.10 192	186.90 179	564.70 178	1078.90 194	219.30 175	256.40 169

baseline		774.90 162	882.28 168	452.77 165	636.50 189	537.20 180	2348.80 191	120.30 176	1504.30 193	474.40 175	1371.10 192	186.90 179	564.70 178	1078.90 194	219.30 175	256.40 169

PVSNet	1207.94 6	829.56 171	937.18 174	506.69 176	645.55 195	585.72 189	2477.98 198	130.52 184	1578.29 200	509.50 182	1460.01 198	194.90 188	637.19 191	1170.78 201	267.07 187	297.17 180

CSCG		826.03 170	963.29 175	414.24 164	421.52 170	426.11 172	2230.35 188	179.52 196	1827.44 204	733.43 203	933.12 174	281.25 199	545.23 176	1800.35 210	262.64 185	271.38 176

K. test v3		877.74 173	980.16 176	570.46 181	1316.85 220	813.15 205	2565.52 201	103.78 172	1509.49 199	548.33 185	1258.90 188	219.93 197	587.82 186	1102.37 200	196.30 170	310.42 183

OurMVSNet-221017-0		999.00 178	999.00 177	999.00 199	999.00 208	999.00 212	999.00 167	999.00 261	999.00 176	999.00 208	999.00 175	999.00 254	999.00 204	999.00 184	999.00 238	999.00 235

EPMVS		999.00 178	999.00 177	999.00 199	999.00 208	999.00 212	999.00 167	999.00 261	999.00 176	999.00 208	999.00 175	999.00 254	999.00 204	999.00 184	999.00 238	999.00 235

uanet_test		1000.00 180	1000.00 179	1000.00 202	1000.00 211	1000.00 215	1000.00 170	1000.00 264	1000.00 178	1000.00 211	1000.00 178	1000.00 257	1000.00 207	1000.00 187	1000.00 241	1000.00 238

sosnet		1000.00 180	1000.00 179	1000.00 202	1000.00 211	1000.00 215	1000.00 170	1000.00 264	1000.00 178	1000.00 211	1000.00 178	1000.00 257	1000.00 207	1000.00 187	1000.00 241	1000.00 238

USDC		1000.00 180	1000.00 179	1000.00 202	1000.00 211	1000.00 215	1000.00 170	1000.00 264	1000.00 178	1000.00 211	1000.00 178	1000.00 257	1000.00 207	1000.00 187	1000.00 241	1000.00 238

TinyColmap		1000.00 180	1000.00 179	1000.00 202	1000.00 211	1000.00 215	1000.00 170	1000.00 264	1000.00 178	1000.00 211	1000.00 178	1000.00 257	1000.00 207	1000.00 187	1000.00 241	1000.00 238

MVSTER		890.06 174	1005.91 183	542.52 177	736.13 200	653.90 197	2616.56 202	145.22 190	1692.10 203	555.69 189	1554.72 200	266.25 198	660.02 192	1219.66 202	266.84 186	313.64 184

PMVS	863.65 3	957.08 175	1054.11 184	666.00 190	401.00 169	495.00 176	3790.00 207	279.00 202	1607.00 202	521.00 184	1745.00 202	90.00 160	1105.00 213	639.00 169	415.00 198	398.00 195
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
PVSNet_0	1661.03 9	968.54 177	1066.82 185	673.70 191	706.94 198	695.69 198	2669.02 203	153.52 192	2108.17 209	605.54 191	1679.14 201	213.26 196	886.75 199	1236.76 203	229.01 182	438.67 196

ACMH	993.80 5	967.92 176	1106.11 186	553.33 178	494.00 174	534.00 178	3581.00 205	136.00 185	1585.00 201	478.00 181	1871.00 204	90.00 160	839.00 196	1460.00 204	260.00 184	287.00 179
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
Patchmtry		1090.75 185	1198.88 187	766.38 197	1290.90 218	485.90 175	2423.98 197	1267.30 268	1297.17 187	923.90 205	923.40 173	1215.54 262	990.23 202	667.90 170	779.80 219	823.02 217

ACMP	1246.57 7	1086.24 184	1235.17 188	639.45 185	596.53 178	639.91 195	3904.24 208	152.04 191	1851.54 205	566.58 190	1997.95 206	138.50 172	938.30 200	1605.46 206	303.70 193	340.14 186
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
test_0402		1110.00 186	1260.00 189	660.00 187	900.00 206	780.00 204	3300.00 204	210.00 199	2040.00 208	690.00 198	1950.00 205	300.00 202	810.00 195	1620.00 207	330.00 194	390.00 194

MVS_111021_LR		1136.45 187	1298.72 190	649.64 186	756.17 201	726.26 201	3785.94 206	138.15 187	2190.64 210	629.63 196	2064.39 207	165.45 178	874.83 198	1678.43 209	279.70 188	347.82 189

ACMM	1311.08 8	1165.06 188	1332.72 191	662.07 189	584.90 176	715.99 200	4373.59 212	153.99 193	1880.27 206	709.02 200	2316.97 208	188.63 185	939.89 201	1484.30 205	302.78 192	330.34 185
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
MSLP-MVS++		1242.93 189	1411.08 192	738.48 195	712.71 199	712.68 199	4168.17 210	136.50 186	2276.40 211	613.28 195	2368.60 211	161.61 175	1130.38 214	1964.54 213	297.88 190	372.39 191

MG-MVS		1256.50 190	1432.00 193	730.00 194	610.00 181	760.00 202	4720.00 213	169.00 194	1920.00 207	723.00 202	2510.00 214	201.00 190	1050.00 211	1645.00 208	390.00 197	380.00 192

ACMMPR		1296.60 191	1480.82 194	743.96 196	899.25 205	763.47 203	4305.47 211	143.90 189	2530.94 214	683.99 197	2346.34 210	201.65 191	1098.25 212	1920.59 212	295.21 189	370.16 190

FPMVS		1407.00 193	1495.59 195	1141.23 207	648.01 196	893.85 209	4124.00 209	503.81 235	3219.04 217	742.72 204	2498.84 213	157.98 174	1727.83 220	832.93 177	732.98 218	802.00 212

TSAR-MVS + GP.		1386.84 192	1622.84 196	678.81 192	952.13 207	840.17 207	5358.21 216	170.75 195	2650.47 215	713.54 201	2394.28 212	209.42 195	855.56 197	1854.36 211	302.42 191	340.71 187

COLMAP_ROB	2144.59 11	1658.33 195	1869.33 197	1025.33 206	1030.00 215	1023.00 219	5311.00 215	359.00 211	3044.00 216	937.00 207	2892.00 215	332.00 206	1440.00 217	2312.00 216	607.00 201	613.00 202
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
DeepC-MVS_fast	2190.19 12	1535.59 194	1886.82 198	481.89 173	847.73 202	830.16 206	7943.84 232	189.23 198	2398.83 212	691.73 199	2341.13 209	209.16 194	230.25 158	1999.25 214	360.46 195	385.25 193
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
F-COLMAP		1878.17 196	2113.11 199	1173.33 210	1231.00 216	1174.00 220	6297.00 218	392.00 216	3356.00 219	1087.00 217	3082.00 216	361.00 210	1670.00 219	2523.00 218	689.00 208	676.00 207

CMPMVS	2623.62 15	1983.08 198	2156.14 200	1463.89 220	1414.80 222	1517.00 225	5239.20 214	867.40 255	3310.30 218	1128.70 219	3489.90 218	366.75 211	2030.20 231	2427.60 217	1160.60 250	844.46 220
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
OpenMVS_ROB	1936.51 10	1959.51 197	2224.88 201	1163.39 209	1253.91 217	1434.22 223	7065.71 222	272.76 201	2472.29 213	1647.54 247	3538.72 219	200.37 189	1496.48 218	2575.17 219	997.45 237	559.48 199

MVS-HIRNet		2125.39 199	2452.68 202	1143.53 208	2938.33 263	1446.92 224	6083.19 217	391.74 215	3801.71 222	1202.10 221	3439.72 217	492.73 220	1304.35 216	3048.25 223	676.32 207	679.32 208

PLC	2858.82 16	2192.92 200	2474.00 203	1349.67 212	1407.00 221	1356.00 222	7164.00 223	475.00 228	3970.00 223	1237.00 224	3765.00 222	451.00 217	1891.00 225	3006.00 222	791.00 224	802.00 212
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
OpenMVS	2352.88 13	2263.08 201	2530.89 204	1459.67 219	1767.00 233	1591.00 228	7932.00 231	399.00 217	3643.00 220	1176.00 220	3569.00 220	297.00 201	1927.00 227	3302.00 224	693.00 213	861.00 221

PCF-MVS	4335.85 20	2272.23 202	2597.03 205	1297.84 211	1701.20 225	1332.37 221	8105.11 233	451.45 224	4031.84 224	1099.10 218	3966.50 223	467.45 218	1734.05 221	2701.68 221	848.94 228	827.11 218
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
CHOSEN 280x420		2340.81 203	2643.03 206	1434.14 213	2025.55 242	1629.36 232	6542.40 219	412.49 218	4219.70 226	1547.02 235	4328.52 225	650.74 236	1798.26 222	3333.17 225	727.72 215	874.79 222

CHOSEN 1792x2688		2340.81 203	2643.03 206	1434.14 213	2025.55 242	1629.36 232	6542.40 219	412.49 218	4219.70 226	1547.02 235	4328.52 225	650.74 236	1798.26 222	3333.17 225	727.72 215	874.79 222

HyFIR lowres test		2340.81 203	2643.03 206	1434.14 213	2025.55 242	1629.36 232	6542.40 219	412.49 218	4219.70 226	1547.02 235	4328.52 225	650.74 236	1798.26 222	3333.17 225	727.72 215	874.79 222

3Dnovator	2482.06 14	2531.17 206	2839.56 209	1606.00 221	1732.00 229	1557.00 227	8375.00 235	483.00 229	4370.00 229	1371.00 230	4200.00 224	350.00 208	2207.00 232	3877.00 231	798.00 225	1054.00 242

tpmrst		2557.50 207	2847.12 210	1688.66 224	1784.08 234	1778.25 242	7445.50 229	342.14 208	4471.54 230	1534.55 234	4382.10 228	530.10 224	2361.21 235	4142.81 235	991.22 236	926.51 227

AdaColmap		2570.77 208	2948.61 211	1437.24 216	1873.64 235	1526.60 226	7819.77 230	373.97 212	4970.45 233	1479.29 232	4648.46 230	525.80 223	1904.97 226	4150.42 236	695.69 214	880.14 225

DeepPCF-MVS	3452.42 18	2670.71 210	3021.57 212	1618.12 222	2377.67 249	1751.39 241	8915.70 238	567.44 243	4569.74 231	1236.84 223	4615.63 229	513.23 221	2291.32 233	3515.48 228	882.39 230	811.66 214

LF4IMVS		2699.50 211	3049.67 213	1649.00 223	1755.00 230	1689.00 236	8330.00 234	464.00 226	4997.00 234	1528.00 233	4763.00 232	568.00 227	2296.00 234	4215.00 237	827.00 227	962.00 232

SD-MVS		2654.53 209	3055.56 214	1451.45 217	1725.60 226	1598.35 229	9203.30 239	315.86 205	5016.02 235	1363.85 227	4894.28 233	387.23 212	2023.43 228	3973.88 232	620.04 204	732.56 209
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
EGC-MVSNET		2819.75 212	3096.89 215	1988.33 234	3105.00 264	2241.00 253	9480.00 243	640.00 249	4209.00 225	1583.00 240	4740.00 231	547.00 226	2797.00 247	2644.00 220	924.00 234	927.00 228

Vis-MVSNet		2877.42 213	3170.00 216	1999.67 235	1673.00 224	2042.00 251	8593.00 236	474.00 227	6452.00 248	1268.00 225	5125.00 236	339.00 207	3004.00 249	4222.00 238	384.00 196	953.00 231
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
SteuartSystems-ACMMP		2891.50 214	3284.78 217	1711.67 225	1954.00 236	1655.00 235	10117.00 252	445.00 223	5102.00 238	1375.00 231	5126.00 237	351.00 209	2638.00 245	4402.00 239	691.00 211	842.00 219
Skip Steuart: Steuart Systems R&D Blog.
3Dnovator+	3414.41 17	3146.67 215	3537.00 218	1975.67 232	2310.00 247	2005.00 250	10100.00 251	626.00 248	5753.00 239	1803.00 250	5179.00 238	487.00 219	2622.00 243	4550.00 240	1025.00 245	1300.00 249

DeepC-MVS	3917.13 19	3155.06 216	3601.83 219	1814.72 230	2515.52 252	1941.53 246	10432.50 253	589.42 244	4789.45 232	1298.65 226	7677.31 254	578.35 228	2589.53 239	3611.78 230	923.52 233	913.10 226
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
DPM-MVS		3268.00 217	3762.89 220	1783.33 228	1756.00 231	1806.00 243	12319.00 255	307.00 203	6319.00 246	1557.00 238	5763.00 239	302.00 203	2609.00 241	5061.00 243	482.00 199	935.00 229

OPM-MVS		3268.00 217	3762.89 220	1783.33 228	1756.00 231	1806.00 243	12319.00 255	307.00 203	6319.00 246	1557.00 238	5763.00 239	302.00 203	2609.00 241	5061.00 243	482.00 199	935.00 229
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
TAPA-MVS	6309.84 21	3374.90 219	3806.99 222	2078.63 237	2535.47 253	2499.25 261	8816.16 237	456.05 225	6255.60 245	1664.52 248	6704.88 244	629.95 234	2768.38 246	6343.93 257	856.35 229	968.25 233
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
tpm2		3617.85 221	4007.23 223	2449.73 242	2012.71 238	1698.05 237	7351.19 225	869.29 256	6132.06 241	1588.28 241	8007.42 257	1281.09 263	3888.11 261	7472.04 261	1351.00 252	1763.02 258

tpm cat1		3617.85 221	4007.23 223	2449.73 242	2012.71 238	1698.05 237	7351.19 225	869.29 256	6132.06 241	1588.28 241	8007.42 257	1281.09 263	3888.11 261	7472.04 261	1351.00 252	1763.02 258

CostFormer		3617.85 221	4007.23 223	2449.73 242	2012.71 238	1698.05 237	7351.19 225	869.29 256	6132.06 241	1588.28 241	8007.42 257	1281.09 263	3888.11 261	7472.04 261	1351.00 252	1763.02 258

tpm		3617.85 221	4007.23 223	2449.73 242	2012.71 238	1698.05 237	7351.19 225	869.29 256	6132.06 241	1588.28 241	8007.42 257	1281.09 263	3888.11 261	7472.04 261	1351.00 252	1763.02 258

TSAR-MVS + MP.		3528.01 220	4065.89 227	1914.35 231	2349.10 248	2141.30 252	12362.70 257	417.60 222	6717.80 252	1759.40 249	6497.50 242	518.18 222	2629.38 244	5164.32 245	806.40 226	972.38 234
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
MVS_111021_HR		3742.80 225	4330.34 228	1980.20 233	2484.31 251	2259.52 254	14973.80 262	515.90 242	6500.13 249	1949.21 252	6146.89 241	535.66 225	2593.66 240	4880.76 242	986.37 235	1087.43 243

MAR-MVS		3973.16 226	4387.92 229	2728.86 248	3345.27 265	3341.39 268	11403.90 254	798.76 253	6555.62 251	2569.29 262	6514.86 243	834.97 248	3237.43 258	5891.08 248	1577.54 257	1607.76 250
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
GST-MVS		4000.00 229	4533.33 230	2400.00 241	2400.00 250	2400.00 255	7200.00 224	2400.00 272	7200.00 259	2400.00 261	7200.00 249	2400.00 267	2400.00 236	7200.00 259	2400.00 264	2400.00 263

SED-MVS		4062.74 230	4671.13 231	2237.56 238	2643.17 254	2465.14 256	13996.40 259	493.26 230	7619.38 260	2107.24 253	7416.93 251	610.24 231	3088.29 254	6075.14 253	1078.39 246	1159.26 244

DVP-MVS++		3981.10 227	4731.32 232	1730.42 226	2191.51 245	1949.98 247	16473.90 264	355.33 209	7172.90 257	1622.98 245	7879.79 255	434.33 215	2428.11 237	5762.12 246	689.04 209	813.18 215

DVP-MVS		3981.10 227	4731.32 232	1730.42 226	2191.51 245	1949.98 247	16473.90 264	355.33 209	7172.90 257	1622.98 245	7879.79 255	434.33 215	2428.11 237	5762.12 246	689.04 209	813.18 215
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
API-MVS		4380.83 232	4906.56 234	2803.67 249	3844.00 266	3116.00 267	13454.00 258	901.00 260	6511.00 250	2794.00 263	7365.00 250	754.00 245	3634.00 259	6622.00 258	1914.00 263	1661.00 253

MSP-MVS		4296.20 231	4911.12 235	2451.45 246	2725.60 259	2598.35 262	16203.30 263	515.86 238	7016.02 253	2363.85 257	6894.28 245	887.23 249	3023.43 250	5973.88 249	1620.04 258	1732.56 254
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
OMC-MVS		5022.26 233	5748.82 236	2842.58 250	4905.27 268	3101.27 266	14933.60 261	812.24 254	9278.40 264	2959.29 264	8800.17 261	1092.24 261	3806.30 260	7568.54 265	1389.60 256	1620.18 252

CLD-MVS		7338.25 234	8341.00 237	4330.00 251	4902.00 267	4991.00 269	23318.00 267	728.00 252	14437.00 274	4378.00 266	13379.00 269	824.00 247	5708.00 265	11429.00 274	1674.00 262	2291.00 262
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
LS3D		7684.71 235	8776.23 238	4410.16 252	5298.55 269	5631.53 270	34329.90 269	1504.57 270	11554.00 273	3896.41 265	15111.00 270	812.19 246	5985.63 266	3516.20 229	2963.23 265	1613.31 251

ZNCC-MVS		9999.00 236	9999.00 239	9999.00 254	9999.00 272	9999.00 273	9999.00 244	9999.00 276	9999.00 265	9999.00 269	9999.00 262	9999.00 270	9999.00 267	9999.00 266	9999.00 268	9999.00 266

patch_mono-2		10000.00 237	10000.00 240	10000.00 255	10000.00 273	10000.00 274	10000.00 245	10000.00 277	10000.00 266	10000.00 270	10000.00 263	10000.00 271	10000.00 268	10000.00 267	10000.00 269	10000.00 267

dcpmvs_2		10000.00 237	10000.00 240	10000.00 255	10000.00 273	10000.00 274	10000.00 245	10000.00 277	10000.00 266	10000.00 270	10000.00 263	10000.00 271	10000.00 268	10000.00 267	10000.00 269	10000.00 267

DCPMVS		10000.00 237	10000.00 240	10000.00 255	10000.00 273	10000.00 274	10000.00 245	10000.00 277	10000.00 266	10000.00 270	10000.00 263	10000.00 271	10000.00 268	10000.00 267	10000.00 269	10000.00 267

UA-Net		10000.00 237	10000.00 240	10000.00 255	10000.00 273	10000.00 274	10000.00 245	10000.00 277	10000.00 266	10000.00 270	10000.00 263	10000.00 271	10000.00 268	10000.00 267	10000.00 269	10000.00 267

uncertanet		10000.00 237	10000.00 240	10000.00 255	10000.00 273	10000.00 274	10000.00 245	10000.00 277	10000.00 266	10000.00 270	10000.00 263	10000.00 271	10000.00 268	10000.00 267	10000.00 269	10000.00 267

uanet		10000.00 237	10000.00 240	10000.00 255	10000.00 273	10000.00 274	10000.00 245	10000.00 277	10000.00 266	10000.00 270	10000.00 263	10000.00 271	10000.00 268	10000.00 267	10000.00 269	10000.00 267

MVE	10021.00 22	10550.67 243	10002.44 246	12195.33 261	6242.00 270	8768.00 272	30896.00 268	4451.00 273	10331.00 272	6247.00 267	18296.00 271	283.00 200	21484.00 275	7364.00 260	5912.00 267	6334.00 265
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
CNLPA		10738.67 244	11772.44 247	7637.33 253	9120.00 271	8206.00 271	22252.00 266	2010.00 271	24984.00 275	7458.00 268	22596.00 272	2940.00 268	10260.00 274	11100.00 273	3492.00 266	4446.00 264

LTVRE_ROB	20565.47 23	23378.08 245	22805.00 248	25097.33 262	15500.00 279	19201.00 280	42712.00 270	6055.00 274	38388.00 276	16926.00 276	38534.00 273	7071.00 269	35653.00 276	29475.00 275	10584.00 275	20438.00 274
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		32606.17 246	34443.44 249	27094.33 263	29249.00 280	25246.00 281	51144.00 271	6705.00 275	42886.00 277	22888.00 277	48534.00 274	13263.00 277	37507.00 277	79298.00 276	16024.00 276	18530.00 273

114514_t		99999.00 247	99999.00 250	99999.00 264	99999.00 281	99999.00 282	99999.00 272	99999.00 283	99999.00 278	99999.00 278	99999.00 275	99999.00 278	99999.00 278	99999.00 277	99999.00 277	99999.00 275

PHI-MVS		99999.00 247	99999.00 250	99999.00 264	99999.00 281	99999.00 282	99999.00 272	99999.00 283	99999.00 278	99999.00 278	99999.00 275	99999.00 278	99999.00 278	99999.00 277	99999.00 277	99999.00 275

XVG-OURS-SEG-HR		999999.00 252	999999.00 252	999999.00 266	999999.00 283	999999.00 284	999999.00 274	999999.00 285	999999.00 280	999999.00 280	999999.00 277	999999.00 280	999999.00 280	999999.00 279	999999.00 279	999999.00 277

XVG-OURS		999999.00 252	999999.00 252	999999.00 266	999999.00 283	999999.00 284	999999.00 274	999999.00 285	999999.00 280	999999.00 280	999999.00 277	999999.00 280	999999.00 280	999999.00 279	999999.00 279	999999.00 277

XVG-ACMP-BASELINE		999999.00 252	999999.00 252	999999.00 266	999999.00 283	999999.00 284	999999.00 274	999999.00 285	999999.00 280	999999.00 280	999999.00 277	999999.00 280	999999.00 280	999999.00 279	999999.00 279	999999.00 277

MP-MVS-pluss		833433.63 249	1111219.60 255	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	10000000.00 282	31.94 130	38.12 136
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
zzz-MVS		833442.10 250	1111233.77 256	67.09 127	65.59 134	64.81 137	284.50 137	10000000.00 288	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		833442.10 250	1111233.77 256	67.09 127	65.59 134	64.81 137	284.50 137	10000000.00 288	219.97 141	59.62 135	229.89 144	12.72 128	103.00 150	203.67 150	27.93 128	33.46 127

iter_conf_final		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

bld_raw_dy_0_64		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

test2506		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

test1111		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

ECVR-MVS		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

test_blank		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

Anonymous20240521		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

cl22		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

miper_ehance_all_eth		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

miper_enhance_ethall		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

cl____		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

DIV-MVS_self_test		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

eth_miper_zixun_eth		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

testtj		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

ET-MVSNet_ETH3D		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

UniMVSNet_ETH3D		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

miper_lstm_enhance		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

D2MVS		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

test_yl		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

thisisatest0530		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

Anonymous20240529		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

Anonymous202405211		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

DCV-MVSNet		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

tttt0517		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

our_test_3		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

thisisatest0515		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

ppachtmachnet_test		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

SMA-MVS		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280
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		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
test_part1		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

thres100view900		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

tfpnnormal		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

tfpn200view9		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

c3_l		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

IterMVS-SCA-FT		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

pmmvs6		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

pmmvs5		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

Anonymous20231211		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

pmmvs-eth3d		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

Anonymous20231206		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

SCA		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

Patchmatch-test		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

Patchmatch-RL test		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

canonicalmvs		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

anonymousdsp		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

FIs		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

FC-MVSNet-test		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

sosnet-low-res		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

AllTest		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

iter_conf05		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

RRT_MVS		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

HPM-MVS++		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

XVS		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

pm-mvs1		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

X-MVStestdata		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

APDe-MVS		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

APD-MVS_3200maxsize		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

pmmvs4		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

test-LLR		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

TESTMET0.1,1		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

test-mter		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

testgi		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

test20.03		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

thres600view7		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

MP-MVS		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
testmvs		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

thres400		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

test123		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

thres200		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

test0.0.03 1		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

pmmvs3		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

EMVS		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

E-PMN		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

PGM-MVS		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

MCST-MVS		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

MVS_Test		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

PMMVS2		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

PM-MVS		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

HQP_MVS		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

mPP-MVS		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

mvsmamba		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

HPM-MVS_fast		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

HPM-MVS		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
LPG-MVS_test		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

EPNet_dtu		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
EPNet		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CNVR-MVS		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

NCCC		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

CP-MVS		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

CPTT-MVS		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

HQP-MVS		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

IS-MVSNet		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

PAPM_NR		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

PAPR		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

Vis-MVSNet (Re-imp)		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

PatchMatch-RL		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

TDRefinement		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

EPP-MVSNet		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

PMMVS		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

PAPM		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

ACMMP		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280
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		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

wuyk23d		10000000.00 255	10000000.00 258	10000000.00 269	10000000.00 286	10000000.00 287	10000000.00 277	10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

APD-MVS		1000000000.00 358	1000000000.00 361	1000000000.00 374	1000000000.00 399	1000000000.00 398	1000000000.00 385	1000000000.00 399	1000000000.00 392	1000000000.00 393	1000000000.00 390	1000000000.00 395	1000000000.00 393	1000000000.00 391	1000000000.00 391	1000000000.00 389
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
FOURS1					2643.17 254	2465.14 256	13996.40 259	493.26 230	7619.38 260	2107.24 253

MSC_two_6792asdad				2237.56 238	2643.17 254	2465.14 256		493.26 230					3088.29 254	6075.14 253	1078.39 246	1159.26 244

PC_three_1452									7619.38 260	2107.24 253	7416.93 251	610.24 231	3088.29 254	6075.14 253	1078.39 246	1159.26 244

No_MVS				2237.56 238	2643.17 254	2465.14 256		493.26 230					3088.29 254	6075.14 253	1078.39 246	1159.26 244

test_one_0601					2643.17 254	2465.14 256		493.26 230	7619.38 260	2107.24 253	7416.93 251	610.24 231

eth-test2					1.42 66

eth-test					10000000.00 286

ZD-MVS					1584.00 223	1821.00 245		378.00 214	3721.00 221	1231.00 222	1833.00 203	321.00 205	1224.00 215	2103.00 215	692.00 212

IU-MVS					2725.60 259	2598.35 262		515.86 238	7016.02 253	2363.85 257				5973.88 249	1620.04 258	1732.56 254

OPU-MVS				2451.45 246	2725.60 259	2598.35 262	9203.30 239				6894.28 245	887.23 249	3023.43 250	5973.88 249	1620.04 258	1732.56 254

test_241102_TWO								515.86 238	7016.02 253	2363.85 257	6894.28 245	887.23 249	3023.43 250	5973.88 249	1620.04 258	1732.56 254

test_241102_ONE					2725.60 259	2598.35 262		515.86 238	7016.02 253	2363.85 257	6894.28 245	887.23 249	3023.43 250

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

test_0728_THIRD									5016.02 235	1363.85 227	4894.28 233	387.23 212	2023.43 228	3973.88 232	620.04 204	732.56 209

test_0728_SECOND				1451.45 217	1725.60 226	1598.35 229	9203.30 239	315.86 205					2023.43 228	3973.88 232	620.04 204	732.56 209

test0726					1725.60 226	1598.35 229	9203.30 239	315.86 205	5016.02 235	1363.85 227	4894.28 233	387.23 212

GSMVS																10000000.00 280

test_part2					10000000.00 286	10000000.00 287				10000000.00 283

sam_mvs1												10000000.00 283				10000000.00 280

sam_mvs												10000000.00 283

ambc				999.00 199	999.00 208	999.00 212	999.00 167	999.00 261		999.00 208	999.00 175	999.00 254	999.00 204	999.00 184	999.00 238	999.00 235

MTGPA								10000000.00 288

test_post1							10000000.00 277				10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282

test_post											10000000.00 280	10000000.00 283	10000000.00 283

patchmatchnet-post											10000000.00 280	10000000.00 283	10000000.00 283

GG-mvs-BLEND				596.01 182	611.29 184	600.33 190	790.30 162	513.12 236		552.71 186	567.40 156	662.54 241	531.67 172	503.93 158	779.80 219	656.02 203

MTMP							10000000.00 277	10000000.00 288

gm-plane-assit					611.29 184	600.33 190			579.21 160		567.40 156		531.67 172	503.93 158

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				10000000.00 269	10000000.00 286	10000000.00 287		10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

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					10000000.00 286	10000000.00 287

plane_prior6					10000000.00 286	10000000.00 287						10000000.00 283

plane_prior5								10000000.00 288					10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

plane_prior4											10000000.00 280

plane_prior3						10000000.00 287			10000000.00 283	10000000.00 283

plane_prior2							10000000.00 277		10000000.00 283

plane_prior1					10000000.00 286

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				569.20 180	667.25 197	644.68 196		96.45 168		428.86 173	1514.17 199	204.21 193	756.58 193	1061.60 193	197.79 171	306.34 182

LGP-MVS_train				10000000.00 269	10000000.00 286	10000000.00 287		10000000.00 288	10000000.00 283	10000000.00 283	10000000.00 280	10000000.00 283	10000000.00 283	10000000.00 282	10000000.00 282	10000000.00 280

test11								1.00 61

door								99.00 170

HQP5-MVS						10000000.00 287

HQP-NCC					10000000.00 286		10000000.00 277		10000000.00 283	10000000.00 283

ACMP_Plane					10000000.00 286		10000000.00 277		10000000.00 283	10000000.00 283

BP-MVS														10000000.00 282

HQP4-MVS										10000000.00 283			10000000.00 283			10000000.00 280

HQP3-MVS								10000000.00 288							10000000.00 282

HQP2-MVS												10000000.00 283

NP-MVS					10000000.00 286	10000000.00 287					10000000.00 280

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

ACMMP++_ref															10000000.00 282

ACMMP++															10000000.00 282

Test By Simon												990.00 253

ITE_SJBPF				2014.00 236	1998.00 237	1992.00 249		701.00 251	5989.00 240	1812.00 251	3612.00 221	650.00 235	2852.00 248	4601.00 241	1195.00 251	1198.00 248

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