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.

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

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

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

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_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

agg_prior					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

test_prior				0.00 1	0.00 1	0.00 1		0.00 1					0.00 1			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

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

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

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

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

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

LCM-MVSNet		0.37 12	0.36 13	0.37 17	0.37 24	0.37 24	0.37 24	0.32 25	0.37 24	0.37 24	0.37 22	0.37 24	0.37 25	0.37 23	0.37 23	0.37 23

v144192		0.40 13	0.40 14	0.40 18	0.40 25	0.40 25	0.40 25	0.40 27	0.40 25	0.40 25	0.40 23	0.40 25	0.40 26	0.40 24	0.40 24	0.40 24

v1921920		0.40 13	0.40 14	0.40 18	0.40 25	0.40 25	0.40 25	0.40 27	0.40 25	0.40 25	0.40 23	0.40 25	0.40 26	0.40 24	0.40 24	0.40 24

v1192		0.40 13	0.40 14	0.40 18	0.40 25	0.40 25	0.40 25	0.40 27	0.40 25	0.40 25	0.40 23	0.40 25	0.40 26	0.40 24	0.40 24	0.40 24

v1144		0.40 13	0.40 14	0.40 18	0.40 25	0.40 25	0.40 25	0.40 27	0.40 25	0.40 25	0.40 23	0.40 25	0.40 26	0.40 24	0.40 24	0.40 24

v148		0.40 13	0.40 14	0.40 18	0.40 25	0.40 25	0.40 25	0.40 27	0.40 25	0.40 25	0.40 23	0.40 25	0.40 26	0.40 24	0.40 24	0.40 24

v7n		0.40 13	0.40 14	0.40 18	0.40 25	0.40 25	0.40 25	0.40 27	0.40 25	0.40 25	0.40 23	0.40 25	0.40 26	0.40 24	0.40 24	0.40 24

v1240		0.40 13	0.40 14	0.40 18	0.40 25	0.40 25	0.40 25	0.40 27	0.40 25	0.40 25	0.40 23	0.40 25	0.40 26	0.40 24	0.40 24	0.40 24

v8		0.40 13	0.40 14	0.40 18	0.40 25	0.40 25	0.40 25	0.40 27	0.40 25	0.40 25	0.40 23	0.40 25	0.40 26	0.40 24	0.40 24	0.40 24

v10		0.40 13	0.40 14	0.40 18	0.40 25	0.40 25	0.40 25	0.40 27	0.40 25	0.40 25	0.40 23	0.40 25	0.40 26	0.40 24	0.40 24	0.40 24

v2v482		0.40 13	0.40 14	0.40 18	0.40 25	0.40 25	0.40 25	0.40 27	0.40 25	0.40 25	0.40 23	0.40 25	0.40 26	0.40 24	0.40 24	0.40 24

V42		0.40 13	0.40 14	0.40 18	0.40 25	0.40 25	0.40 25	0.40 27	0.40 25	0.40 25	0.40 23	0.40 25	0.40 26	0.40 24	0.40 24	0.40 24

GA-MVS		0.40 13	0.40 14	0.40 18	0.40 25	0.40 25	0.40 25	0.40 27	0.40 25	0.40 25	0.40 23	0.40 25	0.40 26	0.40 24	0.40 24	0.40 24

Fast-Effi-MVS+		0.41 25	0.40 14	0.41 30	0.41 37	0.41 37	0.41 37	0.35 26	0.41 37	0.41 37	0.41 35	0.41 37	0.41 38	0.41 36	0.41 36	0.41 36

Fast-Effi-MVS+-dtu		0.44 26	0.44 27	0.44 31	0.44 38	0.44 38	0.44 38	0.44 39	0.44 38	0.44 38	0.44 36	0.44 38	0.44 39	0.44 37	0.44 37	0.44 37

Effi-MVS+		0.58 27	0.56 28	0.62 33	0.53 39	0.62 40	0.53 39	0.53 40	0.53 39	0.62 40	0.62 38	0.53 39	0.62 41	0.62 38	0.53 38	0.62 39

ETV-MVS		0.62 29	0.62 30	0.62 33	0.62 40	0.62 40	0.62 41	0.62 41	0.62 40	0.62 40	0.62 38	0.62 40	0.62 41	0.62 38	0.62 40	0.62 39

EIA-MVS		0.62 29	0.62 30	0.62 33	0.62 40	0.62 40	0.62 41	0.62 41	0.62 40	0.62 40	0.62 38	0.62 40	0.62 41	0.62 38	0.62 40	0.62 39

CS-MVS		0.62 29	0.62 30	0.62 33	0.62 40	0.62 40	0.62 41	0.62 41	0.62 40	0.62 40	0.62 38	0.62 40	0.62 41	0.62 38	0.62 40	0.62 39

Effi-MVS+-dtu		0.59 28	0.61 29	0.53 32	0.68 43	0.53 39	0.53 39	0.68 44	0.68 43	0.53 39	0.53 37	0.68 43	0.53 40	0.68 42	0.53 38	0.53 38

mvs-test1		0.68 32	0.68 33	0.68 37	0.68 43	0.68 44	0.68 44	0.68 44	0.68 43	0.68 44	0.68 42	0.68 43	0.68 45	0.68 42	0.68 43	0.68 43

CDS-MVSNet		0.88 33	0.88 34	0.88 38	0.88 45	0.88 45	0.88 45	0.88 46	0.88 45	0.88 45	0.88 43	0.88 45	0.88 46	0.88 44	0.88 44	0.88 44
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
TAMVS		0.88 33	0.88 34	0.88 38	0.88 45	0.88 45	0.88 45	0.88 46	0.88 45	0.88 45	0.88 43	0.88 45	0.88 46	0.88 44	0.88 44	0.88 44

LCM-MVSNet-Re		0.89 35	0.89 36	0.89 40	0.89 47	0.89 47	0.89 47	0.89 48	0.89 47	0.89 47	0.89 45	0.89 47	0.89 48	0.89 46	0.89 46	0.89 46

DeepMVS_CX				1.00 41	1.00 48	1.00 48		1.00 49	1.00 48	1.00 48	1.00 46	1.00 48	1.00 49	1.00 47	1.00 47	1.00 47

MDA-MVSNet-bldmvs		1.20 36	1.20 37	1.20 42	1.20 49	1.20 50	1.20 48	1.20 51	1.20 49	1.20 49	1.20 47	1.20 49	1.20 50	1.20 48	1.20 48	1.20 48

YYNet1		1.20 36	1.20 37	1.20 42	1.20 49	1.20 50	1.20 48	1.20 51	1.20 49	1.20 49	1.20 47	1.20 49	1.20 50	1.20 48	1.20 48	1.20 48

MDA-MVSNet_test_wron		1.20 36	1.20 37	1.20 42	1.20 49	1.20 50	1.20 48	1.20 51	1.20 49	1.20 49	1.20 47	1.20 49	1.20 50	1.20 48	1.20 48	1.20 48

EI-MVSNet-UG-set		1.42 39	1.42 40	1.42 45	1.42 52	1.42 53	1.42 51	1.42 54	1.42 52	1.42 52	1.42 50	1.42 52	1.42 53	1.42 51	1.42 51	1.42 51

EI-MVSNet-Vis-set		1.42 39	1.42 40	1.42 45	1.42 52	1.42 53	1.42 51	1.42 54	1.42 52	1.42 52	1.42 50	1.42 52	1.42 53	1.42 51	1.42 51	1.42 51

Regformer-3		1.42 39	1.42 40	1.42 45	1.42 52	1.42 53	1.42 51	1.42 54	1.42 52	1.42 52	1.42 50	1.42 52	1.42 53	1.42 51	1.42 51	1.42 51

Regformer-4		1.42 39	1.42 40	1.42 45	1.42 52	1.42 53	1.42 51	1.42 54	1.42 52	1.42 52	1.42 50	1.42 52	1.42 53	1.42 51	1.42 51	1.42 51

Regformer-1		1.42 39	1.42 40	1.42 45	1.42 52	1.42 53	1.42 51	1.42 54	1.42 52	1.42 52	1.42 50	1.42 52	1.42 53	1.42 51	1.42 51	1.42 51

Regformer-2		1.42 39	1.42 40	1.42 45	1.42 52	1.42 53	1.42 51	1.42 54	1.42 52	1.42 52	1.42 50	1.42 52	1.42 53	1.42 51	1.42 51	1.42 51

EI-MVSNet		1.42 39	1.42 40	1.42 45	1.42 52	1.42 53	1.42 51	1.42 54	1.42 52	1.42 52	1.42 50	1.42 52	1.42 53	1.42 51	1.42 51	1.42 51

Regformer		1.42 39	1.42 40	1.42 45	1.42 52	1.42 53	1.42 51	1.42 54	1.42 52	1.42 52	1.42 50	1.42 52	1.42 53	1.42 51	1.42 51	1.42 51

CVMVSNet		1.42 39	1.42 40	1.42 45	1.42 52	1.42 53	1.42 51	1.42 54	1.42 52	1.42 52	1.42 50	1.42 52	1.42 53	1.42 51	1.42 51	1.42 51

EU-MVSNet		1.42 39	1.42 40	1.42 45	1.42 52	1.42 53	1.42 51	1.42 54	1.42 52	1.42 52	1.42 50	1.42 52	1.42 53	1.42 51	1.42 51	1.42 51

PS-CasMVS		1.42 39	1.42 40	1.42 45	1.42 52	1.42 53	1.42 51	1.42 54	1.42 52	1.42 52	1.42 50	1.42 52	1.42 53	1.42 51	1.42 51	1.42 51

UniMVSNet_NR-MVSNet		1.42 39	1.42 40	1.42 45	1.42 52	1.42 53	1.42 51	1.42 54	1.42 52	1.42 52	1.42 50	1.42 52	1.42 53	1.42 51	1.42 51	1.42 51

PEN-MVS		1.42 39	1.42 40	1.42 45	1.42 52	1.42 53	1.42 51	1.42 54	1.42 52	1.42 52	1.42 50	1.42 52	1.42 53	1.42 51	1.42 51	1.42 51

TransMVSNet (Re)		1.42 39	1.42 40	1.42 45	1.42 52	1.42 53	1.42 51	1.42 54	1.42 52	1.42 52	1.42 50	1.42 52	1.42 53	1.42 51	1.42 51	1.42 51

DTE-MVSNet		1.42 39	1.42 40	1.42 45	1.42 52	1.42 53	1.42 51	1.42 54	1.42 52	1.42 52	1.42 50	1.42 52	1.42 53	1.42 51	1.42 51	1.42 51

DU-MVS		1.42 39	1.42 40	1.42 45	1.42 52	1.42 53	1.42 51	1.42 54	1.42 52	1.42 52	1.42 50	1.42 52	1.42 53	1.42 51	1.42 51	1.42 51

UniMVSNet (Re)		1.42 39	1.42 40	1.42 45	1.42 52	1.42 53	1.42 51	1.42 54	1.42 52	1.42 52	1.42 50	1.42 52	1.42 53	1.42 51	1.42 51	1.42 51

CP-MVSNet		1.42 39	1.42 40	1.42 45	1.42 52	1.42 53	1.42 51	1.42 54	1.42 52	1.42 52	1.42 50	1.42 52	1.42 53	1.42 51	1.42 51	1.42 51

WR-MVS_H		1.42 39	1.42 40	1.42 45	1.42 52	1.42 53	1.42 51	1.42 54	1.42 52	1.42 52	1.42 50	1.42 52	1.42 53	1.42 51	1.42 51	1.42 51

WR-MVS		1.42 39	1.42 40	1.42 45	1.42 52	1.42 53	1.42 51	1.42 54	1.42 52	1.42 52	1.42 50	1.42 52	1.42 53	1.42 51	1.42 51	1.42 51

NR-MVSNet		1.42 39	1.42 40	1.42 45	1.42 52	1.42 53	1.42 51	1.42 54	1.42 52	1.42 52	1.42 50	1.42 52	1.42 53	1.42 51	1.42 51	1.42 51

Baseline_NR-MVSNet		1.42 39	1.42 40	1.42 45	1.42 52	1.42 53	1.42 51	1.42 54	1.42 52	1.42 52	1.42 50	1.42 52	1.42 53	1.42 51	1.42 51	1.42 51

TranMVSNet+NR-MVSNet		1.42 39	1.42 40	1.42 45	1.42 52	1.42 53	1.42 51	1.42 54	1.42 52	1.42 52	1.42 50	1.42 52	1.42 53	1.42 51	1.42 51	1.42 51

MVSFormer		1.42 39	1.42 40	1.42 45	1.42 52	1.42 53	1.42 51	1.42 54	1.42 52	1.42 52	1.42 50	1.42 52	1.42 53	1.42 51	1.42 51	1.42 51

jason		1.42 39	1.42 40	1.42 45	1.42 52	1.42 53	1.42 51	1.42 54	1.42 52	1.42 52	1.42 50	1.42 52	1.42 53	1.42 51	1.42 51	1.42 51
jason: jason.
lupinMVS		1.42 39	1.42 40	1.42 45	1.42 52	1.42 53	1.42 51	1.42 54	1.42 52	1.42 52	1.42 50	1.42 52	1.42 53	1.42 51	1.42 51	1.42 51

test_djsdf		1.42 39	1.42 40	1.42 45	1.42 52	1.42 53	1.42 51	1.42 54	1.42 52	1.42 52	1.42 50	1.42 52	1.42 53	1.42 51	1.42 51	1.42 51

alignmvs		2.00 66	2.00 67	2.00 72	2.00 79	2.00 80	2.00 78	2.00 83	2.00 79	2.00 79	2.00 77	2.00 79	2.00 80	2.00 78	2.00 78	2.00 78

nrg030		2.00 66	2.00 67	2.00 72	2.00 79	2.00 80	2.00 78	2.00 83	2.00 79	2.00 79	2.00 77	2.00 79	2.00 80	2.00 78	2.00 78	2.00 78

LFMVS		2.00 66	2.00 67	2.00 72	2.00 79	2.00 80	2.00 78	2.00 83	2.00 79	2.00 79	2.00 77	2.00 79	2.00 80	2.00 78	2.00 78	2.00 78

VDD-MVS		2.00 66	2.00 67	2.00 72	2.00 79	2.00 80	2.00 78	2.00 83	2.00 79	2.00 79	2.00 77	2.00 79	2.00 80	2.00 78	2.00 78	2.00 78

VDDNet		2.00 66	2.00 67	2.00 72	2.00 79	2.00 80	2.00 78	2.00 83	2.00 79	2.00 79	2.00 77	2.00 79	2.00 80	2.00 78	2.00 78	2.00 78

VPNet		2.00 66	2.00 67	2.00 72	2.00 79	2.00 80	2.00 78	2.00 83	2.00 79	2.00 79	2.00 77	2.00 79	2.00 80	2.00 78	2.00 78	2.00 78

VNet		2.00 66	2.00 67	2.00 72	2.00 79	2.00 80	2.00 78	2.00 83	2.00 79	2.00 79	2.00 77	2.00 79	2.00 80	2.00 78	2.00 78	2.00 78

VPA-MVSNet		2.00 66	2.00 67	2.00 72	2.00 79	2.00 80	2.00 78	2.00 83	2.00 79	2.00 79	2.00 77	2.00 79	2.00 80	2.00 78	2.00 78	2.00 78

cascas		2.00 66	2.00 67	2.00 72	2.00 79	2.00 80	2.00 78	2.00 83	2.00 79	2.00 79	2.00 77	2.00 79	2.00 80	2.00 78	2.00 78	2.00 78

UnsupCasMVSNet_eth		5.90 75	5.90 76	5.90 81	5.90 88	5.90 89	5.90 88	5.90 93	5.90 89	5.90 88	5.90 86	5.90 89	5.90 89	5.90 87	5.90 89	5.90 88

UnsupCasMVSNet_bld		5.90 75	5.90 76	5.90 81	5.90 88	5.90 89	5.90 88	5.90 93	5.90 89	5.90 88	5.90 86	5.90 89	5.90 89	5.90 87	5.90 89	5.90 88

WTY-MVS		5.90 75	5.90 76	5.90 81	5.90 88	5.90 89	5.90 88	5.90 93	5.90 89	5.90 88	5.90 86	5.90 89	5.90 89	5.90 87	5.90 89	5.90 88

HY-MVS	5.90 1	5.90 75	5.90 76	5.90 81	5.90 88	5.90 89	5.90 88	5.90 93	5.90 89	5.90 88	5.90 86	5.90 89	5.90 89	5.90 87	5.90 89	5.90 88

sss		5.90 75	5.90 76	5.90 81	5.90 88	5.90 89	5.90 88	5.90 93	5.90 89	5.90 88	5.90 86	5.90 89	5.90 89	5.90 87	5.90 89	5.90 88

Test_1112_low_res		5.90 75	5.90 76	5.90 81	5.90 88	5.90 89	5.90 88	5.90 93	5.90 89	5.90 88	5.90 86	5.90 89	5.90 89	5.90 87	5.90 89	5.90 88

1112_ss		5.90 75	5.90 76	5.90 81	5.90 88	5.90 89	5.90 88	5.90 93	5.90 89	5.90 88	5.90 86	5.90 89	5.90 89	5.90 87	5.90 89	5.90 88

ab-mvs-re		5.90 75	5.90 76	5.90 81	5.90 88	5.90 89	5.90 88	5.90 93	5.90 89	5.90 88	5.90 86	5.90 89	5.90 89	5.90 87	5.90 89	5.90 88

ab-mvs		5.90 75	5.90 76	5.90 81	5.90 88	5.90 89	5.90 88	5.90 93	5.90 89	5.90 88	5.90 86	5.90 89	5.90 89	5.90 87	5.90 89	5.90 88

CDPH-MVS		6.66 84	6.66 85	6.66 90	6.66 97	6.66 98	6.66 97	6.66 102	6.66 98	6.66 97	6.66 95	6.66 98	6.66 98	6.66 96	6.66 98	6.66 97

MDTV_nov1_ep13			9.99 86		9.99 98	9.99 100	9.99 98	9.99 104	9.99 99	9.99 99	9.99 96	9.99 99	9.99 100	9.99 97	9.99 99

xiu_mvs_v1_base_debu		10.28 85	10.28 87	10.28 92	10.28 99	10.28 102	10.28 100	10.28 105	10.28 101	10.28 101	10.28 97	10.28 101	10.28 101	10.28 99	10.28 100	10.28 99

xiu_mvs_v2_base		10.28 85	10.28 87	10.28 92	10.28 99	10.28 102	10.28 100	10.28 105	10.28 101	10.28 101	10.28 97	10.28 101	10.28 101	10.28 99	10.28 100	10.28 99

xiu_mvs_v1_base		10.28 85	10.28 87	10.28 92	10.28 99	10.28 102	10.28 100	10.28 105	10.28 101	10.28 101	10.28 97	10.28 101	10.28 101	10.28 99	10.28 100	10.28 99

xiu_mvs_v1_base_debi		10.28 85	10.28 87	10.28 92	10.28 99	10.28 102	10.28 100	10.28 105	10.28 101	10.28 101	10.28 97	10.28 101	10.28 101	10.28 99	10.28 100	10.28 99

cdsmvs_eth3d_5k		10.28 85	10.28 87	10.28 92	10.28 99	10.28 102	10.28 100	10.28 105	10.28 101	10.28 101	10.28 97	10.28 101	10.28 101	10.28 99	10.28 100	10.28 99

pcd_1.5k_mvsjas		10.28 85	10.28 87	10.28 92	10.28 99	10.28 102	10.28 100	10.28 105	10.28 101	10.28 101	10.28 97	10.28 101	10.28 101	10.28 99	10.28 100	10.28 99

PS-MVSNAJss		10.28 85	10.28 87	10.28 92	10.28 99	10.28 102	10.28 100	10.28 105	10.28 101	10.28 101	10.28 97	10.28 101	10.28 101	10.28 99	10.28 100	10.28 99

PS-MVSNAJ		10.28 85	10.28 87	10.28 92	10.28 99	10.28 102	10.28 100	10.28 105	10.28 101	10.28 101	10.28 97	10.28 101	10.28 101	10.28 99	10.28 100	10.28 99

jajsoiax		10.28 85	10.28 87	10.28 92	10.28 99	10.28 102	10.28 100	10.28 105	10.28 101	10.28 101	10.28 97	10.28 101	10.28 101	10.28 99	10.28 100	10.28 99

mvs_tets		10.28 85	10.28 87	10.28 92	10.28 99	10.28 102	10.28 100	10.28 105	10.28 101	10.28 101	10.28 97	10.28 101	10.28 101	10.28 99	10.28 100	10.28 99

dp		87.20 101	113.80 105	7.42 91	10.50 109	8.88 99	298.82 123	2.70 92	510.35 139	7.79 98	172.93 116	3.37 88	9.16 99	14.00 109	3.71 88	4.23 87

XXY-MVS		15.00 95	15.00 97	15.00 102	15.00 110	15.00 112	15.00 110	15.00 118	15.00 111	15.00 111	15.00 107	15.00 116	15.00 111	15.00 110	15.00 111	15.00 110

BH-w/o		40.00 96	40.00 98	40.00 104	40.00 111	40.00 113	40.00 111	40.00 135	40.00 112	40.00 113	40.00 108	40.00 134	40.00 113	40.00 111	40.00 127	40.00 122

BH-untuned		40.00 96	40.00 98	40.00 104	40.00 111	40.00 113	40.00 111	40.00 135	40.00 112	40.00 113	40.00 108	40.00 134	40.00 113	40.00 111	40.00 127	40.00 122

BH-RMVSNet		40.00 96	40.00 98	40.00 104	40.00 111	40.00 113	40.00 111	40.00 135	40.00 112	40.00 113	40.00 108	40.00 134	40.00 113	40.00 111	40.00 127	40.00 122

TR-MVS		40.00 96	40.00 98	40.00 104	40.00 111	40.00 113	40.00 111	40.00 135	40.00 112	40.00 113	40.00 108	40.00 134	40.00 113	40.00 111	40.00 127	40.00 122

GBi-Net		44.67 100	49.24 102	30.96 103	47.53 115	47.57 117	126.09 115	8.00 103	76.99 116	26.09 112	73.50 113	11.27 111	30.55 112	61.12 115	12.58 110	14.75 109

zzz-MVS		833442.10 222	1111233.77 227	67.09 110	65.59 116	64.81 120	284.50 119	10000000.00 251	219.97 123	59.62 119	229.89 128	12.72 112	103.00 133	203.67 134	27.93 112	33.46 111

MTAPA		833442.10 222	1111233.77 227	67.09 110	65.59 116	64.81 120	284.50 119	10000000.00 251	219.97 123	59.62 119	229.89 128	12.72 112	103.00 133	203.67 134	27.93 112	33.46 111

MP-MVS-pluss		833433.63 221	1111219.60 226	75.70 116	74.28 118	73.29 122	284.50 119	11.35 115	238.58 125	65.86 121	255.35 134	14.55 114	115.69 136	10000000.00 247	31.94 114	38.12 120
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
ACMMP_NAP		118.81 108	133.18 110	75.70 116	74.28 118	73.29 122	284.50 119	11.35 115	238.58 125	65.86 121	255.35 134	14.55 114	115.69 136	222.18 136	31.94 114	38.12 120

CANet		110.62 104	124.04 106	70.34 112	82.03 120	74.27 124	325.54 124	25.25 121	207.16 119	69.28 123	194.38 117	27.53 119	95.79 126	147.76 120	37.43 116	40.97 126

CANet_DTU		110.62 104	124.04 106	70.34 112	82.03 120	74.27 124	325.54 124	25.25 121	207.16 119	69.28 123	194.38 117	27.53 119	95.79 126	147.76 120	37.43 116	40.97 126

MVS_0304		110.62 104	124.04 106	70.34 112	82.03 120	74.27 124	325.54 124	25.25 121	207.16 119	69.28 123	194.38 117	27.53 119	95.79 126	147.76 120	37.43 116	40.97 126

UGNet		110.62 104	124.04 106	70.34 112	82.03 120	74.27 124	325.54 124	25.25 121	207.16 119	69.28 123	194.38 117	27.53 119	95.79 126	147.76 120	37.43 116	40.97 126
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
new_pmnet		88.14 102	98.62 103	56.70 108	98.14 124	56.07 118	246.79 117	15.37 119	148.06 117	50.77 117	143.13 114	23.35 117	62.65 117	93.26 116	68.71 134	51.38 133

N_pmnet		88.14 102	98.62 103	56.70 108	98.14 124	56.07 118	246.79 117	15.37 119	148.06 117	50.77 117	143.13 114	23.35 117	62.65 117	93.26 116	68.71 134	51.38 133

DSMNet-mixed		131.33 116	143.00 118	96.33 128	99.00 126	81.00 128	201.00 116	45.00 139	335.00 137	99.00 137	251.00 133	38.00 133	110.00 135	120.00 119	99.00 136	98.00 135

FMVSNet5		124.76 109	140.93 111	76.26 118	107.44 127	100.17 132	329.88 128	27.12 128	259.44 130	74.30 127	204.34 121	30.74 123	92.41 119	196.98 124	38.15 120	36.19 113

test1		124.76 109	140.93 111	76.26 118	107.44 127	100.17 132	329.88 128	27.12 128	259.44 130	74.30 127	204.34 121	30.74 123	92.41 119	196.98 124	38.15 120	36.19 113

FMVSNet3		124.76 109	140.93 111	76.26 118	107.44 127	100.17 132	329.88 128	27.12 128	259.44 130	74.30 127	204.34 121	30.74 123	92.41 119	196.98 124	38.15 120	36.19 113

FMVSNet2		124.76 109	140.93 111	76.26 118	107.44 127	100.17 132	329.88 128	27.12 128	259.44 130	74.30 127	204.34 121	30.74 123	92.41 119	196.98 124	38.15 120	36.19 113

FMVSNet1		124.76 109	140.93 111	76.26 118	107.44 127	100.17 132	329.88 128	27.12 128	259.44 130	74.30 127	204.34 121	30.74 123	92.41 119	196.98 124	38.15 120	36.19 113

MIMVSNet1		124.76 109	140.93 111	76.26 118	107.44 127	100.17 132	329.88 128	27.12 128	259.44 130	74.30 127	204.34 121	30.74 123	92.41 119	196.98 124	38.15 120	36.19 113

MIMVSNet		124.76 109	140.93 111	76.26 118	107.44 127	100.17 132	329.88 128	27.12 128	259.44 130	74.30 127	204.34 121	30.74 123	92.41 119	196.98 124	38.15 120	36.19 113

PVSNet_Blended_VisFu		136.90 117	155.40 119	81.40 125	111.00 134	96.20 129	407.00 135	25.90 125	251.60 127	85.10 134	240.50 130	37.00 130	99.90 130	199.80 131	40.70 131	48.10 130

PVSNet_BlendedMVS		136.90 117	155.40 119	81.40 125	111.00 134	96.20 129	407.00 135	25.90 125	251.60 127	85.10 134	240.50 130	37.00 130	99.90 130	199.80 131	40.70 131	48.10 130

PVSNet_Blended		136.90 117	155.40 119	81.40 125	111.00 134	96.20 129	407.00 135	25.90 125	251.60 127	85.10 134	240.50 130	37.00 130	99.90 130	199.80 131	40.70 131	48.10 130

DP-MVS		264.78 120	296.02 122	171.04 129	191.70 137	183.96 139	827.10 145	78.36 140	438.24 138	176.64 138	435.12 136	65.04 139	230.52 140	334.02 137	117.96 137	98.64 136

tmp_tt		371.08 121	412.78 123	246.00 131	231.00 138	197.00 140	1293.00 156	376.00 192	756.00 147	609.00 173	71.00 112	106.00 148	195.00 138	102.00 118	171.00 146	346.00 169

EG-PatchMatch MVS		437.03 123	493.12 127	268.77 132	264.80 139	260.20 142	1491.80 159	98.00 149	723.20 146	238.80 139	722.40 144	63.10 138	382.00 144	629.00 147	207.00 153	164.10 141

RPSCF		394.81 122	445.63 124	242.35 130	276.55 140	253.63 141	1207.27 154	90.69 145	715.56 145	241.57 140	684.87 143	111.96 149	320.02 141	548.38 144	133.81 138	153.39 138

DELS-MVS		514.57 130	587.73 133	295.12 135	343.03 141	328.09 145	1540.48 161	116.22 155	988.59 153	325.44 147	906.22 152	119.86 151	365.72 142	788.60 156	161.09 143	191.55 146
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		516.25 131	581.17 132	321.48 138	361.02 142	429.00 153	1995.36 165	78.48 141	796.20 148	283.32 143	796.02 147	96.78 143	382.98 145	636.72 149	186.66 150	152.46 137

ACMH+	729.97 2	661.38 137	754.00 139	383.51 142	368.96 143	376.38 148	2483.74 177	82.42 142	1089.25 161	333.39 148	1219.68 166	66.53 140	573.60 165	957.86 162	184.14 149	200.56 147

MVP-Stereo		473.58 126	533.67 128	293.33 133	376.00 144	318.00 143	1461.00 157	96.00 146	835.00 149	290.00 144	804.00 148	97.00 144	383.00 146	688.00 154	156.00 139	179.00 143
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
MS-PatchMatch		473.58 126	533.67 128	293.33 133	376.00 144	318.00 143	1461.00 157	96.00 146	835.00 149	290.00 144	804.00 148	97.00 144	383.00 146	688.00 154	156.00 139	179.00 143

tpmvs		501.65 129	567.42 131	304.33 136	395.39 146	356.32 146	1512.04 160	216.53 180	994.15 154	350.16 149	804.16 150	119.38 150	380.98 143	555.14 145	159.87 142	175.69 142

PatchmatchNet		492.52 128	551.22 130	316.40 137	400.20 147	357.90 147	1277.10 155	115.80 154	1034.60 160	315.90 146	874.00 151	155.10 154	402.20 148	629.50 148	158.80 141	189.10 145
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
PMVS	863.65 3	957.08 155	1054.11 162	666.00 169	401.00 148	495.00 156	3790.00 185	279.00 182	1607.00 180	521.00 165	1745.00 181	90.00 141	1105.00 193	639.00 150	415.00 179	398.00 176
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
CSCG		826.03 150	963.29 154	414.24 144	421.52 149	426.11 152	2230.35 166	179.52 176	1827.44 182	733.43 183	933.12 154	281.25 180	545.23 157	1800.35 189	262.64 166	271.38 157

IB-MVS	872.44 4	616.41 136	700.96 138	362.78 141	426.10 150	409.25 151	1822.69 162	124.42 163	1186.23 163	366.85 151	1079.42 163	190.60 167	451.78 151	930.72 161	181.59 148	227.30 149
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
ADS-MVSNet2		443.33 124	482.84 125	324.79 139	434.94 151	387.73 149	1110.57 152	87.69 143	887.02 151	282.92 141	779.29 145	98.57 146	422.76 149	502.40 138	162.19 144	163.87 139

ADS-MVSNet		443.33 124	482.84 125	324.79 139	434.94 151	387.73 149	1110.57 152	87.69 143	887.02 151	282.92 141	779.29 145	98.57 146	422.76 149	502.40 138	162.19 144	163.87 139

ACMH	993.80 5	967.92 156	1106.11 164	553.33 158	494.00 153	534.00 158	3581.00 183	136.00 165	1585.00 179	478.00 162	1871.00 182	90.00 141	839.00 177	1460.00 183	260.00 165	287.00 160
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
IterMVS		615.05 135	691.66 137	385.23 143	516.40 154	454.80 154	1863.80 163	102.10 151	1142.20 162	364.10 150	1093.20 165	135.00 152	480.40 152	826.90 157	181.20 147	220.50 148
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
ACMM	1311.08 8	1165.06 167	1332.72 169	662.07 168	584.90 155	715.99 179	4373.59 190	153.99 173	1880.27 184	709.02 180	2316.97 186	188.63 166	939.89 182	1484.30 184	302.78 173	330.34 166
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
new-patchmatchnet		766.12 140	859.03 144	487.38 155	595.68 156	536.14 159	2346.27 168	142.51 168	1488.08 170	422.43 152	1361.32 170	163.65 157	628.60 169	1003.74 170	207.61 154	297.41 162

ACMP	1246.57 7	1086.24 163	1235.17 166	639.45 165	596.53 157	639.91 174	3904.24 186	152.04 171	1851.54 183	566.58 171	1997.95 184	138.50 153	938.30 181	1605.46 185	303.70 174	340.14 167
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
SixPastTwentyTwo		773.62 141	869.37 146	486.35 154	603.45 158	547.15 167	2532.14 178	106.92 153	1434.95 169	428.08 153	1360.56 169	165.15 158	628.96 170	984.09 163	209.01 155	282.94 159

IterMVS-LS		758.94 139	856.56 143	466.10 152	606.60 159	546.80 166	2309.90 167	122.20 162	1402.80 168	463.50 155	1348.20 168	192.60 168	574.60 166	1028.60 171	234.60 164	276.90 158
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
MG-MVS		1256.50 169	1432.00 171	730.00 174	610.00 160	760.00 181	4720.00 191	169.00 174	1920.00 185	723.00 182	2510.00 192	201.00 171	1050.00 191	1645.00 187	390.00 178	380.00 173

SR-MVS		610.10 133	610.10 135	610.10 164	610.10 161	610.10 173	610.10 140	610.10 215	610.10 144	610.10 174	610.10 142	610.10 207	610.10 168	610.10 146	610.10 183	610.10 181

GG-mvs-BLEND				596.01 162	611.29 162	600.33 170	790.30 142	513.12 209		552.71 167	567.40 137	662.54 215	531.67 153	503.93 140	779.80 197	656.02 183

gm-plane-assit					611.29 162	600.33 170			579.21 140		567.40 137		531.67 153	503.93 140

CR-MVSNet		612.36 134	617.81 136	596.01 162	611.29 162	600.33 170	790.30 142	513.12 209	579.21 140	552.71 167	567.40 137	662.54 215	531.67 153	503.93 140	779.80 197	656.02 183

Gipuma		689.75 138	767.00 140	458.00 151	613.00 165	549.00 168	1943.00 164	187.00 177	1230.00 164	518.00 164	1092.00 164	203.00 173	564.00 158	892.00 160	225.00 162	261.00 156
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
gg-mvs-nofinetune		594.69 132	605.37 134	562.67 159	617.29 166	500.33 157	772.30 141	413.12 199	579.21 140	552.71 167	567.40 137	662.54 215	531.67 153	503.93 140	779.80 197	656.02 183

mvs_anonymous		774.90 142	882.28 147	452.77 145	636.50 167	537.20 160	2348.80 169	120.30 156	1504.30 171	474.40 156	1371.10 171	186.90 160	564.70 159	1078.90 173	219.30 156	256.40 150

casdiffmvs		774.90 142	882.28 147	452.77 145	636.50 167	537.20 160	2348.80 169	120.30 156	1504.30 171	474.40 156	1371.10 171	186.90 160	564.70 159	1078.90 173	219.30 156	256.40 150

diffmvs		774.90 142	882.28 147	452.77 145	636.50 167	537.20 160	2348.80 169	120.30 156	1504.30 171	474.40 156	1371.10 171	186.90 160	564.70 159	1078.90 173	219.30 156	256.40 150

baseline2		774.90 142	882.28 147	452.77 145	636.50 167	537.20 160	2348.80 169	120.30 156	1504.30 171	474.40 156	1371.10 171	186.90 160	564.70 159	1078.90 173	219.30 156	256.40 150

baseline1		774.90 142	882.28 147	452.77 145	636.50 167	537.20 160	2348.80 169	120.30 156	1504.30 171	474.40 156	1371.10 171	186.90 160	564.70 159	1078.90 173	219.30 156	256.40 150

baseline		774.90 142	882.28 147	452.77 145	636.50 167	537.20 160	2348.80 169	120.30 156	1504.30 171	474.40 156	1371.10 171	186.90 160	564.70 159	1078.90 173	219.30 156	256.40 150

PVSNet	1207.94 6	829.56 151	937.18 153	506.69 156	645.55 173	585.72 169	2477.98 176	130.52 164	1578.29 178	509.50 163	1460.01 177	194.90 169	637.19 171	1170.78 180	267.07 168	297.17 161

FPMVS		1407.00 172	1495.59 173	1141.23 186	648.01 174	893.85 188	4124.00 187	503.81 208	3219.04 195	742.72 184	2498.84 191	157.98 155	1727.83 199	832.93 158	732.98 196	802.00 192

lessismore_v0				569.20 160	667.25 175	644.68 175		96.45 148		428.86 154	1514.17 178	204.21 174	756.58 173	1061.60 172	197.79 152	306.34 163

PVSNet_0	1661.03 9	968.54 157	1066.82 163	673.70 170	706.94 176	695.69 177	2669.02 181	153.52 172	2108.17 187	605.54 172	1679.14 180	213.26 177	886.75 180	1236.76 182	229.01 163	438.67 177

MSLP-MVS++		1242.93 168	1411.08 170	738.48 175	712.71 177	712.68 178	4168.17 188	136.50 166	2276.40 189	613.28 175	2368.60 189	161.61 156	1130.38 194	1964.54 192	297.88 171	372.39 172

MVSTER		890.06 154	1005.91 161	542.52 157	736.13 178	653.90 176	2616.56 180	145.22 170	1692.10 181	555.69 170	1554.72 179	266.25 179	660.02 172	1219.66 181	266.84 167	313.64 165

MVS_111021_LR		1136.45 166	1298.72 168	649.64 166	756.17 179	726.26 180	3785.94 184	138.15 167	2190.64 188	629.63 176	2064.39 185	165.45 159	874.83 179	1678.43 188	279.70 169	347.82 170

DeepC-MVS_fast	2190.19 12	1535.59 173	1886.82 176	481.89 153	847.73 180	830.16 185	7943.84 210	189.23 178	2398.83 190	691.73 179	2341.13 187	209.16 175	230.25 139	1999.25 193	360.46 176	385.25 174
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
JIA-IIPM		804.30 148	835.64 141	710.26 172	885.90 181	895.90 189	455.98 138	668.73 217	1297.17 165	1002.26 194	1001.67 161	655.98 213	756.98 174	667.90 151	885.21 209	477.90 178

RPMNet		804.30 148	835.64 141	710.26 172	885.90 181	895.90 189	455.98 138	668.73 217	1297.17 165	1002.26 194	1001.67 161	655.98 213	756.98 174	667.90 151	885.21 209	477.90 178

ACMMPR		1296.60 170	1480.82 172	743.96 176	899.25 183	763.47 182	4305.47 189	143.90 169	2530.94 192	683.99 177	2346.34 188	201.65 172	1098.25 192	1920.59 191	295.21 170	370.16 171

test_0402		1110.00 165	1260.00 167	660.00 167	900.00 184	780.00 183	3300.00 182	210.00 179	2040.00 186	690.00 178	1950.00 183	300.00 183	810.00 176	1620.00 186	330.00 175	390.00 175

TSAR-MVS + GP.		1386.84 171	1622.84 174	678.81 171	952.13 185	840.17 186	5358.21 194	170.75 175	2650.47 193	713.54 181	2394.28 190	209.42 176	855.56 178	1854.36 190	302.42 172	340.71 168

ambc				999.00 179	999.00 186	999.00 191	999.00 146	999.00 229		999.00 188	999.00 155	999.00 225	999.00 185	999.00 164	999.00 215	999.00 213

OurMVSNet-221017-0		999.00 158	999.00 156	999.00 179	999.00 186	999.00 191	999.00 146	999.00 229	999.00 155	999.00 188	999.00 155	999.00 225	999.00 185	999.00 164	999.00 215	999.00 213

EPMVS		999.00 158	999.00 156	999.00 179	999.00 186	999.00 191	999.00 146	999.00 229	999.00 155	999.00 188	999.00 155	999.00 225	999.00 185	999.00 164	999.00 215	999.00 213

sosnet		1000.00 160	1000.00 158	1000.00 182	1000.00 189	1000.00 194	1000.00 149	1000.00 232	1000.00 157	1000.00 191	1000.00 158	1000.00 228	1000.00 188	1000.00 167	1000.00 218	1000.00 216

USDC		1000.00 160	1000.00 158	1000.00 182	1000.00 189	1000.00 194	1000.00 149	1000.00 232	1000.00 157	1000.00 191	1000.00 158	1000.00 228	1000.00 188	1000.00 167	1000.00 218	1000.00 216

TinyColmap		1000.00 160	1000.00 158	1000.00 182	1000.00 189	1000.00 194	1000.00 149	1000.00 232	1000.00 157	1000.00 191	1000.00 158	1000.00 228	1000.00 188	1000.00 167	1000.00 218	1000.00 216

COLMAP_ROB	2144.59 11	1658.33 174	1869.33 175	1025.33 185	1030.00 192	1023.00 197	5311.00 193	359.00 190	3044.00 194	937.00 187	2892.00 193	332.00 186	1440.00 196	2312.00 194	607.00 182	613.00 182
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
F-COLMAP		1878.17 175	2113.11 177	1173.33 189	1231.00 193	1174.00 198	6297.00 196	392.00 194	3356.00 197	1087.00 196	3082.00 194	361.00 190	1670.00 198	2523.00 196	689.00 188	676.00 187

OpenMVS_ROB	1936.51 10	1959.51 176	2224.88 179	1163.39 188	1253.91 194	1434.22 201	7065.71 200	272.76 181	2472.29 191	1647.54 223	3538.72 197	200.37 170	1496.48 197	2575.17 197	997.45 214	559.48 180

Patchmtry		1090.75 164	1198.88 165	766.38 177	1290.90 195	485.90 155	2423.98 175	1267.30 235	1297.17 165	923.90 185	923.40 153	1215.54 232	990.23 183	667.90 151	779.80 197	823.02 196

PatchT		856.34 152	860.99 145	842.38 178	1290.90 195	880.90 187	790.30 142	1267.30 235	579.21 140	923.90 185	567.40 137	662.54 215	990.23 183	887.56 159	779.80 197	656.02 183

K. test v3		877.74 153	980.16 155	570.46 161	1316.85 197	813.15 184	2565.52 179	103.78 152	1509.49 177	548.33 166	1258.90 167	219.93 178	587.82 167	1102.37 179	196.30 151	310.42 164

PLC	2858.82 16	2192.92 179	2474.00 181	1349.67 191	1407.00 198	1356.00 200	7164.00 201	475.00 206	3970.00 200	1237.00 202	3765.00 200	451.00 196	1891.00 204	3006.00 199	791.00 202	802.00 192
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
CMPMVS	2623.62 15	1983.08 177	2156.14 178	1463.89 199	1414.80 199	1517.00 203	5239.20 192	867.40 223	3310.30 196	1128.70 198	3489.90 196	366.75 191	2030.20 210	2427.60 195	1160.60 222	844.46 199
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
Vis-MVSNet		2877.42 191	3170.00 193	1999.67 212	1673.00 200	2042.00 227	8593.00 214	474.00 205	6452.00 224	1268.00 203	5125.00 213	339.00 187	3004.00 226	4222.00 215	384.00 177	953.00 209
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
PCF-MVS	4335.85 20	2272.23 181	2597.03 183	1297.84 190	1701.20 201	1332.37 199	8105.11 211	451.45 202	4031.84 201	1099.10 197	3966.50 201	467.45 197	1734.05 200	2701.68 198	848.94 206	827.11 197
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
test_0728_SECOND				1451.45 196	1725.60 202	1598.35 207	9203.30 217	315.86 185					2023.43 207	3973.88 209	620.04 184	732.56 189

test0726					1725.60 202	1598.35 207	9203.30 217	315.86 185	5016.02 211	1363.85 205	4894.28 210	387.23 192

SD-MVS		2654.53 188	3055.56 192	1451.45 196	1725.60 202	1598.35 207	9203.30 217	315.86 185	5016.02 211	1363.85 205	4894.28 210	387.23 192	2023.43 207	3973.88 209	620.04 184	732.56 189
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
3Dnovator	2482.06 14	2531.17 185	2839.56 187	1606.00 200	1732.00 205	1557.00 205	8375.00 213	483.00 207	4370.00 205	1371.00 208	4200.00 202	350.00 188	2207.00 211	3877.00 208	798.00 203	1054.00 219

LF4IMVS		2699.50 190	3049.67 191	1649.00 202	1755.00 206	1689.00 214	8330.00 212	464.00 204	4997.00 210	1528.00 211	4763.00 209	568.00 205	2296.00 213	4215.00 214	827.00 205	962.00 210

DPM-MVS		3268.00 195	3762.89 197	1783.33 206	1756.00 207	1806.00 221	12319.00 227	307.00 183	6319.00 222	1557.00 216	5763.00 216	302.00 184	2609.00 219	5061.00 220	482.00 180	935.00 207

OPM-MVS		3268.00 195	3762.89 197	1783.33 206	1756.00 207	1806.00 221	12319.00 227	307.00 183	6319.00 222	1557.00 216	5763.00 216	302.00 184	2609.00 219	5061.00 220	482.00 180	935.00 207

OpenMVS	2352.88 13	2263.08 180	2530.89 182	1459.67 198	1767.00 209	1591.00 206	7932.00 209	399.00 195	3643.00 198	1176.00 199	3569.00 198	297.00 182	1927.00 206	3302.00 201	693.00 191	861.00 200

tpmrst		2557.50 186	2847.12 188	1688.66 203	1784.08 210	1778.25 220	7445.50 207	342.14 188	4471.54 206	1534.55 212	4382.10 206	530.10 203	2361.21 214	4142.81 212	991.22 213	926.51 206

AdaColmap		2570.77 187	2948.61 189	1437.24 195	1873.64 211	1526.60 204	7819.77 208	373.97 191	4970.45 209	1479.29 210	4648.46 208	525.80 202	1904.97 205	4150.42 213	695.69 192	880.14 204

SteuartSystems-ACMMP		2891.50 192	3284.78 194	1711.67 204	1954.00 212	1655.00 213	10117.00 224	445.00 201	5102.00 214	1375.00 209	5126.00 214	351.00 189	2638.00 223	4402.00 216	691.00 190	842.00 198
Skip Steuart: Steuart Systems R&D Blog.
ITE_SJBPF				2014.00 213	1998.00 213	1992.00 225		701.00 219	5989.00 216	1812.00 227	3612.00 199	650.00 209	2852.00 225	4601.00 218	1195.00 223	1198.00 221

tpm2		3617.85 199	4007.23 200	2449.73 216	2012.71 214	1698.05 215	7351.19 203	869.29 224	6132.06 217	1588.28 218	8007.42 227	1281.09 233	3888.11 231	7472.04 230	1351.00 224	1763.02 228

tpm cat1		3617.85 199	4007.23 200	2449.73 216	2012.71 214	1698.05 215	7351.19 203	869.29 224	6132.06 217	1588.28 218	8007.42 227	1281.09 233	3888.11 231	7472.04 230	1351.00 224	1763.02 228

CostFormer		3617.85 199	4007.23 200	2449.73 216	2012.71 214	1698.05 215	7351.19 203	869.29 224	6132.06 217	1588.28 218	8007.42 227	1281.09 233	3888.11 231	7472.04 230	1351.00 224	1763.02 228

tpm		3617.85 199	4007.23 200	2449.73 216	2012.71 214	1698.05 215	7351.19 203	869.29 224	6132.06 217	1588.28 218	8007.42 227	1281.09 233	3888.11 231	7472.04 230	1351.00 224	1763.02 228

CHOSEN 280x420		2340.81 182	2643.03 184	1434.14 192	2025.55 218	1629.36 210	6542.40 197	412.49 196	4219.70 202	1547.02 213	4328.52 203	650.74 210	1798.26 201	3333.17 202	727.72 193	874.79 201

CHOSEN 1792x2688		2340.81 182	2643.03 184	1434.14 192	2025.55 218	1629.36 210	6542.40 197	412.49 196	4219.70 202	1547.02 213	4328.52 203	650.74 210	1798.26 201	3333.17 202	727.72 193	874.79 201

HyFIR lowres test		2340.81 182	2643.03 184	1434.14 192	2025.55 218	1629.36 210	6542.40 197	412.49 196	4219.70 202	1547.02 213	4328.52 203	650.74 210	1798.26 201	3333.17 202	727.72 193	874.79 201

DVP-MVS		3981.10 205	4731.32 208	1730.42 205	2191.51 221	1949.98 224	16473.90 234	355.33 189	7172.90 230	1622.98 222	7879.79 226	434.33 195	2428.11 216	5762.12 223	689.04 189	813.18 195

3Dnovator+	3414.41 17	3146.67 193	3537.00 195	1975.67 210	2310.00 222	2005.00 226	10100.00 223	626.00 216	5753.00 215	1803.00 226	5179.00 215	487.00 198	2622.00 221	4550.00 217	1025.00 221	1300.00 222

TSAR-MVS + MP.		3528.01 198	4065.89 204	1914.35 209	2349.10 223	2141.30 228	12362.70 229	417.60 200	6717.80 228	1759.40 225	6497.50 219	518.18 201	2629.38 222	5164.32 222	806.40 204	972.38 212
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
DeepPCF-MVS	3452.42 18	2670.71 189	3021.57 190	1618.12 201	2377.67 224	1751.39 219	8915.70 216	567.44 213	4569.74 207	1236.84 201	4615.63 207	513.23 200	2291.32 212	3515.48 205	882.39 208	811.66 194

GST-MVS		4000.00 206	4533.33 207	2400.00 215	2400.00 225	2400.00 230	7200.00 202	2400.00 239	7200.00 231	2400.00 230	7200.00 223	2400.00 237	2400.00 215	7200.00 228	2400.00 233	2400.00 233

MVS_111021_HR		3742.80 203	4330.34 205	1980.20 211	2484.31 226	2259.52 229	14973.80 232	515.90 212	6500.13 225	1949.21 228	6146.89 218	535.66 204	2593.66 218	4880.76 219	986.37 212	1087.43 220

DeepC-MVS	3917.13 19	3155.06 194	3601.83 196	1814.72 208	2515.52 227	1941.53 223	10432.50 225	589.42 214	4789.45 208	1298.65 204	7677.31 225	578.35 206	2589.53 217	3611.78 207	923.52 211	913.10 205
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
TAPA-MVS	6309.84 21	3374.90 197	3806.99 199	2078.63 214	2535.47 228	2499.25 231	8816.16 215	456.05 203	6255.60 221	1664.52 224	6704.88 221	629.95 208	2768.38 224	6343.93 226	856.35 207	968.25 211
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
MSP-MVS		4296.20 207	4911.12 210	2451.45 220	2725.60 229	2598.35 232	16203.30 233	515.86 211	7016.02 229	2363.85 229	6894.28 222	887.23 223	3023.43 227	5973.88 225	1620.04 230	1732.56 227

MVS-HIRNet		2125.39 178	2452.68 180	1143.53 187	2938.33 230	1446.92 202	6083.19 195	391.74 193	3801.71 199	1202.10 200	3439.72 195	492.73 199	1304.35 195	3048.25 200	676.32 187	679.32 188

MAR-MVS		3973.16 204	4387.92 206	2728.86 221	3345.27 231	3341.39 235	11403.90 226	798.76 221	6555.62 227	2569.29 231	6514.86 220	834.97 222	3237.43 228	5891.08 224	1577.54 229	1607.76 223
Zhenyu Xu, Yiguang Liu, Xuelei Shi, Ying Wang, Yunan Zheng: MARMVS: Matching Ambiguity Reduced Multiple View Stereo for Efficient Large Scale Scene Reconstruction. CVPR 2020
API-MVS		4380.83 208	4906.56 209	2803.67 222	3844.00 232	3116.00 234	13454.00 230	901.00 228	6511.00 226	2794.00 232	7365.00 224	754.00 219	3634.00 229	6622.00 227	1914.00 232	1661.00 226

CLD-MVS		7338.25 210	8341.00 212	4330.00 224	4902.00 233	4991.00 236	23318.00 236	728.00 220	14437.00 238	4378.00 235	13379.00 235	824.00 221	5708.00 235	11429.00 239	1674.00 231	2291.00 232
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
OMC-MVS		5022.26 209	5748.82 211	2842.58 223	4905.27 234	3101.27 233	14933.60 231	812.24 222	9278.40 232	2959.29 233	8800.17 231	1092.24 231	3806.30 230	7568.54 234	1389.60 228	1620.18 225

LS3D		7684.71 211	8776.23 213	4410.16 225	5298.55 235	5631.53 237	34329.90 238	1504.57 237	11554.00 237	3896.41 234	15111.00 236	812.19 220	5985.63 236	3516.20 206	2963.23 234	1613.31 224

MVE	10021.00 22	10550.67 215	10002.44 217	12195.33 230	6242.00 236	8768.00 239	30896.00 237	4451.00 240	10331.00 236	6247.00 236	18296.00 237	283.00 181	21484.00 241	7364.00 229	5912.00 236	6334.00 235
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
CNLPA		10738.67 216	11772.44 218	7637.33 226	9120.00 237	8206.00 238	22252.00 235	2010.00 238	24984.00 239	7458.00 237	22596.00 238	2940.00 238	10260.00 240	11100.00 238	3492.00 235	4446.00 234

UA-Net		10000.00 212	10000.00 214	10000.00 227	10000.00 238	10000.00 240	10000.00 220	10000.00 243	10000.00 233	10000.00 238	10000.00 232	10000.00 240	10000.00 237	10000.00 235	10000.00 237	10000.00 236

uncertanet		10000.00 212	10000.00 214	10000.00 227	10000.00 238	10000.00 240	10000.00 220	10000.00 243	10000.00 233	10000.00 238	10000.00 232	10000.00 240	10000.00 237	10000.00 235	10000.00 237	10000.00 236

uanet		10000.00 212	10000.00 214	10000.00 227	10000.00 238	10000.00 240	10000.00 220	10000.00 243	10000.00 233	10000.00 238	10000.00 232	10000.00 240	10000.00 237	10000.00 235	10000.00 237	10000.00 236

LTVRE_ROB	20565.47 23	23378.08 217	22805.00 219	25097.33 231	15500.00 241	19201.00 243	42712.00 239	6055.00 241	38388.00 240	16926.00 241	38534.00 239	7071.00 239	35653.00 242	29475.00 240	10584.00 240	20438.00 240
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		32606.17 218	34443.44 220	27094.33 232	29249.00 242	25246.00 244	51144.00 240	6705.00 242	42886.00 241	22888.00 242	48534.00 240	13263.00 243	37507.00 243	79298.00 241	16024.00 241	18530.00 239

114514_t		99999.00 219	99999.00 221	99999.00 233	99999.00 243	99999.00 245	99999.00 241	99999.00 246	99999.00 242	99999.00 243	99999.00 241	99999.00 244	99999.00 244	99999.00 242	99999.00 242	99999.00 241

PHI-MVS		99999.00 219	99999.00 221	99999.00 233	99999.00 243	99999.00 245	99999.00 241	99999.00 246	99999.00 242	99999.00 243	99999.00 241	99999.00 244	99999.00 244	99999.00 242	99999.00 242	99999.00 241

XVG-OURS-SEG-HR		999999.00 224	999999.00 223	999999.00 235	999999.00 245	999999.00 247	999999.00 243	999999.00 248	999999.00 244	999999.00 245	999999.00 243	999999.00 246	999999.00 246	999999.00 244	999999.00 244	999999.00 243

XVG-OURS		999999.00 224	999999.00 223	999999.00 235	999999.00 245	999999.00 247	999999.00 243	999999.00 248	999999.00 244	999999.00 245	999999.00 243	999999.00 246	999999.00 246	999999.00 244	999999.00 244	999999.00 243

XVG-ACMP-BASELINE		999999.00 224	999999.00 223	999999.00 235	999999.00 245	999999.00 247	999999.00 243	999999.00 248	999999.00 244	999999.00 245	999999.00 243	999999.00 246	999999.00 246	999999.00 244	999999.00 244	999999.00 243

testtj		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

ET-MVSNet_ETH3D		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

UniMVSNet_ETH3D		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

miper_lstm_enhance		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

D2MVS		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

test_yl		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

thisisatest0530		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

Anonymous20240529		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

Anonymous202405211		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

DCV-MVSNet		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

tttt0517		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

our_test_3		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

thisisatest0515		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

ppachtmachnet_test		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

SMA-MVS		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

DPE-MVS		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

test_part2					10000000.00 248	10000000.00 250				10000000.00 248

thres100view900		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

tfpnnormal		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

tfpn200view9		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

IterMVS-SCA-FT		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

pmmvs6		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

pmmvs5		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

Anonymous20231211		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

pmmvs-eth3d		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

Anonymous20231206		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

SCA		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

Patchmatch-test		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

Patchmatch-RL test		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

canonicalmvs		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

anonymousdsp		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

FIs		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

FC-MVSNet-test		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

sosnet-low-res		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

AllTest		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

TestCases				10000000.00 238	10000000.00 248	10000000.00 250		10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

testing_2		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

test_normal		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

HPM-MVS++		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

XVS		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

pm-mvs1		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

X-MVStestdata		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

APDe-MVS		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

APD-MVS_3200maxsize		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

pmmvs4		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

test-LLR		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

TESTMET0.1,1		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

test-mter		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

testgi		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

test20.03		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

thres600view7		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

MP-MVS		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
testmvs		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

thres400		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

test123		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

thres200		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

test0.0.03 1		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

pmmvs3		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

EMVS		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

E-PMN		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

PGM-MVS		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

MCST-MVS		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

MVS_Test		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

PMMVS2		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

PM-MVS		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

HQP_MVS		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

plane_prior7					10000000.00 248	10000000.00 250

plane_prior6					10000000.00 248	10000000.00 250						10000000.00 249

plane_prior1					10000000.00 248

mPP-MVS		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

DI_MVS_plusplus_test		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

DWT-MVSNet_test		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

HPM-MVS_fast		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

PatchFormer-LS_test		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

HPM-MVS		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
LPG-MVS_test		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

LGP-MVS_train				10000000.00 238	10000000.00 248	10000000.00 250		10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

EPNet_dtu		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
EPNet		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
HQP-NCC					10000000.00 248		10000000.00 246		10000000.00 247	10000000.00 248

ACMP_Plane					10000000.00 248		10000000.00 246		10000000.00 247	10000000.00 248

CNVR-MVS		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

NCCC		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

CP-MVS		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

NP-MVS					10000000.00 248	10000000.00 250					10000000.00 246

CPTT-MVS		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

HQP-MVS		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

IS-MVSNet		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

PAPM_NR		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

PAPR		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

Vis-MVSNet (Re-imp)		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

PatchMatch-RL		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

TDRefinement		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

EPP-MVSNet		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

PMMVS		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

PAPM		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

ACMMP		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246
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		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

wuyk23d		10000000.00 227	10000000.00 229	10000000.00 238	10000000.00 248	10000000.00 250	10000000.00 246	10000000.00 251	10000000.00 247	10000000.00 248	10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

APD-MVS		1000000000.00 317	1000000000.00 319	1000000000.00 331	1000000000.00 347	1000000000.00 349	1000000000.00 342	1000000000.00 350	1000000000.00 343	1000000000.00 345	1000000000.00 343	1000000000.00 349	1000000000.00 347	1000000000.00 344	1000000000.00 344	1000000000.00 343
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
save filter2										0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

test_0728_THIRD									5016.02 211	1363.85 205	4894.28 210	387.23 192	2023.43 207	3973.88 209	620.04 184	732.56 189

GSMVS																10000000.00 246

test_part1				10000000.00 238		10000000.00 250	10000000.00 246	10000000.00 251				10000000.00 249	10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

sam_mvs1												10000000.00 249				10000000.00 246

sam_mvs												10000000.00 249

MTGPA								10000000.00 251

test_post1							10000000.00 246				10000000.00 246	10000000.00 249	10000000.00 249	10000000.00 247

test_post											10000000.00 246	10000000.00 249	10000000.00 249

patchmatchnet-post											10000000.00 246	10000000.00 249	10000000.00 249

MTMP							10000000.00 246	10000000.00 251

test9_res														0.00 1	0.00 1	0.00 1

agg_prior2														0.00 1	0.00 1	0.00 1

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

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

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

testdata2													0.00 1	0.00 1

segment_acmp												0.00 1

testdata1							0.00 1		0.00 1

plane_prior5								10000000.00 251					10000000.00 249	10000000.00 247	10000000.00 247	10000000.00 246

plane_prior4											10000000.00 246

plane_prior3						10000000.00 250			10000000.00 247	10000000.00 248

plane_prior2							10000000.00 246		10000000.00 247

plane_prior						1.00 48	2.00 78		2.00 79						2.00 78

n2								14.20 117

nn								1.42 54

door-mid								1.42 54

test11								1.00 49

door								99.00 150

HQP5-MVS						10000000.00 250

BP-MVS														10000000.00 247

HQP4-MVS										10000000.00 248			10000000.00 249			10000000.00 246

HQP3-MVS								10000000.00 251							10000000.00 247

HQP2-MVS												10000000.00 249

MDTV_nov1_ep13_2view						9.99 100	9.99 98		9.99 99	9.99 99		9.99 99		9.99 97		9.99 98

ACMMP++_ref															10000000.00 247

ACMMP++															10000000.00 247

Test By Simon												990.00 224

High-resolution multi-view benchmark