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.

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_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

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

liao1		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

liao		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

HC-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

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 12	0.37 17	0.37 23	0.37 24	0.37 22	0.32 24	0.37 22	0.37 23	0.37 21	0.37 23	0.37 23	0.37 21	0.37 21	0.37 23

v144192		0.40 13	0.40 13	0.40 18	0.40 24	0.40 25	0.40 23	0.40 25	0.40 23	0.40 24	0.40 22	0.40 24	0.40 24	0.40 22	0.40 22	0.40 24

v1921920		0.40 13	0.40 13	0.40 18	0.40 24	0.40 25	0.40 23	0.40 25	0.40 23	0.40 24	0.40 22	0.40 24	0.40 24	0.40 22	0.40 22	0.40 24

v1192		0.40 13	0.40 13	0.40 18	0.40 24	0.40 25	0.40 23	0.40 25	0.40 23	0.40 24	0.40 22	0.40 24	0.40 24	0.40 22	0.40 22	0.40 24

v1144		0.40 13	0.40 13	0.40 18	0.40 24	0.40 25	0.40 23	0.40 25	0.40 23	0.40 24	0.40 22	0.40 24	0.40 24	0.40 22	0.40 22	0.40 24

v148		0.40 13	0.40 13	0.40 18	0.40 24	0.40 25	0.40 23	0.40 25	0.40 23	0.40 24	0.40 22	0.40 24	0.40 24	0.40 22	0.40 22	0.40 24

v748		0.40 13	0.40 13	0.40 18	0.40 24	0.40 25	0.40 23	0.40 25	0.40 23	0.40 24	0.40 22	0.40 24	0.40 24	0.40 22	0.40 22	0.40 24

v7n		0.40 13	0.40 13	0.40 18	0.40 24	0.40 25	0.40 23	0.40 25	0.40 23	0.40 24	0.40 22	0.40 24	0.40 24	0.40 22	0.40 22	0.40 24

v1141		0.40 13	0.40 13	0.40 18	0.40 24	0.40 25	0.40 23	0.40 25	0.40 23	0.40 24	0.40 22	0.40 24	0.40 24	0.40 22	0.40 22	0.40 24

v1neww		0.40 13	0.40 13	0.40 18	0.40 24	0.40 25	0.40 23	0.40 25	0.40 23	0.40 24	0.40 22	0.40 24	0.40 24	0.40 22	0.40 22	0.40 24

v7new		0.40 13	0.40 13	0.40 18	0.40 24	0.40 25	0.40 23	0.40 25	0.40 23	0.40 24	0.40 22	0.40 24	0.40 24	0.40 22	0.40 22	0.40 24

v1240		0.40 13	0.40 13	0.40 18	0.40 24	0.40 25	0.40 23	0.40 25	0.40 23	0.40 24	0.40 22	0.40 24	0.40 24	0.40 22	0.40 22	0.40 24

v18		0.40 13	0.40 13	0.40 18	0.40 24	0.40 25	0.40 23	0.40 25	0.40 23	0.40 24	0.40 22	0.40 24	0.40 24	0.40 22	0.40 22	0.40 24

v17		0.40 13	0.40 13	0.40 18	0.40 24	0.40 25	0.40 23	0.40 25	0.40 23	0.40 24	0.40 22	0.40 24	0.40 24	0.40 22	0.40 22	0.40 24

v16		0.40 13	0.40 13	0.40 18	0.40 24	0.40 25	0.40 23	0.40 25	0.40 23	0.40 24	0.40 22	0.40 24	0.40 24	0.40 22	0.40 22	0.40 24

divwei89l23v2f112		0.40 13	0.40 13	0.40 18	0.40 24	0.40 25	0.40 23	0.40 25	0.40 23	0.40 24	0.40 22	0.40 24	0.40 24	0.40 22	0.40 22	0.40 24

v15		0.40 13	0.40 13	0.40 18	0.40 24	0.40 25	0.40 23	0.40 25	0.40 23	0.40 24	0.40 22	0.40 24	0.40 24	0.40 22	0.40 22	0.40 24

v13		0.40 13	0.40 13	0.40 18	0.40 24	0.40 25	0.40 23	0.40 25	0.40 23	0.40 24	0.40 22	0.40 24	0.40 24	0.40 22	0.40 22	0.40 24

v12		0.40 13	0.40 13	0.40 18	0.40 24	0.40 25	0.40 23	0.40 25	0.40 23	0.40 24	0.40 22	0.40 24	0.40 24	0.40 22	0.40 22	0.40 24

v8		0.40 13	0.40 13	0.40 18	0.40 24	0.40 25	0.40 23	0.40 25	0.40 23	0.40 24	0.40 22	0.40 24	0.40 24	0.40 22	0.40 22	0.40 24

v7		0.40 13	0.40 13	0.40 18	0.40 24	0.40 25	0.40 23	0.40 25	0.40 23	0.40 24	0.40 22	0.40 24	0.40 24	0.40 22	0.40 22	0.40 24

v6		0.40 13	0.40 13	0.40 18	0.40 24	0.40 25	0.40 23	0.40 25	0.40 23	0.40 24	0.40 22	0.40 24	0.40 24	0.40 22	0.40 22	0.40 24

v11		0.40 13	0.40 13	0.40 18	0.40 24	0.40 25	0.40 23	0.40 25	0.40 23	0.40 24	0.40 22	0.40 24	0.40 24	0.40 22	0.40 22	0.40 24

v52		0.40 13	0.40 13	0.40 18	0.40 24	0.40 25	0.40 23	0.40 25	0.40 23	0.40 24	0.40 22	0.40 24	0.40 24	0.40 22	0.40 22	0.40 24

V14		0.40 13	0.40 13	0.40 18	0.40 24	0.40 25	0.40 23	0.40 25	0.40 23	0.40 24	0.40 22	0.40 24	0.40 24	0.40 22	0.40 22	0.40 24

v10		0.40 13	0.40 13	0.40 18	0.40 24	0.40 25	0.40 23	0.40 25	0.40 23	0.40 24	0.40 22	0.40 24	0.40 24	0.40 22	0.40 22	0.40 24

V4		0.40 13	0.40 13	0.40 18	0.40 24	0.40 25	0.40 23	0.40 25	0.40 23	0.40 24	0.40 22	0.40 24	0.40 24	0.40 22	0.40 22	0.40 24

v2v482		0.40 13	0.40 13	0.40 18	0.40 24	0.40 25	0.40 23	0.40 25	0.40 23	0.40 24	0.40 22	0.40 24	0.40 24	0.40 22	0.40 22	0.40 24

v1		0.40 13	0.40 13	0.40 18	0.40 24	0.40 25	0.40 23	0.40 25	0.40 23	0.40 24	0.40 22	0.40 24	0.40 24	0.40 22	0.40 22	0.40 24

V42		0.40 13	0.40 13	0.40 18	0.40 24	0.40 25	0.40 23	0.40 25	0.40 23	0.40 24	0.40 22	0.40 24	0.40 24	0.40 22	0.40 22	0.40 24

V9		0.40 13	0.40 13	0.40 18	0.40 24	0.40 25	0.40 23	0.40 25	0.40 23	0.40 24	0.40 22	0.40 24	0.40 24	0.40 22	0.40 22	0.40 24

GA-MVS		0.40 13	0.40 13	0.40 18	0.40 24	0.40 25	0.40 23	0.40 25	0.40 23	0.40 24	0.40 22	0.40 24	0.40 24	0.40 22	0.40 22	0.40 24

CDS-MVSNet		0.88 44	0.88 44	0.88 49	0.88 55	0.88 56	0.88 54	0.88 56	0.88 54	0.88 55	0.88 53	0.88 55	0.88 55	0.88 53	0.88 53	0.88 55
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
TAMVS		0.88 44	0.88 44	0.88 49	0.88 55	0.88 56	0.88 54	0.88 56	0.88 54	0.88 55	0.88 53	0.88 55	0.88 55	0.88 53	0.88 53	0.88 55

LCM-MVSNet-Re		0.89 46	0.89 46	0.89 51	0.89 57	0.89 58	0.89 56	0.89 58	0.89 56	0.89 57	0.89 55	0.89 57	0.89 57	0.89 55	0.89 55	0.89 57

MDA-MVSNet-bldmvs		1.20 47	1.20 47	1.20 53	1.20 59	1.20 61	1.20 57	1.20 61	1.20 58	1.20 59	1.20 57	1.20 59	1.20 59	1.20 57	1.20 57	1.20 59

YYNet1		1.20 47	1.20 47	1.20 53	1.20 59	1.20 61	1.20 57	1.20 61	1.20 58	1.20 59	1.20 57	1.20 59	1.20 59	1.20 57	1.20 57	1.20 59

MDA-MVSNet_test_wron		1.20 47	1.20 47	1.20 53	1.20 59	1.20 61	1.20 57	1.20 61	1.20 58	1.20 59	1.20 57	1.20 59	1.20 59	1.20 57	1.20 57	1.20 59

EI-MVSNet-UG-set		1.42 50	1.42 50	1.42 56	1.42 62	1.42 64	1.42 60	1.42 64	1.42 61	1.42 62	1.42 60	1.42 62	1.42 62	1.42 60	1.42 60	1.42 62

EI-MVSNet-Vis-set		1.42 50	1.42 50	1.42 56	1.42 62	1.42 64	1.42 60	1.42 64	1.42 61	1.42 62	1.42 60	1.42 62	1.42 62	1.42 60	1.42 60	1.42 62

Regformer-3		1.42 50	1.42 50	1.42 56	1.42 62	1.42 64	1.42 60	1.42 64	1.42 61	1.42 62	1.42 60	1.42 62	1.42 62	1.42 60	1.42 60	1.42 62

Regformer-4		1.42 50	1.42 50	1.42 56	1.42 62	1.42 64	1.42 60	1.42 64	1.42 61	1.42 62	1.42 60	1.42 62	1.42 62	1.42 60	1.42 60	1.42 62

Regformer-1		1.42 50	1.42 50	1.42 56	1.42 62	1.42 64	1.42 60	1.42 64	1.42 61	1.42 62	1.42 60	1.42 62	1.42 62	1.42 60	1.42 60	1.42 62

Regformer-2		1.42 50	1.42 50	1.42 56	1.42 62	1.42 64	1.42 60	1.42 64	1.42 61	1.42 62	1.42 60	1.42 62	1.42 62	1.42 60	1.42 60	1.42 62

EI-MVSNet		1.42 50	1.42 50	1.42 56	1.42 62	1.42 64	1.42 60	1.42 64	1.42 61	1.42 62	1.42 60	1.42 62	1.42 62	1.42 60	1.42 60	1.42 62

Regformer		1.42 50	1.42 50	1.42 56	1.42 62	1.42 64	1.42 60	1.42 64	1.42 61	1.42 62	1.42 60	1.42 62	1.42 62	1.42 60	1.42 60	1.42 62

CVMVSNet		1.42 50	1.42 50	1.42 56	1.42 62	1.42 64	1.42 60	1.42 64	1.42 61	1.42 62	1.42 60	1.42 62	1.42 62	1.42 60	1.42 60	1.42 62

EU-MVSNet		1.42 50	1.42 50	1.42 56	1.42 62	1.42 64	1.42 60	1.42 64	1.42 61	1.42 62	1.42 60	1.42 62	1.42 62	1.42 60	1.42 60	1.42 62

PS-CasMVS		1.42 50	1.42 50	1.42 56	1.42 62	1.42 64	1.42 60	1.42 64	1.42 61	1.42 62	1.42 60	1.42 62	1.42 62	1.42 60	1.42 60	1.42 62

UniMVSNet_NR-MVSNet		1.42 50	1.42 50	1.42 56	1.42 62	1.42 64	1.42 60	1.42 64	1.42 61	1.42 62	1.42 60	1.42 62	1.42 62	1.42 60	1.42 60	1.42 62

PEN-MVS		1.42 50	1.42 50	1.42 56	1.42 62	1.42 64	1.42 60	1.42 64	1.42 61	1.42 62	1.42 60	1.42 62	1.42 62	1.42 60	1.42 60	1.42 62

TransMVSNet (Re)		1.42 50	1.42 50	1.42 56	1.42 62	1.42 64	1.42 60	1.42 64	1.42 61	1.42 62	1.42 60	1.42 62	1.42 62	1.42 60	1.42 60	1.42 62

DTE-MVSNet		1.42 50	1.42 50	1.42 56	1.42 62	1.42 64	1.42 60	1.42 64	1.42 61	1.42 62	1.42 60	1.42 62	1.42 62	1.42 60	1.42 60	1.42 62

DU-MVS		1.42 50	1.42 50	1.42 56	1.42 62	1.42 64	1.42 60	1.42 64	1.42 61	1.42 62	1.42 60	1.42 62	1.42 62	1.42 60	1.42 60	1.42 62

UniMVSNet (Re)		1.42 50	1.42 50	1.42 56	1.42 62	1.42 64	1.42 60	1.42 64	1.42 61	1.42 62	1.42 60	1.42 62	1.42 62	1.42 60	1.42 60	1.42 62

CP-MVSNet		1.42 50	1.42 50	1.42 56	1.42 62	1.42 64	1.42 60	1.42 64	1.42 61	1.42 62	1.42 60	1.42 62	1.42 62	1.42 60	1.42 60	1.42 62

WR-MVS_H		1.42 50	1.42 50	1.42 56	1.42 62	1.42 64	1.42 60	1.42 64	1.42 61	1.42 62	1.42 60	1.42 62	1.42 62	1.42 60	1.42 60	1.42 62

WR-MVS		1.42 50	1.42 50	1.42 56	1.42 62	1.42 64	1.42 60	1.42 64	1.42 61	1.42 62	1.42 60	1.42 62	1.42 62	1.42 60	1.42 60	1.42 62

NR-MVSNet		1.42 50	1.42 50	1.42 56	1.42 62	1.42 64	1.42 60	1.42 64	1.42 61	1.42 62	1.42 60	1.42 62	1.42 62	1.42 60	1.42 60	1.42 62

Baseline_NR-MVSNet		1.42 50	1.42 50	1.42 56	1.42 62	1.42 64	1.42 60	1.42 64	1.42 61	1.42 62	1.42 60	1.42 62	1.42 62	1.42 60	1.42 60	1.42 62

TranMVSNet+NR-MVSNet		1.42 50	1.42 50	1.42 56	1.42 62	1.42 64	1.42 60	1.42 64	1.42 61	1.42 62	1.42 60	1.42 62	1.42 62	1.42 60	1.42 60	1.42 62

MVSFormer		1.42 50	1.42 50	1.42 56	1.42 62	1.42 64	1.42 60	1.42 64	1.42 61	1.42 62	1.42 60	1.42 62	1.42 62	1.42 60	1.42 60	1.42 62

jason		1.42 50	1.42 50	1.42 56	1.42 62	1.42 64	1.42 60	1.42 64	1.42 61	1.42 62	1.42 60	1.42 62	1.42 62	1.42 60	1.42 60	1.42 62
jason: jason.
lupinMVS		1.42 50	1.42 50	1.42 56	1.42 62	1.42 64	1.42 60	1.42 64	1.42 61	1.42 62	1.42 60	1.42 62	1.42 62	1.42 60	1.42 60	1.42 62

test_djsdf		1.42 50	1.42 50	1.42 56	1.42 62	1.42 64	1.42 60	1.42 64	1.42 61	1.42 62	1.42 60	1.42 62	1.42 62	1.42 60	1.42 60	1.42 62

alignmvs		2.00 77	2.00 77	2.00 83	2.00 89	2.00 91	2.00 87	2.00 93	2.00 88	2.00 89	2.00 87	2.00 89	2.00 89	2.00 87	2.00 87	2.00 89

nrg030		2.00 77	2.00 77	2.00 83	2.00 89	2.00 91	2.00 87	2.00 93	2.00 88	2.00 89	2.00 87	2.00 89	2.00 89	2.00 87	2.00 87	2.00 89

LFMVS		2.00 77	2.00 77	2.00 83	2.00 89	2.00 91	2.00 87	2.00 93	2.00 88	2.00 89	2.00 87	2.00 89	2.00 89	2.00 87	2.00 87	2.00 89

VDD-MVS		2.00 77	2.00 77	2.00 83	2.00 89	2.00 91	2.00 87	2.00 93	2.00 88	2.00 89	2.00 87	2.00 89	2.00 89	2.00 87	2.00 87	2.00 89

VDDNet		2.00 77	2.00 77	2.00 83	2.00 89	2.00 91	2.00 87	2.00 93	2.00 88	2.00 89	2.00 87	2.00 89	2.00 89	2.00 87	2.00 87	2.00 89

VPNet		2.00 77	2.00 77	2.00 83	2.00 89	2.00 91	2.00 87	2.00 93	2.00 88	2.00 89	2.00 87	2.00 89	2.00 89	2.00 87	2.00 87	2.00 89

VNet		2.00 77	2.00 77	2.00 83	2.00 89	2.00 91	2.00 87	2.00 93	2.00 88	2.00 89	2.00 87	2.00 89	2.00 89	2.00 87	2.00 87	2.00 89

VPA-MVSNet		2.00 77	2.00 77	2.00 83	2.00 89	2.00 91	2.00 87	2.00 93	2.00 88	2.00 89	2.00 87	2.00 89	2.00 89	2.00 87	2.00 87	2.00 89

cascas		2.00 77	2.00 77	2.00 83	2.00 89	2.00 91	2.00 87	2.00 93	2.00 88	2.00 89	2.00 87	2.00 89	2.00 89	2.00 87	2.00 87	2.00 89

UnsupCasMVSNet_eth		5.90 86	5.90 86	5.90 92	5.90 98	5.90 100	5.90 97	5.90 103	5.90 98	5.90 98	5.90 96	5.90 99	5.90 98	5.90 96	5.90 98	5.90 99

UnsupCasMVSNet_bld		5.90 86	5.90 86	5.90 92	5.90 98	5.90 100	5.90 97	5.90 103	5.90 98	5.90 98	5.90 96	5.90 99	5.90 98	5.90 96	5.90 98	5.90 99

WTY-MVS		5.90 86	5.90 86	5.90 92	5.90 98	5.90 100	5.90 97	5.90 103	5.90 98	5.90 98	5.90 96	5.90 99	5.90 98	5.90 96	5.90 98	5.90 99

HY-MVS	5.90 1	5.90 86	5.90 86	5.90 92	5.90 98	5.90 100	5.90 97	5.90 103	5.90 98	5.90 98	5.90 96	5.90 99	5.90 98	5.90 96	5.90 98	5.90 99

sss		5.90 86	5.90 86	5.90 92	5.90 98	5.90 100	5.90 97	5.90 103	5.90 98	5.90 98	5.90 96	5.90 99	5.90 98	5.90 96	5.90 98	5.90 99

Test_1112_low_res		5.90 86	5.90 86	5.90 92	5.90 98	5.90 100	5.90 97	5.90 103	5.90 98	5.90 98	5.90 96	5.90 99	5.90 98	5.90 96	5.90 98	5.90 99

1112_ss		5.90 86	5.90 86	5.90 92	5.90 98	5.90 100	5.90 97	5.90 103	5.90 98	5.90 98	5.90 96	5.90 99	5.90 98	5.90 96	5.90 98	5.90 99

ab-mvs-re		5.90 86	5.90 86	5.90 92	5.90 98	5.90 100	5.90 97	5.90 103	5.90 98	5.90 98	5.90 96	5.90 99	5.90 98	5.90 96	5.90 98	5.90 99

ab-mvs		5.90 86	5.90 86	5.90 92	5.90 98	5.90 100	5.90 97	5.90 103	5.90 98	5.90 98	5.90 96	5.90 99	5.90 98	5.90 96	5.90 98	5.90 99

CDPH-MVS		6.66 95	6.66 95	6.66 101	6.66 107	6.66 109	6.66 106	6.66 112	6.66 107	6.66 107	6.66 105	6.66 108	6.66 107	6.66 105	6.66 107	6.66 108

cdsmvs_eth3d_5k		10.28 96	10.28 97	10.28 103	10.28 109	10.28 113	10.28 109	10.28 115	10.28 110	10.28 111	10.28 107	10.28 111	10.28 110	10.28 108	10.28 109	10.28 110

pcd_1.5k_mvsjas		10.28 96	10.28 97	10.28 103	10.28 109	10.28 113	10.28 109	10.28 115	10.28 110	10.28 111	10.28 107	10.28 111	10.28 110	10.28 108	10.28 109	10.28 110

pcd1.5k->3k		10.28 96	10.28 97	10.28 103	10.28 109	10.28 113	10.28 109	10.28 115	10.28 110	10.28 111	10.28 107	10.28 111	10.28 110	10.28 108	10.28 109	10.28 110

PS-MVSNAJss		10.28 96	10.28 97	10.28 103	10.28 109	10.28 113	10.28 109	10.28 115	10.28 110	10.28 111	10.28 107	10.28 111	10.28 110	10.28 108	10.28 109	10.28 110

PS-MVSNAJ		10.28 96	10.28 97	10.28 103	10.28 109	10.28 113	10.28 109	10.28 115	10.28 110	10.28 111	10.28 107	10.28 111	10.28 110	10.28 108	10.28 109	10.28 110

jajsoiax		10.28 96	10.28 97	10.28 103	10.28 109	10.28 113	10.28 109	10.28 115	10.28 110	10.28 111	10.28 107	10.28 111	10.28 110	10.28 108	10.28 109	10.28 110

mvs_tets		10.28 96	10.28 97	10.28 103	10.28 109	10.28 113	10.28 109	10.28 115	10.28 110	10.28 111	10.28 107	10.28 111	10.28 110	10.28 108	10.28 109	10.28 110

XXY-MVS		15.00 103	15.00 104	15.00 110	15.00 117	15.00 120	15.00 116	15.00 123	15.00 117	15.00 118	15.00 114	15.00 119	15.00 117	15.00 116	15.00 117	15.00 118

BH-w/o		40.00 104	40.00 105	40.00 112	40.00 118	40.00 121	40.00 117	40.00 138	40.00 118	40.00 120	40.00 115	40.00 135	40.00 119	40.00 117	40.00 127	40.00 126

BH-untuned		40.00 104	40.00 105	40.00 112	40.00 118	40.00 121	40.00 117	40.00 138	40.00 118	40.00 120	40.00 115	40.00 135	40.00 119	40.00 117	40.00 127	40.00 126

BH-RMVSNet		40.00 104	40.00 105	40.00 112	40.00 118	40.00 121	40.00 117	40.00 138	40.00 118	40.00 120	40.00 115	40.00 135	40.00 119	40.00 117	40.00 127	40.00 126

TR-MVS		40.00 104	40.00 105	40.00 112	40.00 118	40.00 121	40.00 117	40.00 138	40.00 118	40.00 120	40.00 115	40.00 135	40.00 119	40.00 117	40.00 127	40.00 126

GBi-Net		44.67 108	49.24 109	30.96 111	47.53 122	47.57 125	126.09 121	8.00 113	76.99 122	26.09 119	73.50 120	11.27 118	30.55 118	61.12 121	12.58 116	14.75 117

dp		87.20 109	113.80 112	7.42 102	10.50 116	8.88 110	298.82 125	2.70 102	510.35 139	7.79 108	172.93 123	3.37 98	9.16 108	14.00 115	3.71 97	4.23 98

new_pmnet		88.14 110	98.62 110	56.70 116	98.14 124	56.07 126	246.79 123	15.37 124	148.06 123	50.77 124	143.13 121	23.35 120	62.65 123	93.26 122	68.71 134	51.38 135

N_pmnet		88.14 110	98.62 110	56.70 116	98.14 124	56.07 126	246.79 123	15.37 124	148.06 123	50.77 124	143.13 121	23.35 120	62.65 123	93.26 122	68.71 134	51.38 135

UGNet		110.62 112	124.04 113	70.34 118	82.03 123	74.27 128	325.54 126	25.25 127	207.16 125	69.28 126	194.38 124	27.53 122	95.79 133	147.76 126	37.43 119	40.97 130
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
FMVSNet5		124.76 113	140.93 114	76.26 120	107.44 127	100.17 134	329.88 127	27.12 131	259.44 130	74.30 127	204.34 125	30.74 123	92.41 125	196.98 128	38.15 120	36.19 119

test1		124.76 113	140.93 114	76.26 120	107.44 127	100.17 134	329.88 127	27.12 131	259.44 130	74.30 127	204.34 125	30.74 123	92.41 125	196.98 128	38.15 120	36.19 119

FMVSNet3		124.76 113	140.93 114	76.26 120	107.44 127	100.17 134	329.88 127	27.12 131	259.44 130	74.30 127	204.34 125	30.74 123	92.41 125	196.98 128	38.15 120	36.19 119

FMVSNet2		124.76 113	140.93 114	76.26 120	107.44 127	100.17 134	329.88 127	27.12 131	259.44 130	74.30 127	204.34 125	30.74 123	92.41 125	196.98 128	38.15 120	36.19 119

FMVSNet1		124.76 113	140.93 114	76.26 120	107.44 127	100.17 134	329.88 127	27.12 131	259.44 130	74.30 127	204.34 125	30.74 123	92.41 125	196.98 128	38.15 120	36.19 119

MIMVSNet1		124.76 113	140.93 114	76.26 120	107.44 127	100.17 134	329.88 127	27.12 131	259.44 130	74.30 127	204.34 125	30.74 123	92.41 125	196.98 128	38.15 120	36.19 119

MIMVSNet		124.76 113	140.93 114	76.26 120	107.44 127	100.17 134	329.88 127	27.12 131	259.44 130	74.30 127	204.34 125	30.74 123	92.41 125	196.98 128	38.15 120	36.19 119

DSMNet-mixed		131.33 120	143.00 121	96.33 130	99.00 126	81.00 129	201.00 122	45.00 142	335.00 137	99.00 138	251.00 136	38.00 134	110.00 137	120.00 125	99.00 136	98.00 137

PVSNet_Blended_VisFu		136.90 121	155.40 122	81.40 127	111.00 134	96.20 131	407.00 134	25.90 128	251.60 127	85.10 135	240.50 133	37.00 131	99.90 134	199.80 135	40.70 131	48.10 132

PVSNet_BlendedMVS		136.90 121	155.40 122	81.40 127	111.00 134	96.20 131	407.00 134	25.90 128	251.60 127	85.10 135	240.50 133	37.00 131	99.90 134	199.80 135	40.70 131	48.10 132

PVSNet_Blended		136.90 121	155.40 122	81.40 127	111.00 134	96.20 131	407.00 134	25.90 128	251.60 127	85.10 135	240.50 133	37.00 131	99.90 134	199.80 135	40.70 131	48.10 132

DP-MVS		264.78 124	296.02 125	171.04 131	191.70 137	183.96 141	827.10 142	78.36 144	438.24 138	176.64 139	435.12 137	65.04 140	230.52 140	334.02 138	117.96 137	98.64 138

HyFIR lowres test		317.00 125	397.69 126	74.93 119	1190.04 185	86.11 130	1576.45 159	22.83 126	228.70 126	78.08 134	225.04 132	33.24 130	94.29 132	187.60 127	37.22 118	44.39 131

DUST3R		371.08 126	412.78 127	246.00 133	231.00 138	197.00 142	1293.00 153	376.00 186	756.00 145	609.00 169	71.00 119	106.00 149	195.00 138	102.00 124	171.00 147	346.00 167

RPSCF		394.81 127	445.63 128	242.35 132	276.55 140	253.63 143	1207.27 151	90.69 149	715.56 143	241.57 141	684.87 141	111.96 150	320.02 141	548.38 144	133.81 139	153.39 140

EG-PatchMatch MVS		437.03 128	493.12 131	268.77 134	264.80 139	260.20 144	1491.80 156	98.00 153	723.20 144	238.80 140	722.40 142	63.10 139	382.00 144	629.00 146	207.00 154	164.10 144

ADS-MVSNet2		443.33 129	482.84 129	324.79 142	434.94 152	387.73 152	1110.57 149	87.69 147	887.02 149	282.92 142	779.29 143	98.57 147	422.76 149	502.40 139	162.19 145	163.87 142

ADS-MVSNet		443.33 129	482.84 129	324.79 142	434.94 152	387.73 152	1110.57 149	87.69 147	887.02 149	282.92 142	779.29 143	98.57 147	422.76 149	502.40 139	162.19 145	163.87 142

MVP-PatchMatch		473.58 131	533.67 132	293.33 135	376.00 144	318.00 145	1461.00 154	96.00 150	835.00 147	290.00 145	804.00 147	97.00 145	383.00 146	688.00 153	156.00 140	179.00 146

MS-PatchMatch		473.58 131	533.67 132	293.33 135	376.00 144	318.00 145	1461.00 154	96.00 150	835.00 147	290.00 145	804.00 147	97.00 145	383.00 146	688.00 153	156.00 140	179.00 146

PatchmatchNet		492.52 133	551.22 134	316.40 139	400.20 148	357.90 150	1277.10 152	115.80 158	1034.60 158	315.90 147	874.00 150	155.10 156	402.20 148	629.50 147	158.80 142	189.10 148
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
LP		495.57 134	552.82 135	323.82 141	377.78 146	343.94 148	1099.61 148	67.44 143	1450.39 168	417.42 153	790.39 145	130.18 153	472.61 152	519.53 143	122.60 138	154.91 141

tpmvs		501.65 135	567.42 136	304.33 138	395.39 147	356.32 149	1512.04 157	216.53 179	994.15 152	350.16 150	804.16 149	119.38 151	380.98 143	555.14 145	159.87 143	175.69 145

DELS-MVS		514.57 136	587.73 138	295.12 137	343.03 141	328.09 147	1540.48 158	116.22 159	988.59 151	325.44 148	906.22 151	119.86 152	365.72 142	788.60 155	161.09 144	191.55 149
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		516.25 137	581.17 137	321.48 140	361.02 142	429.00 156	1995.36 163	78.48 145	796.20 146	283.32 144	796.02 146	96.78 144	382.98 145	636.72 148	186.66 151	152.46 139

gg-mvs-nofinetune		594.69 138	605.37 139	562.67 157	617.29 163	500.33 160	772.30 139	413.12 191	579.21 140	552.71 164	567.40 138	662.54 203	531.67 154	503.93 141	779.80 185	656.02 180

CR-MVSNet		612.36 139	617.81 140	596.01 160	611.29 161	600.33 168	790.30 140	513.12 200	579.21 140	552.71 164	567.40 138	662.54 203	531.67 154	503.93 141	779.80 185	656.02 180

IterMVS		615.05 140	691.66 141	385.23 146	516.40 155	454.80 157	1863.80 161	102.10 155	1142.20 160	364.10 151	1093.20 163	135.00 154	480.40 153	826.90 156	181.20 148	220.50 151
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
IB-MVS	872.44 4	616.41 141	700.96 142	362.78 144	426.10 151	409.25 154	1822.69 160	124.42 163	1186.23 161	366.85 152	1079.42 161	190.60 164	451.78 151	930.72 160	181.59 149	227.30 152
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	661.38 142	754.00 143	383.51 145	368.96 143	376.38 151	2483.74 170	82.42 146	1089.25 159	333.39 149	1219.68 164	66.53 141	573.60 160	957.86 161	184.14 150	200.56 150

Gipuma		689.75 143	767.00 144	458.00 150	613.00 162	549.00 166	1943.00 162	187.00 176	1230.00 162	518.00 161	1092.00 162	203.00 170	564.00 157	892.00 159	225.00 158	261.00 155
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
IterMVS-LS		758.94 144	856.56 147	466.10 151	606.60 159	546.80 164	2309.90 165	122.20 162	1402.80 166	463.50 156	1348.20 166	192.60 165	574.60 161	1028.60 168	234.60 160	276.90 157
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
SixPastTwentyTwo		773.62 145	869.37 149	486.35 153	603.45 158	547.15 165	2532.14 171	106.92 157	1434.95 167	428.08 154	1360.56 167	165.15 159	628.96 163	984.09 162	209.01 155	282.94 158

mvs_anonymous		774.90 146	882.28 150	452.77 148	636.50 164	537.20 162	2348.80 166	120.30 160	1504.30 169	474.40 157	1371.10 168	186.90 161	564.70 158	1078.90 170	219.30 156	256.40 153

diffmvs		774.90 146	882.28 150	452.77 148	636.50 164	537.20 162	2348.80 166	120.30 160	1504.30 169	474.40 157	1371.10 168	186.90 161	564.70 158	1078.90 170	219.30 156	256.40 153

JIA-IIPM		804.30 148	835.64 145	710.26 168	885.90 174	895.90 184	455.98 137	668.73 205	1297.17 163	1002.26 188	1001.67 159	655.98 201	756.98 167	667.90 150	885.21 195	477.90 176

RPMNet		804.30 148	835.64 145	710.26 168	885.90 174	895.90 184	455.98 137	668.73 205	1297.17 163	1002.26 188	1001.67 159	655.98 201	756.98 167	667.90 150	885.21 195	477.90 176

CSCG		826.03 150	963.29 153	414.24 147	421.52 150	426.11 155	2230.35 164	179.52 175	1827.44 176	733.43 178	933.12 153	281.25 177	545.23 156	1800.35 182	262.64 162	271.38 156

PVSNet	1207.94 6	829.56 151	937.18 152	506.69 154	645.55 166	585.72 167	2477.98 169	130.52 164	1578.29 172	509.50 160	1460.01 170	194.90 166	637.19 164	1170.78 173	267.07 164	297.17 160

PatchT		856.34 152	860.99 148	842.38 174	1290.90 188	880.90 182	790.30 140	1267.30 223	579.21 140	923.90 180	567.40 138	662.54 203	990.23 176	887.56 158	779.80 185	656.02 180

K. test v3		877.74 153	980.16 154	570.46 159	1316.85 190	813.15 179	2565.52 172	103.78 156	1509.49 171	548.33 163	1258.90 165	219.93 175	587.82 162	1102.37 172	196.30 152	310.42 162

MVSTER		890.06 154	1005.91 160	542.52 155	736.13 171	653.90 171	2616.56 173	145.22 169	1692.10 175	555.69 166	1554.72 172	266.25 176	660.02 165	1219.66 174	266.84 163	313.64 163

PMVS	863.65 3	957.08 155	1054.11 161	666.00 165	401.00 149	495.00 159	3790.00 178	279.00 181	1607.00 174	521.00 162	1745.00 174	90.00 142	1105.00 185	639.00 149	415.00 175	398.00 174
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
ACMH	993.80 5	967.92 156	1106.11 163	553.33 156	494.00 154	534.00 161	3581.00 176	136.00 165	1585.00 173	478.00 159	1871.00 175	90.00 142	839.00 170	1460.00 176	260.00 161	287.00 159
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
PVSNet_0	1661.03 9	968.54 157	1066.82 162	673.70 166	706.94 169	695.69 172	2669.02 174	153.52 171	2108.17 181	605.54 168	1679.14 173	213.26 174	886.75 173	1236.76 175	229.01 159	438.67 175

OurMVSNet-221017-0		999.00 158	999.00 155	999.00 175	999.00 179	999.00 186	999.00 143	999.00 218	999.00 153	999.00 183	999.00 154	999.00 211	999.00 178	999.00 163	999.00 201	999.00 201

EPMVS		999.00 158	999.00 155	999.00 175	999.00 179	999.00 186	999.00 143	999.00 218	999.00 153	999.00 183	999.00 154	999.00 211	999.00 178	999.00 163	999.00 201	999.00 201

sosnet		1000.00 160	1000.00 157	1000.00 177	1000.00 181	1000.00 188	1000.00 145	1000.00 220	1000.00 155	1000.00 185	1000.00 156	1000.00 213	1000.00 180	1000.00 165	1000.00 203	1000.00 203

USDC		1000.00 160	1000.00 157	1000.00 177	1000.00 181	1000.00 188	1000.00 145	1000.00 220	1000.00 155	1000.00 185	1000.00 156	1000.00 213	1000.00 180	1000.00 165	1000.00 203	1000.00 203

TinyColmap		1000.00 160	1000.00 157	1000.00 177	1000.00 181	1000.00 188	1000.00 145	1000.00 220	1000.00 155	1000.00 185	1000.00 156	1000.00 213	1000.00 180	1000.00 165	1000.00 203	1000.00 203

ACMP	1246.57 7	1086.24 163	1235.17 165	639.45 161	596.53 157	639.91 169	3904.24 179	152.04 170	1851.54 177	566.58 167	1997.95 177	138.50 155	938.30 174	1605.46 178	303.70 170	340.14 165
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
Patchmtry		1090.75 164	1198.88 164	766.38 173	1290.90 188	485.90 158	2423.98 168	1267.30 223	1297.17 163	923.90 180	923.40 152	1215.54 217	990.23 176	667.90 150	779.80 185	823.02 189

test_0402		1110.00 165	1260.00 166	660.00 163	900.00 177	780.00 178	3300.00 175	210.00 178	2040.00 180	690.00 173	1950.00 176	300.00 180	810.00 169	1620.00 179	330.00 171	390.00 173

MVS_111021_LR		1136.45 166	1298.72 167	649.64 162	756.17 172	726.26 175	3785.94 177	138.15 167	2190.64 182	629.63 171	2064.39 178	165.45 160	874.83 172	1678.43 181	279.70 165	347.82 168

ACMM	1311.08 8	1165.06 167	1332.72 168	662.07 164	584.90 156	715.99 174	4373.59 183	153.99 172	1880.27 178	709.02 175	2316.97 179	188.63 163	939.89 175	1484.30 177	302.78 169	330.34 164
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
MSLP-MVS		1242.93 168	1411.08 169	738.48 171	712.71 170	712.68 173	4168.17 181	136.50 166	2276.40 183	613.28 170	2368.60 182	161.61 158	1130.38 186	1964.54 185	297.88 167	372.39 170

MG-MVS		1256.50 169	1432.00 170	730.00 170	610.00 160	760.00 176	4720.00 184	169.00 173	1920.00 179	723.00 177	2510.00 185	201.00 168	1050.00 183	1645.00 180	390.00 174	380.00 171

ACMMPR		1296.60 170	1480.82 171	743.96 172	899.25 176	763.47 177	4305.47 182	143.90 168	2530.94 186	683.99 172	2346.34 181	201.65 169	1098.25 184	1920.59 184	295.21 166	370.16 169

TSAR-MVS		1386.84 171	1622.84 173	678.81 167	952.13 178	840.17 181	5358.21 187	170.75 174	2650.47 187	713.54 176	2394.28 183	209.42 173	855.56 171	1854.36 183	302.42 168	340.71 166

FPMVS		1407.00 172	1495.59 172	1141.23 181	648.01 167	893.85 183	4124.00 180	503.81 199	3219.04 189	742.72 179	2498.84 184	157.98 157	1727.83 191	832.93 157	732.98 184	802.00 186

DeepC-MVS_fast	2190.19 12	1535.59 173	1886.82 175	481.89 152	847.73 173	830.16 180	7943.84 201	189.23 177	2398.83 184	691.73 174	2341.13 180	209.16 172	230.25 139	1999.25 186	360.46 172	385.25 172
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
COLMAP_ROB	2144.59 11	1658.33 174	1869.33 174	1025.33 180	1030.00 184	1023.00 191	5311.00 186	359.00 184	3044.00 188	937.00 182	2892.00 186	332.00 181	1440.00 188	2312.00 187	607.00 176	613.00 179
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	2113.11 176	1173.33 184	1231.00 186	1174.00 192	6297.00 189	392.00 188	3356.00 191	1087.00 190	3082.00 187	361.00 185	1670.00 190	2523.00 189	689.00 179	676.00 183

OpenMVS_ROB	1936.51 10	1959.51 176	2224.88 178	1163.39 183	1253.91 187	1434.22 195	7065.71 191	272.76 180	2472.29 185	1647.54 211	3538.72 190	200.37 167	1496.48 189	2575.17 190	997.45 200	559.48 178

CMPMVS	2623.62 15	1983.08 177	2156.14 177	1463.89 191	1414.80 192	1517.00 197	5239.20 185	867.40 211	3310.30 190	1128.70 192	3489.90 189	366.75 186	2030.20 198	2427.60 188	1160.60 207	844.46 192
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
MVS-HIRNet		2125.39 178	2452.68 179	1143.53 182	2938.33 214	1446.92 196	6083.19 188	391.74 187	3801.71 193	1202.10 194	3439.72 188	492.73 191	1304.35 187	3048.25 193	676.32 178	679.32 184

PLC	2858.82 16	2192.92 179	2474.00 180	1349.67 186	1407.00 191	1356.00 194	7164.00 192	475.00 197	3970.00 194	1237.00 196	3765.00 193	451.00 188	1891.00 194	3006.00 192	791.00 189	802.00 186
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
OpenMVS	2352.88 13	2263.08 180	2530.89 181	1459.67 190	1767.00 198	1591.00 200	7932.00 200	399.00 189	3643.00 192	1176.00 193	3569.00 191	297.00 179	1927.00 196	3302.00 194	693.00 181	861.00 193

PCF-MVS	4335.85 20	2272.23 181	2597.03 182	1297.84 185	1701.20 194	1332.37 193	8105.11 202	451.45 193	4031.84 195	1099.10 191	3966.50 194	467.45 189	1734.05 192	2701.68 191	848.94 192	827.11 190
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
HyFIR		2340.81 182	2643.03 183	1434.14 187	2025.55 208	1629.36 202	6542.40 190	412.49 190	4219.70 196	1547.02 205	4328.52 196	650.74 200	1798.26 193	3333.17 195	727.72 183	874.79 194

3Dnovator	2482.06 14	2531.17 183	2839.56 184	1606.00 192	1732.00 196	1557.00 199	8375.00 204	483.00 198	4370.00 197	1371.00 200	4200.00 195	350.00 183	2207.00 199	3877.00 199	798.00 190	1054.00 206

tpmrst		2557.50 184	2847.12 185	1688.66 195	1784.08 199	1778.25 211	7445.50 198	342.14 183	4471.54 198	1534.55 204	4382.10 197	530.10 194	2361.21 202	4142.81 201	991.22 199	926.51 197

AdaColmap		2570.77 185	2948.61 186	1437.24 188	1873.64 200	1526.60 198	7819.77 199	373.97 185	4970.45 201	1479.29 202	4648.46 199	525.80 193	1904.97 195	4150.42 202	695.69 182	880.14 195

SD-MVS		2654.53 186	3055.56 189	1451.45 189	1725.60 195	1598.35 201	9203.30 208	315.86 182	5016.02 203	1363.85 199	4894.28 201	387.23 187	2023.43 197	3973.88 200	620.04 177	732.56 185

DeepPCF-MVS	3452.42 18	2670.71 187	3021.57 187	1618.12 193	2377.67 210	1751.39 210	8915.70 207	567.44 202	4569.74 199	1236.84 195	4615.63 198	513.23 192	2291.32 200	3515.48 196	882.39 194	811.66 188

LF4IMVS		2699.50 188	3049.67 188	1649.00 194	1755.00 197	1689.00 204	8330.00 203	464.00 195	4997.00 202	1528.00 203	4763.00 200	568.00 196	2296.00 201	4215.00 203	827.00 191	962.00 199

Vis-MVSNet		2877.42 189	3170.00 190	1999.67 200	1673.00 193	2042.00 215	8593.00 205	474.00 196	6452.00 213	1268.00 197	5125.00 202	339.00 182	3004.00 209	4222.00 204	384.00 173	953.00 198
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
SteuartSystems-ACMMP		2891.50 190	3284.78 191	1711.67 196	1954.00 201	1655.00 203	10117.00 213	445.00 192	5102.00 204	1375.00 201	5126.00 203	351.00 184	2638.00 206	4402.00 205	691.00 180	842.00 191
Skip Steuart: Steuart Systems R&D Blog.
3Dnovator+	3414.41 17	3146.67 191	3537.00 192	1975.67 198	2310.00 209	2005.00 214	10100.00 212	626.00 204	5753.00 205	1803.00 213	5179.00 204	487.00 190	2622.00 205	4550.00 206	1025.00 206	1300.00 209

DeepC-MVS	3917.13 19	3155.06 192	3601.83 193	1814.72 197	2515.52 212	1941.53 212	10432.50 214	589.42 203	4789.45 200	1298.65 198	7677.31 209	578.35 197	2589.53 203	3611.78 198	923.52 197	913.10 196
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	3374.90 193	3806.99 194	2078.63 202	2535.47 213	2499.25 217	8816.16 206	456.05 194	6255.60 212	1664.52 212	6704.88 207	629.95 198	2768.38 207	6343.93 210	856.35 193	968.25 200
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
tpm2		3617.85 194	4007.23 195	2449.73 203	2012.71 203	1698.05 205	7351.19 193	869.29 212	6132.06 207	1588.28 206	8007.42 210	1281.09 218	3888.11 213	7472.04 213	1351.00 209	1763.02 214

tpm cat1		3617.85 194	4007.23 195	2449.73 203	2012.71 203	1698.05 205	7351.19 193	869.29 212	6132.06 207	1588.28 206	8007.42 210	1281.09 218	3888.11 213	7472.04 213	1351.00 209	1763.02 214

tpmp4_e23		3617.85 194	4007.23 195	2449.73 203	2012.71 203	1698.05 205	7351.19 193	869.29 212	6132.06 207	1588.28 206	8007.42 210	1281.09 218	3888.11 213	7472.04 213	1351.00 209	1763.02 214

CostFormer		3617.85 194	4007.23 195	2449.73 203	2012.71 203	1698.05 205	7351.19 193	869.29 212	6132.06 207	1588.28 206	8007.42 210	1281.09 218	3888.11 213	7472.04 213	1351.00 209	1763.02 214

tpm		3617.85 194	4007.23 195	2449.73 203	2012.71 203	1698.05 205	7351.19 193	869.29 212	6132.06 207	1588.28 206	8007.42 210	1281.09 218	3888.11 213	7472.04 213	1351.00 209	1763.02 214

MVS_111021_HR		3742.80 199	4330.34 200	1980.20 199	2484.31 211	2259.52 216	14973.80 218	515.90 201	6500.13 214	1949.21 215	6146.89 205	535.66 195	2593.66 204	4880.76 208	986.37 198	1087.43 207

MAR-MVS		3973.16 200	4387.92 201	2728.86 208	3345.27 215	3341.39 220	11403.90 215	798.76 209	6555.62 216	2569.29 216	6514.86 206	834.97 209	3237.43 210	5891.08 209	1577.54 215	1607.76 210
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		4380.83 201	4906.56 202	2803.67 209	3844.00 216	3116.00 219	13454.00 216	901.00 217	6511.00 215	2794.00 217	7365.00 208	754.00 206	3634.00 211	6622.00 211	1914.00 217	1661.00 213

OMC-MVS		5022.26 202	5748.82 203	2842.58 210	4905.27 218	3101.27 218	14933.60 217	812.24 210	9278.40 217	2959.29 218	8800.17 215	1092.24 216	3806.30 212	7568.54 218	1389.60 214	1620.18 212

CLD-MVS		7338.25 203	8341.00 204	4330.00 211	4902.00 217	4991.00 221	23318.00 220	728.00 208	14437.00 223	4378.00 220	13379.00 219	824.00 208	5708.00 218	11429.00 223	1674.00 216	2291.00 219
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
LS3D		7684.71 204	8776.23 205	4410.16 212	5298.55 219	5631.53 222	34329.90 222	1504.57 225	11554.00 222	3896.41 219	15111.00 220	812.19 207	5985.63 219	3516.20 197	2963.23 218	1613.31 211

UA-Net		10000.00 205	10000.00 206	10000.00 214	10000.00 222	10000.00 225	10000.00 209	10000.00 230	10000.00 218	10000.00 223	10000.00 216	10000.00 225	10000.00 220	10000.00 219	10000.00 221	10000.00 222

uncertanet		10000.00 205	10000.00 206	10000.00 214	10000.00 222	10000.00 225	10000.00 209	10000.00 230	10000.00 218	10000.00 223	10000.00 216	10000.00 225	10000.00 220	10000.00 219	10000.00 221	10000.00 222

uanet		10000.00 205	10000.00 206	10000.00 214	10000.00 222	10000.00 225	10000.00 209	10000.00 230	10000.00 218	10000.00 223	10000.00 216	10000.00 225	10000.00 220	10000.00 219	10000.00 221	10000.00 222

MVE	10021.00 22	10550.67 208	10002.44 209	12195.33 217	6242.00 220	8768.00 224	30896.00 221	4451.00 227	10331.00 221	6247.00 221	18296.00 221	283.00 178	21484.00 224	7364.00 212	5912.00 220	6334.00 221
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
CNLPA		10738.67 209	11772.44 210	7637.33 213	9120.00 221	8206.00 223	22252.00 219	2010.00 226	24984.00 224	7458.00 222	22596.00 222	2940.00 223	10260.00 223	11100.00 222	3492.00 219	4446.00 220

LTVRE_ROB	20565.47 23	23378.08 210	22805.00 211	25097.33 218	15500.00 225	19201.00 228	42712.00 223	6055.00 228	38388.00 225	16926.00 226	38534.00 223	7071.00 224	35653.00 225	29475.00 224	10584.00 224	20438.00 226
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		32606.17 211	34443.44 212	27094.33 219	29249.00 226	25246.00 229	51144.00 224	6705.00 229	42886.00 226	22888.00 227	48534.00 224	13263.00 228	37507.00 226	79298.00 225	16024.00 225	18530.00 225

114514_t		99999.00 212	99999.00 213	99999.00 220	99999.00 227	99999.00 230	99999.00 225	99999.00 233	99999.00 227	99999.00 228	99999.00 225	99999.00 229	99999.00 227	99999.00 226	99999.00 226	99999.00 227

PHI-MVS		99999.00 212	99999.00 213	99999.00 220	99999.00 227	99999.00 230	99999.00 225	99999.00 233	99999.00 227	99999.00 228	99999.00 225	99999.00 229	99999.00 227	99999.00 226	99999.00 226	99999.00 227

XVG-OURS-SEG-HR		999999.00 214	999999.00 215	999999.00 222	999999.00 229	999999.00 232	999999.00 227	999999.00 235	999999.00 229	999999.00 230	999999.00 227	999999.00 231	999999.00 229	999999.00 228	999999.00 228	999999.00 229

XVG-OURS		999999.00 214	999999.00 215	999999.00 222	999999.00 229	999999.00 232	999999.00 227	999999.00 235	999999.00 229	999999.00 230	999999.00 227	999999.00 231	999999.00 229	999999.00 228	999999.00 228	999999.00 229

XVG-ACMP-BASELINE		999999.00 214	999999.00 215	999999.00 222	999999.00 229	999999.00 232	999999.00 227	999999.00 235	999999.00 229	999999.00 230	999999.00 227	999999.00 231	999999.00 229	999999.00 228	999999.00 228	999999.00 229

Anonymous20231206		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

Patchmatch-RL test		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

canonicalmvs		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

FIs		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

FC-MVSNet-test		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

sosnet-low-res		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

AllTest		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

testing_2		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

DI_MVS_test_normal		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

HPM-MVS++		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

XVS		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

pm-mvs1		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

X-MVStestdata		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

APDe-MVS		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

APD-MVS_3200maxsize		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

test-LLR		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

TESTMET0.1,1		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

test-mter		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

testgi		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

test20.03		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

1111		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

.test1245		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

MP-MVS		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

testmvs		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

test123		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

test0.0.03 1		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

test12356		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

testus		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

pmmvs3		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

testmv		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

EMVS		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

E-PMN		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

test2356		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

test1235678		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

PGM-MVS		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

MCST-MVS		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

MVS_Test		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

PMMVS2		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

PM-MVS		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

HQP_MVS		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

mPP-MVS		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

DI_MVS_test_dynamic		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

DWT-MVSNet_test		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

Test4		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

HPM-MVS_fast		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

PatchFormer-LS_test		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

testpf		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

HPM-MVS		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

LPG-MVS_test		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

EPNet_dtu		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
EPNet		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CNVR-MVS		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

NCCC		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

CP-MVS		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

no-one		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

CPTT-MVS		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

HQP-MVS		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

IS-MVSNet		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

PAPM_NR		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

PAPR		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

Vis-MVSNet (Re-imp)		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

PatchMatch-RL		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

TDRefinement		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

EPP-MVSNet		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

PMMVS		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

PAPM		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

ACMMP		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232
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		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

PNet_i23d		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

wuyk23d		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

wuykxyi23d		10000000.00 217	10000000.00 218	10000000.00 225	10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

APD-MVS		1000000000.00 288	1000000000.00 289	1000000000.00 298	1000000000.00 313	1000000000.00 315	1000000000.00 305	1000000000.00 314	1000000000.00 309	1000000000.00 311	1000000000.00 307	1000000000.00 310	1000000000.00 307	1000000000.00 306	1000000000.00 309	1000000000.00 307
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
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

Patchmatch-test1					10000000.00 232	10000000.00 235	10000000.00 230	10000000.00 238		10000000.00 233	10000000.00 230	10000000.00 234			10000000.00 231

Patchmatch-test					10000000.00 232	10000000.00 235					10000000.00 230

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				10000000.00 225	10000000.00 232	10000000.00 235		10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

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					10000000.00 232	10000000.00 235

plane_prior6					10000000.00 232	10000000.00 235						10000000.00 234

plane_prior5								10000000.00 238					10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

plane_prior4											10000000.00 230

plane_prior3						10000000.00 235			10000000.00 232	10000000.00 233

plane_prior2							10000000.00 230		10000000.00 232

plane_prior1					10000000.00 232

plane_prior						1.00 59	2.00 87		2.00 88						2.00 87

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

n2								14.20 122

nn								1.42 64

door-mid								1.42 64

lessismore_v0				569.20 158	667.25 168	644.68 170		96.45 152		428.86 155	1514.17 171	204.21 171	756.58 166	1061.60 169	197.79 153	306.34 161

LGP-MVS_train				10000000.00 225	10000000.00 232	10000000.00 235		10000000.00 238	10000000.00 232	10000000.00 233	10000000.00 230	10000000.00 234	10000000.00 232	10000000.00 231	10000000.00 231	10000000.00 232

test11								1.00 59

door								99.00 154

HQP5-MVS						10000000.00 235

HQP-NCC					10000000.00 232		10000000.00 230		10000000.00 232	10000000.00 233

ACMP_Plane					10000000.00 232		10000000.00 230		10000000.00 232	10000000.00 233

High-resolution multi-view benchmark