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	courty.	delive.	electro	facade	kicker	meadow	office	pipes	playgr.	relief	relief.	terrace	terrai.

Fast-Effi-MVS+-dtu		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

Effi-MVS+-dtu		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	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	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	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

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	0.00 1

v144192		0.40 6	0.40 6	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 6	0.40 6	0.40 7	0.40 7

v1921920		0.40 6	0.40 6	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 6	0.40 6	0.40 7	0.40 7

v1192		0.40 6	0.40 6	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 6	0.40 6	0.40 7	0.40 7

v1144		0.40 6	0.40 6	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 6	0.40 6	0.40 7	0.40 7

v148		0.40 6	0.40 6	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 6	0.40 6	0.40 7	0.40 7

v748		0.40 6	0.40 6	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 6	0.40 6	0.40 7	0.40 7

v7n		0.40 6	0.40 6	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 6	0.40 6	0.40 7	0.40 7

v1141		0.40 6	0.40 6	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 6	0.40 6	0.40 7	0.40 7

v1neww		0.40 6	0.40 6	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 6	0.40 6	0.40 7	0.40 7

v7new		0.40 6	0.40 6	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 6	0.40 6	0.40 7	0.40 7

v1240		0.40 6	0.40 6	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 6	0.40 6	0.40 7	0.40 7

v18		0.40 6	0.40 6	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 6	0.40 6	0.40 7	0.40 7

v17		0.40 6	0.40 6	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 6	0.40 6	0.40 7	0.40 7

v16		0.40 6	0.40 6	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 6	0.40 6	0.40 7	0.40 7

divwei89l23v2f112		0.40 6	0.40 6	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 6	0.40 6	0.40 7	0.40 7

v15		0.40 6	0.40 6	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 6	0.40 6	0.40 7	0.40 7

v13		0.40 6	0.40 6	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 6	0.40 6	0.40 7	0.40 7

v12		0.40 6	0.40 6	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 6	0.40 6	0.40 7	0.40 7

v8		0.40 6	0.40 6	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 6	0.40 6	0.40 7	0.40 7

v7		0.40 6	0.40 6	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 6	0.40 6	0.40 7	0.40 7

v6		0.40 6	0.40 6	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 6	0.40 6	0.40 7	0.40 7

v11		0.40 6	0.40 6	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 6	0.40 6	0.40 7	0.40 7

v52		0.40 6	0.40 6	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 6	0.40 6	0.40 7	0.40 7

V14		0.40 6	0.40 6	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 6	0.40 6	0.40 7	0.40 7

v10		0.40 6	0.40 6	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 6	0.40 6	0.40 7	0.40 7

V4		0.40 6	0.40 6	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 6	0.40 6	0.40 7	0.40 7

v2v482		0.40 6	0.40 6	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 6	0.40 6	0.40 7	0.40 7

v1		0.40 6	0.40 6	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 6	0.40 6	0.40 7	0.40 7

V42		0.40 6	0.40 6	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 6	0.40 6	0.40 7	0.40 7

V9		0.40 6	0.40 6	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 6	0.40 6	0.40 7	0.40 7

GA-MVS		0.40 6	0.40 6	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 7	0.40 6	0.40 6	0.40 7	0.40 7

Fast-Effi-MVS+		0.41 37	0.41 37	0.41 38	0.41 38	0.41 38	0.41 38	0.41 38	0.41 38	0.41 38	0.41 38	0.41 38	0.41 38	0.41 37	0.41 37	0.41 38	0.41 38

Effi-MVS+		0.53 38	0.53 38	0.53 39	0.53 39	0.53 39	0.53 39	0.53 39	0.53 39	0.53 39	0.53 39	0.53 39	0.53 39	0.53 38	0.53 38	0.53 39	0.53 39

CDS-MVSNet		0.88 39	0.88 39	0.88 40	0.88 40	0.88 40	0.88 40	0.88 40	0.88 40	0.88 40	0.88 40	0.88 40	0.88 40	0.88 39	0.88 39	0.88 40	0.88 40
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
TAMVS		0.88 39	0.88 39	0.88 40	0.88 40	0.88 40	0.88 40	0.88 40	0.88 40	0.88 40	0.88 40	0.88 40	0.88 40	0.88 39	0.88 39	0.88 40	0.88 40

DeepMVS_CX						1.00 42	1.00 42	1.00 42	1.00 42	1.00 42	1.00 42	1.00 42	1.00 42	1.00 41		1.00 42	1.00 42

MDA-MVSNet-bldmvs		1.20 41	1.20 41	1.20 42	1.20 42	1.20 43	1.20 43	1.20 43	1.20 43	1.20 43	1.20 43	1.20 43	1.20 43	1.20 42	1.20 41	1.20 43	1.20 43

CVMVSNet		1.42 42	1.42 42	1.42 43	1.42 43	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 43	1.42 42	1.42 44	1.42 44

EU-MVSNet		1.42 42	1.42 42	1.42 43	1.42 43	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 43	1.42 42	1.42 44	1.42 44

PS-CasMVS		1.42 42	1.42 42	1.42 43	1.42 43	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 43	1.42 42	1.42 44	1.42 44

UniMVSNet_NR-MVSNet		1.42 42	1.42 42	1.42 43	1.42 43	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 43	1.42 42	1.42 44	1.42 44

PEN-MVS		1.42 42	1.42 42	1.42 43	1.42 43	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 43	1.42 42	1.42 44	1.42 44

TransMVSNet (Re)		1.42 42	1.42 42	1.42 43	1.42 43	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 43	1.42 42	1.42 44	1.42 44

DTE-MVSNet		1.42 42	1.42 42	1.42 43	1.42 43	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 43	1.42 42	1.42 44	1.42 44

DU-MVS		1.42 42	1.42 42	1.42 43	1.42 43	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 43	1.42 42	1.42 44	1.42 44

UniMVSNet (Re)		1.42 42	1.42 42	1.42 43	1.42 43	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 43	1.42 42	1.42 44	1.42 44

CP-MVSNet		1.42 42	1.42 42	1.42 43	1.42 43	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 43	1.42 42	1.42 44	1.42 44

WR-MVS_H		1.42 42	1.42 42	1.42 43	1.42 43	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 43	1.42 42	1.42 44	1.42 44

WR-MVS		1.42 42	1.42 42	1.42 43	1.42 43	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 43	1.42 42	1.42 44	1.42 44

NR-MVSNet		1.42 42	1.42 42	1.42 43	1.42 43	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 43	1.42 42	1.42 44	1.42 44

Baseline_NR-MVSNet		1.42 42	1.42 42	1.42 43	1.42 43	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 43	1.42 42	1.42 44	1.42 44

TranMVSNet+NR-MVSNet		1.42 42	1.42 42	1.42 43	1.42 43	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 44	1.42 43	1.42 42	1.42 44	1.42 44

CDPH-MVS		6.66 57	6.66 57	6.66 58	6.66 58	6.66 59	6.66 59	6.66 59	6.66 59	6.66 59	6.66 59	6.66 59	6.66 59	6.66 58	6.66 57	6.66 59	6.66 59

MDTV_nov1_ep13_2view		9.99 58	9.99 58	9.99 59	9.99 59	9.99 60	9.99 60	9.99 60	9.99 60	9.99 60	9.99 60	9.99 60	9.99 60	9.99 59	9.99 58	9.99 60	9.99 60

MDTV_nov1_ep13		9.99 58	9.99 58	9.99 59	9.99 59	9.99 60	9.99 60	9.99 60	9.99 60	9.99 60	9.99 60	9.99 60	9.99 60	9.99 59	9.99 58	9.99 60	9.99 60

new_pmnet		75.00 62	74.67 62	75.39 63	85.42 65	96.03 67	98.77 66	173.23 64	69.57 64	36.19 63	56.93 64	117.43 85	32.98 62	85.38 70	68.41 62	25.74 62	28.95 62

N_pmnet		75.00 62	74.67 62	75.39 63	85.42 65	96.03 67	98.77 66	173.23 64	69.57 64	36.19 63	56.93 64	117.43 85	32.98 62	85.38 70	68.41 62	25.74 62	28.95 62

GBi-Net		39.84 60	35.75 60	44.63 61	43.04 61	49.88 62	51.06 62	86.51 63	35.34 62	17.20 62	29.83 62	15.85 62	43.43 64	35.35 61	35.70 60	26.51 64	48.28 64

X-MVS		52.20 61	52.20 61	52.20 62	52.20 62	52.20 63	52.20 63	52.20 62	52.20 63	52.20 72	52.20 63	52.20 81	52.20 65	52.20 62	52.20 61	52.20 65	52.20 65

CANet		100.44 64	93.07 64	109.04 65	111.90 67	131.06 71	119.40 68	222.42 73	80.48 66	36.93 65	70.80 66	40.92 67	89.90 66	100.59 72	101.42 65	73.68 70	126.25 66

CANet_DTU		100.44 64	93.07 64	109.04 65	111.90 67	131.06 71	119.40 68	222.42 73	80.48 66	36.93 65	70.80 66	40.92 67	89.90 66	100.59 72	101.42 65	73.68 70	126.25 66

MVS_0304		100.44 64	93.07 64	109.04 65	111.90 67	131.06 71	119.40 68	222.42 73	80.48 66	36.93 65	70.80 66	40.92 67	89.90 66	100.59 72	101.42 65	73.68 70	126.25 66

UGNet		100.44 64	93.07 64	109.04 65	111.90 67	131.06 71	119.40 68	222.42 73	80.48 66	36.93 65	70.80 66	40.92 67	89.90 66	100.59 72	101.42 65	73.68 70	126.25 66
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
PVSNet_Blended_VisFu		129.22 77	115.76 77	144.92 78	140.60 80	162.80 82	166.50 81	281.20 78	114.70 70	55.50 75	96.20 72	51.80 78	140.60 79	114.70 76	114.70 78	85.10 74	155.40 70

PVSNet_BlendedMVS		129.22 77	115.76 77	144.92 78	140.60 80	162.80 82	166.50 81	281.20 78	114.70 70	55.50 75	96.20 72	51.80 78	140.60 79	114.70 76	114.70 78	85.10 74	155.40 70

PVSNet_Blended		129.22 77	115.76 77	144.92 78	140.60 80	162.80 82	166.50 81	281.20 78	114.70 70	55.50 75	96.20 72	51.80 78	140.60 79	114.70 76	114.70 78	85.10 74	155.40 70

FMVSNet5		116.86 68	110.47 70	124.32 69	131.47 73	157.41 75	150.67 74	199.64 66	115.30 73	56.61 78	97.70 75	51.77 71	117.26 70	77.26 63	113.14 71	90.25 77	160.68 73

test1		116.86 68	110.47 70	124.32 69	131.47 73	157.41 75	150.67 74	199.64 66	115.30 73	56.61 78	97.70 75	51.77 71	117.26 70	77.26 63	113.14 71	90.25 77	160.68 73

FMVSNet3		116.86 68	110.47 70	124.32 69	131.47 73	157.41 75	150.67 74	199.64 66	115.30 73	56.61 78	97.70 75	51.77 71	117.26 70	77.26 63	113.14 71	90.25 77	160.68 73

FMVSNet2		116.86 68	110.47 70	124.32 69	131.47 73	157.41 75	150.67 74	199.64 66	115.30 73	56.61 78	97.70 75	51.77 71	117.26 70	77.26 63	113.14 71	90.25 77	160.68 73

FMVSNet1		116.86 68	110.47 70	124.32 69	131.47 73	157.41 75	150.67 74	199.64 66	115.30 73	56.61 78	97.70 75	51.77 71	117.26 70	77.26 63	113.14 71	90.25 77	160.68 73

MIMVSNet1		116.86 68	110.47 70	124.32 69	131.47 73	157.41 75	150.67 74	199.64 66	115.30 73	56.61 78	97.70 75	51.77 71	117.26 70	77.26 63	113.14 71	90.25 77	160.68 73

MIMVSNet		116.86 68	110.47 70	124.32 69	131.47 73	157.41 75	150.67 74	199.64 66	115.30 73	56.61 78	97.70 75	51.77 71	117.26 70	77.26 63	113.14 71	90.25 77	160.68 73

ACMMP_Plus		119.64 75	106.58 68	134.88 76	123.82 71	127.44 69	145.38 72	298.43 81	116.16 80	43.72 70	77.82 70	29.30 64	131.24 77	117.82 79	106.21 69	66.69 68	171.29 80

MPTG		119.64 75	106.58 68	134.88 76	123.82 71	127.44 69	145.38 72	298.43 81	116.16 80	43.72 70	77.82 70	29.30 64	131.24 77	117.82 79	106.21 69	66.69 68	171.29 80

SixPastTwentyTwo		210.90 80	189.75 80	235.58 81	225.41 83	284.88 85	267.17 84	485.88 84	164.28 83	76.51 85	137.62 82	76.69 84	214.49 82	206.28 81	208.00 81	144.02 85	250.52 82

PatchT		878.42 105	785.05 105	987.36 106	1050.05 115	922.05 107	1111.05 114	677.05 85	950.05 113	1285.90 152	750.05 115	640.05 126	850.05 103	950.05 107	950.05 107	950.05 118	333.05 83

LP		413.85 83	365.67 83	470.06 85	505.99 92	560.16 93	484.94 90	977.47 92	310.10 84	140.33 87	226.97 84	133.09 88	397.21 85	428.08 85	451.30 86	314.39 90	450.02 84

RPSCF		376.53 81	341.80 81	417.05 83	418.60 86	457.01 90	467.46 89	825.25 90	336.12 86	159.32 90	260.40 86	151.13 90	386.94 84	364.25 83	352.10 82	244.72 86	471.62 85

EG-PatchMatch MVS		402.98 82	364.36 82	448.05 84	435.50 87	473.00 91	489.60 91	910.20 91	338.60 87	127.30 86	205.10 83	123.50 87	434.60 86	450.70 88	447.70 85	291.10 88	511.90 86

ADS-MVSNet		452.36 85	406.02 85	506.42 89	534.76 95	628.22 96	552.79 93	1009.99 99	333.98 85	149.26 88	246.67 85	149.01 89	447.03 88	465.35 89	501.18 89	344.69 92	517.75 87

PatchmatchNet		452.63 86	410.20 86	502.13 88	520.70 94	614.40 94	546.00 92	1018.80 100	379.00 89	167.50 91	277.10 87	169.40 92	437.10 87	437.10 86	457.50 87	322.70 91	536.90 88
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
MS-PatchMatch		438.85 84	388.71 84	497.33 86	479.00 88	527.00 92	558.00 94	988.00 93	379.00 89	174.00 92	278.00 88	162.00 91	494.00 90	418.00 84	412.00 83	291.00 87	545.00 89

DELS-MVS		458.84 87	423.31 87	500.30 87	511.99 93	616.59 95	578.86 95	991.10 94	355.79 88	158.99 89	319.09 90	190.62 94	453.64 89	437.73 87	439.52 84	307.20 89	603.81 90
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
dps		534.60 88	472.40 88	607.16 91	690.38 102	718.85 99	636.03 96	1231.66 102	422.74 91	198.65 94	325.68 91	194.97 95	512.90 91	509.81 91	513.65 90	373.33 94	621.11 91

IterMVS		554.60 91	488.63 89	631.57 96	636.90 99	700.80 97	674.70 98	1271.10 104	430.50 92	207.10 96	370.50 92	202.70 96	611.80 95	534.20 94	545.30 93	387.80 95	636.40 92
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
GG-mvs-BLEND		557.53 92	503.49 90	620.58 93	485.90 89	370.41 86	267.30 85	710.53 86	454.42 94	785.72 128	491.23 101	326.12 109	881.92 105	538.27 95	650.05 98	592.08 107	693.94 93

gm-plane-assit		551.84 89	503.49 90	608.24 92	411.90 85	370.41 86	267.30 85	710.53 86	454.42 94	785.72 128	491.23 101	326.12 109	881.92 105	538.27 95	650.05 98	592.08 107	693.94 93

gg-mvs-nofinetune		557.53 92	503.49 90	620.58 93	485.90 89	370.41 86	267.30 85	710.53 86	454.42 94	785.72 128	491.23 101	326.12 109	881.92 105	538.27 95	650.05 98	592.08 107	693.94 93

CR-MVSNet		557.53 92	503.49 90	620.58 93	485.90 89	370.41 86	267.30 85	710.53 86	454.42 94	785.72 128	491.23 101	326.12 109	881.92 105	538.27 95	650.05 98	592.08 107	693.94 93

Gipuma		587.77 95	529.57 95	655.67 97	637.00 100	733.00 100	749.00 100	1245.00 103	525.00 100	269.00 102	445.00 97	253.00 100	637.00 97	525.00 93	525.00 91	397.00 96	701.00 97
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
IB-MVS	750.90 3	552.99 90	511.38 94	601.53 90	606.02 98	735.75 101	688.75 99	1183.86 101	436.09 93	210.63 97	397.40 93	233.85 98	551.05 92	521.77 92	533.78 92	368.88 93	721.05 98
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
MVS_Test		654.54 96	583.51 96	737.40 99	721.80 103	822.10 103	808.60 102	1494.00 106	542.20 102	259.90 100	441.60 95	257.70 102	689.10 99	620.80 99	617.70 95	451.00 100	782.50 99

diffmvs		654.54 96	583.51 96	737.40 99	721.80 103	822.10 103	808.60 102	1494.00 106	542.20 102	259.90 100	441.60 95	257.70 102	689.10 99	620.80 99	617.70 95	451.00 100	782.50 99

IterMVS-LS		714.97 100	638.00 101	804.77 103	793.60 106	914.20 106	886.50 107	1612.70 108	588.30 104	285.30 103	491.20 100	278.40 105	759.20 101	677.40 102	681.30 103	491.30 102	835.20 101
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
ACMH+	702.88 1	670.82 98	589.81 98	765.33 101	662.52 101	701.42 98	795.24 101	1698.33 109	598.81 105	226.55 98	403.02 94	187.13 93	786.82 102	724.80 104	646.56 97	422.52 98	866.95 102

new-patchmatchnet		712.65 99	632.59 99	806.05 104	787.79 105	936.25 108	882.47 105	1795.72 110	528.60 101	244.29 99	471.90 98	257.36 101	681.47 98	705.16 103	659.05 102	444.55 99	869.82 103

PMVS	743.55 2	836.66 103	637.90 100	1068.55 112	1306.50 119	875.12 105	1166.70 117	2629.00 115	512.24 99	196.22 93	282.69 89	237.15 99	597.87 94	842.47 106	765.54 105	514.99 103	950.09 104
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
MVSTER		834.63 102	737.03 104	948.49 105	988.86 108	1140.51 118	1129.34 116	1832.80 112	682.42 106	319.01 104	550.98 107	311.35 108	872.51 104	763.95 105	757.83 104	548.41 104	952.20 105

MSLP-MVS++		993.91 107	732.21 103	1299.24 116	1631.22 122	1345.26 120	1480.05 121	2524.20 114	735.65 107	463.57 119	499.89 105	302.78 106	1292.66 118	675.99 101	612.79 94	403.71 97	953.11 106

RPMNet		858.01 104	961.99 110	736.69 98	550.05 96	1120.24 116	1212.05 118	463.05 83	485.90 98	550.05 121	580.05 108	890.05 138	559.05 93	1485.90 120	1185.90 118	1085.90 124	985.90 107

ambc			999.00 111		999.00 109	999.00 110	999.00 108		999.00 115	999.00 136	999.00 122	999.00 143	999.00 111	999.00 110	999.00 110	999.00 119	999.00 108

EPMVS		999.00 108	999.00 111	999.00 107	999.00 109	999.00 110	999.00 108	999.00 95	999.00 115	999.00 136	999.00 122	999.00 143	999.00 111	999.00 110	999.00 110	999.00 119	999.00 108

sosnet		1000.00 109	1000.00 113	1000.00 108	1000.00 111	1000.00 112	1000.00 110	1000.00 96	1000.00 117	1000.00 138	1000.00 124	1000.00 145	1000.00 113	1000.00 112	1000.00 112	1000.00 121	1000.00 110

USDC		1000.00 109	1000.00 113	1000.00 108	1000.00 111	1000.00 112	1000.00 110	1000.00 96	1000.00 117	1000.00 138	1000.00 124	1000.00 145	1000.00 113	1000.00 112	1000.00 112	1000.00 121	1000.00 110

TinyColmap		1000.00 109	1000.00 113	1000.00 108	1000.00 111	1000.00 112	1000.00 110	1000.00 96	1000.00 117	1000.00 138	1000.00 124	1000.00 145	1000.00 113	1000.00 112	1000.00 112	1000.00 121	1000.00 110

CSCG		727.26 101	663.25 102	801.94 102	590.65 97	811.25 102	854.12 104	1805.32 111	816.43 110	388.25 108	612.42 109	345.37 115	621.61 96	507.46 90	471.55 88	551.65 105	1078.31 113

MVS_111021_LR		1055.24 113	916.36 108	1217.27 114	1129.93 117	1268.26 119	1313.88 120	2635.76 116	923.19 112	396.92 113	704.88 113	327.66 113	1136.32 116	965.38 108	946.95 106	690.83 115	1278.20 114

ACMH	935.68 4	948.23 106	857.00 106	1054.67 111	946.00 107	970.00 109	1125.00 115	2467.00 113	823.00 111	330.00 106	622.00 110	211.00 97	891.00 109	970.00 109	1061.00 115	569.00 106	1342.00 115
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
PLC	4785.50 15	3275.54 144	3030.86 145	3561.00 143	4093.00 150	4596.00 149	5174.00 155	4267.00 124	3570.00 150	1495.00 155	2940.00 152	1594.00 155	3947.00 148	3817.00 149	3343.00 148	2390.00 150	1356.00 116
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
ACMP	1170.86 6	1091.37 114	943.23 109	1264.21 115	1112.10 116	1138.94 117	1276.90 119	2675.36 117	989.62 114	426.15 117	742.77 114	349.09 117	1454.51 122	1047.36 115	969.90 108	640.22 111	1364.94 117
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
TSAR-MVS + GP.		1239.27 115	1094.74 118	1407.89 117	1220.99 118	1845.47 125	1680.98 124	3191.81 119	1098.41 120	362.98 107	679.12 112	339.31 114	1323.06 119	1173.24 119	1093.83 116	667.49 113	1433.78 118

FPMVS		1356.65 118	1072.60 116	1688.04 120	1840.79 123	1397.01 121	1793.24 125	4397.86 126	804.66 108	408.78 114	538.65 106	407.36 118	894.84 110	1587.73 121	1286.38 120	792.73 117	1486.39 119

ACMMPR		1265.65 116	1083.59 117	1478.06 119	1441.06 121	1438.61 123	1540.68 123	3284.05 121	1219.68 122	458.81 118	803.22 117	346.91 116	1421.66 121	1126.11 118	1150.51 117	722.08 116	1500.09 120

DeepC-MVS_fast	2081.98 8	1311.87 117	1172.50 119	1474.47 118	1411.78 120	1397.23 122	1519.03 122	3401.40 122	1201.29 121	417.90 115	801.95 116	976.25 142	1409.37 120	1114.52 117	1201.12 119	687.33 114	1515.14 121
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
ACMM	1129.18 5	1047.56 112	912.90 107	1204.67 113	1040.21 114	1016.71 115	1105.32 113	2918.67 118	813.91 109	327.22 105	665.34 111	267.72 104	1192.58 117	1091.35 116	991.88 109	643.99 112	1543.40 122
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
MVS-HIRNet		1975.98 120	1797.02 122	2184.76 122	2111.07 125	2443.03 129	2503.43 128	4063.71 123	1684.46 131	711.34 126	1456.05 134	848.70 136	2396.26 134	1900.93 122	1915.01 123	1322.75 132	2330.99 123

PCF-MVS	3738.24 13	2129.60 122	1746.89 121	2576.10 129	2258.22 129	2263.67 126	2650.06 133	6361.78 140	1676.15 130	695.66 125	1209.77 128	737.88 129	2237.28 125	2083.02 129	1835.31 121	1253.58 130	2422.45 124
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
SD-MVS		2324.36 128	1910.97 123	2806.65 137	2945.31 137	3305.03 141	3267.51 138	5962.25 139	1896.37 133	848.15 133	1224.25 129	661.55 127	2707.30 138	1913.40 123	1871.41 122	1109.38 125	2504.79 125

OpenMVS	2049.89 7	1895.92 119	1721.29 120	2099.67 121	2064.00 124	2419.00 128	2138.00 126	4572.00 127	1541.00 128	548.00 120	937.00 119	580.00 124	1983.00 124	1971.00 127	1993.00 125	1293.00 131	2608.00 126

CHOSEN 280x420		2225.10 123	1992.66 126	2496.28 124	2192.10 126	2641.81 130	2621.41 130	5345.34 131	2116.46 136	1002.26 141	1683.84 138	837.43 132	2338.65 127	1920.94 124	2020.28 126	1477.92 136	2727.86 127

CHOSEN 1792x2688		2225.10 123	1992.66 126	2496.28 124	2192.10 126	2641.81 130	2621.41 130	5345.34 131	2116.46 136	1002.26 141	1683.84 138	837.43 132	2338.65 127	1920.94 124	2020.28 126	1477.92 136	2727.86 127

HyFIR lowres test		2225.10 123	1992.66 126	2496.28 124	2192.10 126	2641.81 130	2621.41 130	5345.34 131	2116.46 136	1002.26 141	1683.84 138	837.43 132	2338.65 127	1920.94 124	2020.28 126	1477.92 136	2727.86 127

Vis-MVSNet		2390.77 130	1976.57 124	2874.00 138	2644.00 135	3248.00 139	3040.00 136	7371.00 144	1627.00 129	421.00 116	1200.00 127	622.00 125	2251.00 126	2326.00 135	2052.00 129	1517.00 139	2761.00 130
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
CMPMVS	2507.20 10	2083.60 121	1983.13 125	2200.81 123	2582.70 133	3097.30 136	2332.10 127	4364.50 125	1390.00 123	653.68 124	997.75 121	742.65 131	1880.20 123	2298.80 134	2413.60 137	1391.70 134	2941.80 131
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
AdaColmap		2288.90 126	2080.73 130	2531.77 127	2485.98 132	2757.87 133	2974.47 135	4914.62 128	2255.54 139	804.63 132	1611.14 137	842.30 135	2657.83 137	2056.92 128	1960.62 124	1353.09 133	3080.73 132

3Dnovator	2220.89 9	2303.77 127	2037.00 129	2615.00 130	2617.00 134	2967.00 135	2616.00 129	5882.00 138	1928.00 134	589.00 122	907.00 118	528.00 123	2443.00 136	2370.00 136	2392.00 136	1543.00 140	3167.00 133

TSAR-MVS + MP.		4216.58 146	4674.68 148	3682.13 145	3752.63 148	4315.48 148	4264.77 151	7782.51 147	2583.81 142	1125.68 149	16722.30 159	882.60 137	3589.10 147	2523.80 139	2486.45 139	1578.08 142	3208.34 134

DeepPCF-MVS	3033.31 11	2362.79 129	2183.15 131	2572.38 128	2349.28 130	2383.16 127	2740.92 134	5212.97 130	2043.02 135	751.44 127	1466.47 135	1327.42 153	2904.33 139	2573.45 140	2227.77 130	1475.33 135	3260.73 135

TAPA-MVS	5463.68 16	2764.21 138	2434.28 133	3149.14 140	3645.15 147	3257.60 140	3452.71 142	6526.32 141	2591.85 143	651.36 123	1964.77 147	947.44 141	2924.41 140	2523.36 138	2452.68 138	1694.86 144	3302.28 136
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
SteuartSystems-ACMMP		2615.00 131	2242.57 132	3049.50 139	2828.00 136	2801.00 134	3323.00 140	6648.00 142	2491.00 140	1023.00 144	1605.00 136	697.00 128	2926.00 141	2502.00 137	2279.00 131	1549.00 141	3323.00 137
Skip Steuart: Steuart Systems R&D Blog.
tpm cat1		2652.13 132	2606.66 136	2705.18 132	3151.86 139	6902.39 152	3612.17 143	5463.78 134	1457.76 124	391.31 109	1358.61 130	446.44 119	2360.09 130	2296.48 130	2290.90 132	1251.84 126	3494.04 138

tpmp4_e23		2652.13 132	2606.66 136	2705.18 132	3151.86 139	6902.39 152	3612.17 143	5463.78 134	1457.76 124	391.31 109	1358.61 130	446.44 119	2360.09 130	2296.48 130	2290.90 132	1251.84 126	3494.04 138

CostFormer		2652.13 132	2606.66 136	2705.18 132	3151.86 139	6902.39 152	3612.17 143	5463.78 134	1457.76 124	391.31 109	1358.61 130	446.44 119	2360.09 130	2296.48 130	2290.90 132	1251.84 126	3494.04 138

tpm		2652.13 132	2606.66 136	2705.18 132	3151.86 139	6902.39 152	3612.17 143	5463.78 134	1457.76 124	391.31 109	1358.61 130	446.44 119	2360.09 130	2296.48 130	2290.90 132	1251.84 126	3494.04 138

HSP-MVS		3241.28 143	2825.26 144	3726.65 146	3945.31 149	4305.03 147	4267.51 152	6962.25 143	2896.37 148	1068.15 146	1824.25 145	1061.55 150	4307.30 149	3013.40 147	3171.41 146	1809.38 147	3504.79 142

TSAR-MVS + ACMM		3184.92 141	2679.45 141	3774.64 147	3302.51 144	4168.07 146	4256.74 150	8947.31 150	2634.53 144	1026.25 145	1723.72 143	1043.87 149	3387.29 145	2794.29 141	2687.41 141	1727.73 145	3704.25 143

3Dnovator+	3173.67 12	2938.77 139	2519.43 134	3428.00 141	3256.00 143	3708.00 144	3443.00 141	7516.00 145	2525.00 141	1121.00 148	972.00 120	925.00 140	3192.00 143	2899.00 143	2897.00 145	2040.00 148	3710.00 144

COLMAP_ROB	3798.28 14	2690.62 137	2704.29 142	2674.67 131	3138.00 138	3522.00 143	3826.00 148	3219.00 120	2702.00 145	1138.00 150	2260.00 149	1212.00 152	2968.00 142	2936.00 145	2571.00 140	1759.00 146	3727.00 145
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
MVS_111021_HR		3192.50 142	2773.91 143	3680.86 144	3515.58 145	3815.81 145	4020.82 149	7766.11 146	2775.23 147	1300.96 154	2221.19 148	1117.25 151	3420.01 146	2873.98 142	2835.60 144	2061.69 149	3778.31 146

OPM-MVS		3051.54 140	2661.57 140	3506.50 142	3532.00 146	3332.00 142	3744.00 147	7839.00 148	2772.00 146	985.00 135	1919.00 146	738.00 130	3319.00 144	2901.00 144	2715.00 142	1620.00 143	4254.00 147

tpmrst		2688.71 136	2604.46 135	2787.00 136	2472.96 131	3190.36 137	3313.69 139	5003.06 129	1837.26 132	1097.38 147	1721.89 142	1012.20 148	2415.09 135	2970.27 146	2736.80 143	2419.79 151	4762.44 148

MAR-MVS		3961.62 145	3726.55 146	4235.86 148	4107.62 151	6522.83 151	4862.93 154	7956.64 149	3380.98 149	1665.13 156	3231.54 153	1650.34 156	4357.29 150	3198.61 148	3209.42 147	2465.52 152	4892.15 149
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
DeepC-MVS	5581.15 17	4824.92 148	5020.53 149	4596.70 149	4714.52 152	3205.14 138	3108.50 137	10234.20 153	3823.34 152	1885.23 158	9002.42 156	2045.34 159	4715.23 152	7652.65 153	3993.41 149	2922.51 153	5421.41 150
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
OMC-MVS		4439.92 147	3906.78 147	5061.92 150	4748.70 153	5679.38 150	5855.03 156	9923.00 151	4023.36 153	1740.95 157	1693.78 141	1693.78 157	4658.45 151	4254.77 150	4135.74 150	3445.36 154	5866.63 151

TSAR-MVS + COLMAP		6088.23 149	5315.97 150	6989.21 151	6522.51 154	8025.15 156	7938.31 157	15276.20 154	5401.97 155	1914.31 159	3802.65 154	1979.48 158	6704.11 154	5217.07 151	5137.16 151	3579.82 155	7648.29 152

LS3D		7481.83 151	6596.02 152	8515.28 153	9871.71 156	9844.03 158	9225.16 159	18308.40 156	5364.90 154	1267.41 151	2381.61 150	1512.79 154	7225.72 155	8875.69 154	9516.28 153	5193.26 157	8676.83 153

CLD-MVS		6986.85 150	6222.57 151	7878.50 152	7707.00 155	8884.00 157	9025.00 158	15607.00 155	6148.00 156	2571.00 160	4822.00 155	2082.00 160	7875.00 156	6389.00 152	6449.00 152	4486.00 156	8784.00 154
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
ACMMP		9999.00 152	9999.00 153	9999.00 154	9999.00 158	9999.00 159	9999.00 160	9999.00 152	9999.00 157	9999.00 162	9999.00 157	9999.00 162	9999.00 157	9999.00 155	9999.00 154	9999.00 159	9999.00 155
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
MVE	11086.50 18	13278.69 153	12303.57 154	14416.33 155	9890.00 157	17107.00 160	4634.00 153	59884.00 159	3666.00 151	966.00 134	1792.00 144	896.00 139	5680.00 153	20677.00 158	23030.00 157	5444.00 158	18957.00 156
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
CNLPA		17763.08 154	15907.71 155	19927.67 156	19334.00 159	22387.00 161	22896.00 161	38668.00 157	15772.00 158	7632.00 161	13229.00 158	7123.00 161	19334.00 158	15773.00 156	15700.00 155	11702.00 160	21370.00 157

LTVRE_ROB	38377.89 19	49656.08 156	18936.71 156	85495.33 158	306852.00 162	22526.00 162	29206.00 162	112098.00 161	30022.00 159	17348.00 164	2824.00 151	11239.00 163	29457.00 159	20569.00 157	19941.00 156	18011.00 161	25436.00 158
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		31705.85 155	29167.57 157	34667.17 157	44079.00 160	28314.00 163	44778.00 163	43648.00 158	31045.00 160	14849.00 163	26179.00 160	13752.00 164	38088.00 160	30859.00 159	30835.00 158	22561.00 162	43189.00 159

PHI-MVS		99999.00 157	99999.00 158	99999.00 159	99999.00 161	99999.00 164	99999.00 164	99999.00 160	99999.00 161	99999.00 165	99999.00 161	99999.00 165	99999.00 161	99999.00 160	99999.00 159	99999.00 163	99999.00 160

conf0.01		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

conf0.002		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

thresconf0.02		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

tfpn_n400		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

tfpnconf		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

tfpnview11		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

tfpn1000		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

tfpn_ndepth		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

conf200view11		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

thres100view900		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

tfpnnormal		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

tfpn200view9		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

view600		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

view800		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

conf0.05thres1000		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

tfpn		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

ESAPD		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

pmmvs6		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

pmmvs5		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

Anonymous20231211		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

pmmvs-eth3d		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

Anonymous20231206		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

canonicalmvs		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

anonymousdsp		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

FC-MVSNet-train		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

UA-Net		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

FC-MVSNet-test		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

sosnet-low-res		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

DI_MVS_plusplus_trai		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

HPM-MVS++		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

pm-mvs1		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

APDe-MVS		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

pmmvs4		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

test-LLR		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

TESTMET0.1,1		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

test-mter		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

testgi		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

test20.03		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

thres600view7		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

1111		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

.test1245		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

MP-MVS		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

testmvs		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

thres400		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

test123		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

thres200		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

test0.0.03 1		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

test12356		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

testus		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

pmmvs3		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

testmv		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

EMVS		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

E-PMN		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

test2356		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

test1235678		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

PGM-MVS		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

MCST-MVS		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

PMMVS2		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

PM-MVS		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

DWT-MVSNet_training		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

testpf		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

LGP-MVS_train		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

EPNet_dtu		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
EPNet		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CNVR-MVS		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

NCCC		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

CP-MVS		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

no-one		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

CPTT-MVS		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

HQP-MVS		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

IS_MVSNet		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

Vis-MVSNet (Re-imp)		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

PatchMatch-RL		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

TDRefinement		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

EPP-MVSNet		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

PMMVS		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 163	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 166	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

APD-MVS		1000000000.00 234	1000000000.00 235	1000000000.00 236	1000000000.00 240	1000000000.00 241	1000000000.00 242	1000000000.00 238	1000000000.00 239	1000000000.00 243	1000000000.00 238	1000000000.00 243	1000000000.00 238	1000000000.00 237	1000000000.00 236	1000000000.00 240	1000000000.00 237
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
MTAPA										41.98 69		28.43 63

MTMP										10000000.00 166		31.71 66

Patchmatch-RL test							10000000.00 165

tmp_tt				299.50 82	365.00 84	54.00 66	649.00 97	241.00 77	159.00 82	204.00 95	479.00 99	308.00 107	243.00 83	246.00 82	82.00 64	95.00 84

XVS					52.20 62	52.20 63	52.20 63			52.20 72		52.20 81				52.20 65

X-MVStestdata					52.20 62	52.20 63	52.20 63			52.20 72		52.20 81				52.20 65

mPP-MVS					10000000.00 163							10000000.00 166

NP-MVS									10000000.00 162

Patchmtry						1825.90 124	885.90 106	1405.90 105		1285.90 152

High-resolution multi-view benchmark