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.

SMA-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

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 7	0.40 7	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 7	0.40 7	0.40 8	0.40 8

v1921920		0.40 7	0.40 7	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 7	0.40 7	0.40 8	0.40 8

v1192		0.40 7	0.40 7	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 7	0.40 7	0.40 8	0.40 8

v1144		0.40 7	0.40 7	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 7	0.40 7	0.40 8	0.40 8

v148		0.40 7	0.40 7	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 7	0.40 7	0.40 8	0.40 8

v748		0.40 7	0.40 7	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 7	0.40 7	0.40 8	0.40 8

v7n		0.40 7	0.40 7	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 7	0.40 7	0.40 8	0.40 8

v1141		0.40 7	0.40 7	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 7	0.40 7	0.40 8	0.40 8

v1neww		0.40 7	0.40 7	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 7	0.40 7	0.40 8	0.40 8

v7new		0.40 7	0.40 7	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 7	0.40 7	0.40 8	0.40 8

v1240		0.40 7	0.40 7	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 7	0.40 7	0.40 8	0.40 8

v18		0.40 7	0.40 7	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 7	0.40 7	0.40 8	0.40 8

v17		0.40 7	0.40 7	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 7	0.40 7	0.40 8	0.40 8

v16		0.40 7	0.40 7	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 7	0.40 7	0.40 8	0.40 8

divwei89l23v2f112		0.40 7	0.40 7	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 7	0.40 7	0.40 8	0.40 8

v15		0.40 7	0.40 7	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 7	0.40 7	0.40 8	0.40 8

v13		0.40 7	0.40 7	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 7	0.40 7	0.40 8	0.40 8

v12		0.40 7	0.40 7	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 7	0.40 7	0.40 8	0.40 8

v8		0.40 7	0.40 7	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 7	0.40 7	0.40 8	0.40 8

v7		0.40 7	0.40 7	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 7	0.40 7	0.40 8	0.40 8

v6		0.40 7	0.40 7	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 7	0.40 7	0.40 8	0.40 8

v11		0.40 7	0.40 7	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 7	0.40 7	0.40 8	0.40 8

v52		0.40 7	0.40 7	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 7	0.40 7	0.40 8	0.40 8

V14		0.40 7	0.40 7	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 7	0.40 7	0.40 8	0.40 8

v10		0.40 7	0.40 7	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 7	0.40 7	0.40 8	0.40 8

V4		0.40 7	0.40 7	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 7	0.40 7	0.40 8	0.40 8

v2v482		0.40 7	0.40 7	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 7	0.40 7	0.40 8	0.40 8

v1		0.40 7	0.40 7	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 7	0.40 7	0.40 8	0.40 8

V42		0.40 7	0.40 7	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 7	0.40 7	0.40 8	0.40 8

V9		0.40 7	0.40 7	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 7	0.40 7	0.40 8	0.40 8

GA-MVS		0.40 7	0.40 7	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 8	0.40 7	0.40 7	0.40 8	0.40 8

Fast-Effi-MVS+		0.41 38	0.41 38	0.41 39	0.41 39	0.41 39	0.41 39	0.41 39	0.41 39	0.41 39	0.41 39	0.41 39	0.41 39	0.41 38	0.41 38	0.41 39	0.41 39

Effi-MVS+		0.53 39	0.53 39	0.53 40	0.53 40	0.53 40	0.53 40	0.53 40	0.53 40	0.53 40	0.53 40	0.53 40	0.53 40	0.53 39	0.53 39	0.53 40	0.53 40

CDS-MVSNet		0.88 40	0.88 40	0.88 41	0.88 41	0.88 41	0.88 41	0.88 41	0.88 41	0.88 41	0.88 41	0.88 41	0.88 41	0.88 40	0.88 40	0.88 41	0.88 41
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
TAMVS		0.88 40	0.88 40	0.88 41	0.88 41	0.88 41	0.88 41	0.88 41	0.88 41	0.88 41	0.88 41	0.88 41	0.88 41	0.88 40	0.88 40	0.88 41	0.88 41

MDA-MVSNet-bldmvs		1.20 42	1.20 42	1.20 43	1.20 43	1.20 44	1.20 44	1.20 44	1.20 44	1.20 44	1.20 44	1.20 44	1.20 44	1.20 43	1.20 42	1.20 44	1.20 44

CVMVSNet		1.42 43	1.42 43	1.42 44	1.42 44	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 44	1.42 43	1.42 45	1.42 45

EU-MVSNet		1.42 43	1.42 43	1.42 44	1.42 44	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 44	1.42 43	1.42 45	1.42 45

PS-CasMVS		1.42 43	1.42 43	1.42 44	1.42 44	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 44	1.42 43	1.42 45	1.42 45

UniMVSNet_NR-MVSNet		1.42 43	1.42 43	1.42 44	1.42 44	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 44	1.42 43	1.42 45	1.42 45

PEN-MVS		1.42 43	1.42 43	1.42 44	1.42 44	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 44	1.42 43	1.42 45	1.42 45

TransMVSNet (Re)		1.42 43	1.42 43	1.42 44	1.42 44	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 44	1.42 43	1.42 45	1.42 45

DTE-MVSNet		1.42 43	1.42 43	1.42 44	1.42 44	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 44	1.42 43	1.42 45	1.42 45

DU-MVS		1.42 43	1.42 43	1.42 44	1.42 44	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 44	1.42 43	1.42 45	1.42 45

UniMVSNet (Re)		1.42 43	1.42 43	1.42 44	1.42 44	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 44	1.42 43	1.42 45	1.42 45

CP-MVSNet		1.42 43	1.42 43	1.42 44	1.42 44	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 44	1.42 43	1.42 45	1.42 45

WR-MVS_H		1.42 43	1.42 43	1.42 44	1.42 44	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 44	1.42 43	1.42 45	1.42 45

WR-MVS		1.42 43	1.42 43	1.42 44	1.42 44	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 44	1.42 43	1.42 45	1.42 45

NR-MVSNet		1.42 43	1.42 43	1.42 44	1.42 44	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 44	1.42 43	1.42 45	1.42 45

Baseline_NR-MVSNet		1.42 43	1.42 43	1.42 44	1.42 44	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 44	1.42 43	1.42 45	1.42 45

TranMVSNet+NR-MVSNet		1.42 43	1.42 43	1.42 44	1.42 44	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 45	1.42 44	1.42 43	1.42 45	1.42 45

CDPH-MVS		6.66 58	6.66 58	6.66 59	6.66 59	6.66 60	6.66 60	6.66 60	6.66 60	6.66 60	6.66 60	6.66 60	6.66 60	6.66 59	6.66 58	6.66 60	6.66 60

MDTV_nov1_ep13_2view		9.99 59	9.99 59	9.99 60	9.99 60	9.99 61	9.99 61	9.99 61	9.99 61	9.99 61	9.99 61	9.99 61	9.99 61	9.99 60	9.99 59	9.99 61	9.99 61

MDTV_nov1_ep13		9.99 59	9.99 59	9.99 60	9.99 60	9.99 61	9.99 61	9.99 61	9.99 61	9.99 61	9.99 61	9.99 61	9.99 61	9.99 60	9.99 59	9.99 61	9.99 61

GBi-Net		39.84 61	35.75 61	44.63 62	43.04 62	49.88 63	51.06 63	86.51 64	35.34 63	17.20 63	29.83 63	15.85 63	43.43 65	35.35 62	35.70 61	26.51 65	48.28 65

XVS					52.20 63	52.20 64	52.20 64			52.20 73		52.20 82				52.20 66

X-MVStestdata					52.20 63	52.20 64	52.20 64			52.20 73		52.20 82				52.20 66

X-MVS		52.20 62	52.20 62	52.20 63	52.20 63	52.20 64	52.20 64	52.20 63	52.20 64	52.20 73	52.20 64	52.20 82	52.20 66	52.20 63	52.20 62	52.20 66	52.20 66

new_pmnet		75.00 63	74.67 63	75.39 64	85.42 66	96.03 68	98.77 67	173.23 65	69.57 65	36.19 64	56.93 65	117.43 86	32.98 63	85.38 71	68.41 63	25.74 63	28.95 63

N_pmnet		75.00 63	74.67 63	75.39 64	85.42 66	96.03 68	98.77 67	173.23 65	69.57 65	36.19 64	56.93 65	117.43 86	32.98 63	85.38 71	68.41 63	25.74 63	28.95 63

CANet		100.44 65	93.07 65	109.04 66	111.90 68	131.06 72	119.40 69	222.42 74	80.48 67	36.93 66	70.80 67	40.92 68	89.90 67	100.59 73	101.42 66	73.68 71	126.25 67

CANet_DTU		100.44 65	93.07 65	109.04 66	111.90 68	131.06 72	119.40 69	222.42 74	80.48 67	36.93 66	70.80 67	40.92 68	89.90 67	100.59 73	101.42 66	73.68 71	126.25 67

MVS_0304		100.44 65	93.07 65	109.04 66	111.90 68	131.06 72	119.40 69	222.42 74	80.48 67	36.93 66	70.80 67	40.92 68	89.90 67	100.59 73	101.42 66	73.68 71	126.25 67

UGNet		100.44 65	93.07 65	109.04 66	111.90 68	131.06 72	119.40 69	222.42 74	80.48 67	36.93 66	70.80 67	40.92 68	89.90 67	100.59 73	101.42 66	73.68 71	126.25 67
Wanjuan Su, Qingshan Xu, Wenbing Tao: Uncertainty-guided Multi-view Stereo Network for Depth Estimation. IEEE Transactions on Circuits and Systems for Video Technology, 2022
ACMMP_Plus		119.64 76	106.58 69	134.88 77	123.82 72	127.44 70	145.38 73	298.43 82	116.16 81	43.72 71	77.82 71	29.30 65	131.24 78	117.82 80	106.21 70	66.69 69	171.29 81

zzz-MVS		119.64 76	106.58 69	134.88 77	123.82 72	127.44 70	145.38 73	298.43 82	116.16 81	43.72 71	77.82 71	29.30 65	131.24 78	117.82 80	106.21 70	66.69 69	171.29 81

FMVSNet5		116.86 69	110.47 71	124.32 70	131.47 74	157.41 76	150.67 75	199.64 67	115.30 74	56.61 79	97.70 76	51.77 72	117.26 71	77.26 64	113.14 72	90.25 78	160.68 74

test1		116.86 69	110.47 71	124.32 70	131.47 74	157.41 76	150.67 75	199.64 67	115.30 74	56.61 79	97.70 76	51.77 72	117.26 71	77.26 64	113.14 72	90.25 78	160.68 74

FMVSNet3		116.86 69	110.47 71	124.32 70	131.47 74	157.41 76	150.67 75	199.64 67	115.30 74	56.61 79	97.70 76	51.77 72	117.26 71	77.26 64	113.14 72	90.25 78	160.68 74

FMVSNet2		116.86 69	110.47 71	124.32 70	131.47 74	157.41 76	150.67 75	199.64 67	115.30 74	56.61 79	97.70 76	51.77 72	117.26 71	77.26 64	113.14 72	90.25 78	160.68 74

FMVSNet1		116.86 69	110.47 71	124.32 70	131.47 74	157.41 76	150.67 75	199.64 67	115.30 74	56.61 79	97.70 76	51.77 72	117.26 71	77.26 64	113.14 72	90.25 78	160.68 74

MIMVSNet1		116.86 69	110.47 71	124.32 70	131.47 74	157.41 76	150.67 75	199.64 67	115.30 74	56.61 79	97.70 76	51.77 72	117.26 71	77.26 64	113.14 72	90.25 78	160.68 74

MIMVSNet		116.86 69	110.47 71	124.32 70	131.47 74	157.41 76	150.67 75	199.64 67	115.30 74	56.61 79	97.70 76	51.77 72	117.26 71	77.26 64	113.14 72	90.25 78	160.68 74

PVSNet_Blended_VisFu		129.22 78	115.76 78	144.92 79	140.60 81	162.80 83	166.50 82	281.20 79	114.70 71	55.50 76	96.20 73	51.80 79	140.60 80	114.70 77	114.70 79	85.10 75	155.40 71

PVSNet_BlendedMVS		129.22 78	115.76 78	144.92 79	140.60 81	162.80 83	166.50 82	281.20 79	114.70 71	55.50 76	96.20 73	51.80 79	140.60 80	114.70 77	114.70 79	85.10 75	155.40 71

PVSNet_Blended		129.22 78	115.76 78	144.92 79	140.60 81	162.80 83	166.50 82	281.20 79	114.70 71	55.50 76	96.20 73	51.80 79	140.60 80	114.70 77	114.70 79	85.10 75	155.40 71

SixPastTwentyTwo		210.90 81	189.75 81	235.58 82	225.41 84	284.88 86	267.17 85	485.88 85	164.28 84	76.51 86	137.62 83	76.69 85	214.49 83	206.28 82	208.00 82	144.02 86	250.52 83

tmp_tt				299.50 83	365.00 85	54.00 67	649.00 98	241.00 78	159.00 83	204.00 96	479.00 100	308.00 108	243.00 84	246.00 83	82.00 65	95.00 85

gm-plane-assit		551.84 90	503.49 91	608.24 93	411.90 86	370.41 87	267.30 86	710.53 87	454.42 95	785.72 129	491.23 102	326.12 110	881.92 106	538.27 96	650.05 99	592.08 108	693.94 94

RPSCF		376.53 82	341.80 82	417.05 84	418.60 87	457.01 91	467.46 90	825.25 91	336.12 87	159.32 91	260.40 87	151.13 91	386.94 85	364.25 84	352.10 83	244.72 87	471.62 86

EG-PatchMatch MVS		402.98 83	364.36 83	448.05 85	435.50 88	473.00 92	489.60 92	910.20 92	338.60 88	127.30 87	205.10 84	123.50 88	434.60 87	450.70 89	447.70 86	291.10 89	511.90 87

MS-PatchMatch		438.85 85	388.71 85	497.33 87	479.00 89	527.00 93	558.00 95	988.00 94	379.00 90	174.00 93	278.00 89	162.00 92	494.00 91	418.00 85	412.00 84	291.00 88	545.00 90

GG-mvs-BLEND		557.53 93	503.49 91	620.58 94	485.90 90	370.41 87	267.30 86	710.53 87	454.42 95	785.72 129	491.23 102	326.12 110	881.92 106	538.27 96	650.05 99	592.08 108	693.94 94

gg-mvs-nofinetune		557.53 93	503.49 91	620.58 94	485.90 90	370.41 87	267.30 86	710.53 87	454.42 95	785.72 129	491.23 102	326.12 110	881.92 106	538.27 96	650.05 99	592.08 108	693.94 94

CR-MVSNet		557.53 93	503.49 91	620.58 94	485.90 90	370.41 87	267.30 86	710.53 87	454.42 95	785.72 129	491.23 102	326.12 110	881.92 106	538.27 96	650.05 99	592.08 108	693.94 94

LP		413.85 84	365.67 84	470.06 86	505.99 93	560.16 94	484.94 91	977.47 93	310.10 85	140.33 88	226.97 85	133.09 89	397.21 86	428.08 86	451.30 87	314.39 91	450.02 85

DELS-MVS		458.84 88	423.31 88	500.30 88	511.99 94	616.59 96	578.86 96	991.10 95	355.79 89	158.99 90	319.09 91	190.62 95	453.64 90	437.73 88	439.52 85	307.20 90	603.81 91
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
PatchmatchNet		452.63 87	410.20 87	502.13 89	520.70 95	614.40 95	546.00 93	1018.80 101	379.00 90	167.50 92	277.10 88	169.40 93	437.10 88	437.10 87	457.50 88	322.70 92	536.90 89
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
ADS-MVSNet		452.36 86	406.02 86	506.42 90	534.76 96	628.22 97	552.79 94	1009.99 100	333.98 86	149.26 89	246.67 86	149.01 90	447.03 89	465.35 90	501.18 90	344.69 93	517.75 88

RPMNet		858.01 105	961.99 111	736.69 99	550.05 97	1120.24 117	1212.05 119	463.05 84	485.90 99	550.05 122	580.05 109	890.05 139	559.05 94	1485.90 121	1185.90 119	1085.90 125	985.90 108

CSCG		727.26 102	663.25 103	801.94 103	590.65 98	811.25 103	854.12 105	1805.32 112	816.43 111	388.25 109	612.42 110	345.37 116	621.61 97	507.46 91	471.55 89	551.65 106	1078.31 114

IB-MVS	750.90 3	552.99 91	511.38 95	601.53 91	606.02 99	735.75 102	688.75 100	1183.86 102	436.09 94	210.63 98	397.40 94	233.85 99	551.05 93	521.77 93	533.78 93	368.88 94	721.05 99
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
IterMVS		554.60 92	488.63 90	631.57 97	636.90 100	700.80 98	674.70 99	1271.10 105	430.50 93	207.10 97	370.50 93	202.70 97	611.80 96	534.20 95	545.30 94	387.80 96	636.40 93
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
Gipuma		587.77 96	529.57 96	655.67 98	637.00 101	733.00 101	749.00 101	1245.00 104	525.00 101	269.00 103	445.00 98	253.00 101	637.00 98	525.00 94	525.00 92	397.00 97	701.00 98
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
ACMH+	702.88 1	670.82 99	589.81 99	765.33 102	662.52 102	701.42 99	795.24 102	1698.33 110	598.81 106	226.55 99	403.02 95	187.13 94	786.82 103	724.80 105	646.56 98	422.52 99	866.95 103

dps		534.60 89	472.40 89	607.16 92	690.38 103	718.85 100	636.03 97	1231.66 103	422.74 92	198.65 95	325.68 92	194.97 96	512.90 92	509.81 92	513.65 91	373.33 95	621.11 92

MVS_Test		654.54 97	583.51 97	737.40 100	721.80 104	822.10 104	808.60 103	1494.00 107	542.20 103	259.90 101	441.60 96	257.70 103	689.10 100	620.80 100	617.70 96	451.00 101	782.50 100

diffmvs		654.54 97	583.51 97	737.40 100	721.80 104	822.10 104	808.60 103	1494.00 107	542.20 103	259.90 101	441.60 96	257.70 103	689.10 100	620.80 100	617.70 96	451.00 101	782.50 100

new-patchmatchnet		712.65 100	632.59 100	806.05 105	787.79 106	936.25 109	882.47 106	1795.72 111	528.60 102	244.29 100	471.90 99	257.36 102	681.47 99	705.16 104	659.05 103	444.55 100	869.82 104

IterMVS-LS		714.97 101	638.00 102	804.77 104	793.60 107	914.20 107	886.50 108	1612.70 109	588.30 105	285.30 104	491.20 101	278.40 106	759.20 102	677.40 103	681.30 104	491.30 103	835.20 102
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
ACMH	935.68 4	948.23 107	857.00 107	1054.67 112	946.00 108	970.00 110	1125.00 116	2467.00 114	823.00 112	330.00 107	622.00 111	211.00 98	891.00 110	970.00 110	1061.00 116	569.00 107	1342.00 116
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
MVSTER		834.63 103	737.03 105	948.49 106	988.86 109	1140.51 119	1129.34 117	1832.80 113	682.42 107	319.01 105	550.98 108	311.35 109	872.51 105	763.95 106	757.83 105	548.41 105	952.20 106

ambc			999.00 112		999.00 110	999.00 111	999.00 109		999.00 116	999.00 137	999.00 123	999.00 144	999.00 112	999.00 111	999.00 111	999.00 120	999.00 109

EPMVS		999.00 109	999.00 112	999.00 108	999.00 110	999.00 111	999.00 109	999.00 96	999.00 116	999.00 137	999.00 123	999.00 144	999.00 112	999.00 111	999.00 111	999.00 120	999.00 109

sosnet		1000.00 110	1000.00 114	1000.00 109	1000.00 112	1000.00 113	1000.00 111	1000.00 97	1000.00 118	1000.00 139	1000.00 125	1000.00 146	1000.00 114	1000.00 113	1000.00 113	1000.00 122	1000.00 111

USDC		1000.00 110	1000.00 114	1000.00 109	1000.00 112	1000.00 113	1000.00 111	1000.00 97	1000.00 118	1000.00 139	1000.00 125	1000.00 146	1000.00 114	1000.00 113	1000.00 113	1000.00 122	1000.00 111

TinyColmap		1000.00 110	1000.00 114	1000.00 109	1000.00 112	1000.00 113	1000.00 111	1000.00 97	1000.00 118	1000.00 139	1000.00 125	1000.00 146	1000.00 114	1000.00 113	1000.00 113	1000.00 122	1000.00 111

ACMM	1129.18 5	1047.56 113	912.90 108	1204.67 114	1040.21 115	1016.71 116	1105.32 114	2918.67 119	813.91 110	327.22 106	665.34 112	267.72 105	1192.58 118	1091.35 117	991.88 110	643.99 113	1543.40 123
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
PatchT		878.42 106	785.05 106	987.36 107	1050.05 116	922.05 108	1111.05 115	677.05 86	950.05 114	1285.90 153	750.05 116	640.05 127	850.05 104	950.05 108	950.05 108	950.05 119	333.05 84

ACMP	1170.86 6	1091.37 115	943.23 110	1264.21 116	1112.10 117	1138.94 118	1276.90 120	2675.36 118	989.62 115	426.15 118	742.77 115	349.09 118	1454.51 123	1047.36 116	969.90 109	640.22 112	1364.94 118
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
MVS_111021_LR		1055.24 114	916.36 109	1217.27 115	1129.93 118	1268.26 120	1313.88 121	2635.76 117	923.19 113	396.92 114	704.88 114	327.66 114	1136.32 117	965.38 109	946.95 107	690.83 116	1278.20 115

TSAR-MVS + GP.		1239.27 116	1094.74 119	1407.89 118	1220.99 119	1845.47 126	1680.98 125	3191.81 120	1098.41 121	362.98 108	679.12 113	339.31 115	1323.06 120	1173.24 120	1093.83 117	667.49 114	1433.78 119

PMVS	743.55 2	836.66 104	637.90 101	1068.55 113	1306.50 120	875.12 106	1166.70 118	2629.00 116	512.24 100	196.22 94	282.69 90	237.15 100	597.87 95	842.47 107	765.54 106	514.99 104	950.09 105
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
DeepC-MVS_fast	2081.98 8	1311.87 118	1172.50 120	1474.47 119	1411.78 121	1397.23 123	1519.03 123	3401.40 123	1201.29 122	417.90 116	801.95 117	976.25 143	1409.37 121	1114.52 118	1201.12 120	687.33 115	1515.14 122
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
ACMMPR		1265.65 117	1083.59 118	1478.06 120	1441.06 122	1438.61 124	1540.68 124	3284.05 122	1219.68 123	458.81 119	803.22 118	346.91 117	1421.66 122	1126.11 119	1150.51 118	722.08 117	1500.09 121

MSLP-MVS++		993.91 108	732.21 104	1299.24 117	1631.22 123	1345.26 121	1480.05 122	2524.20 115	735.65 108	463.57 120	499.89 106	302.78 107	1292.66 119	675.99 102	612.79 95	403.71 98	953.11 107

FPMVS		1356.65 119	1072.60 117	1688.04 121	1840.79 124	1397.01 122	1793.24 126	4397.86 127	804.66 109	408.78 115	538.65 107	407.36 119	894.84 111	1587.73 122	1286.38 121	792.73 118	1486.39 120

OpenMVS	2049.89 7	1895.92 120	1721.29 121	2099.67 122	2064.00 125	2419.00 129	2138.00 127	4572.00 128	1541.00 129	548.00 121	937.00 120	580.00 125	1983.00 125	1971.00 128	1993.00 126	1293.00 132	2608.00 127

MVS-HIRNet		1975.98 121	1797.02 123	2184.76 123	2111.07 126	2443.03 130	2503.43 129	4063.71 124	1684.46 132	711.34 127	1456.05 135	848.70 137	2396.26 135	1900.93 123	1915.01 124	1322.75 133	2330.99 124

CHOSEN 280x420		2225.10 124	1992.66 127	2496.28 125	2192.10 127	2641.81 131	2621.41 131	5345.34 132	2116.46 137	1002.26 142	1683.84 139	837.43 133	2338.65 128	1920.94 125	2020.28 127	1477.92 137	2727.86 128

CHOSEN 1792x2688		2225.10 124	1992.66 127	2496.28 125	2192.10 127	2641.81 131	2621.41 131	5345.34 132	2116.46 137	1002.26 142	1683.84 139	837.43 133	2338.65 128	1920.94 125	2020.28 127	1477.92 137	2727.86 128

HyFIR lowres test		2225.10 124	1992.66 127	2496.28 125	2192.10 127	2641.81 131	2621.41 131	5345.34 132	2116.46 137	1002.26 142	1683.84 139	837.43 133	2338.65 128	1920.94 125	2020.28 127	1477.92 137	2727.86 128

PCF-MVS	3738.24 13	2129.60 123	1746.89 122	2576.10 130	2258.22 130	2263.67 127	2650.06 134	6361.78 141	1676.15 131	695.66 126	1209.77 129	737.88 130	2237.28 126	2083.02 130	1835.31 122	1253.58 131	2422.45 125
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
DeepPCF-MVS	3033.31 11	2362.79 130	2183.15 132	2572.38 129	2349.28 131	2383.16 128	2740.92 135	5212.97 131	2043.02 136	751.44 128	1466.47 136	1327.42 154	2904.33 140	2573.45 141	2227.77 131	1475.33 136	3260.73 136

tpmrst		2688.71 137	2604.46 136	2787.00 137	2472.96 132	3190.36 138	3313.69 140	5003.06 130	1837.26 133	1097.38 148	1721.89 143	1012.20 149	2415.09 136	2970.27 147	2736.80 144	2419.79 152	4762.44 149

AdaColmap		2288.90 127	2080.73 131	2531.77 128	2485.98 133	2757.87 134	2974.47 136	4914.62 129	2255.54 140	804.63 133	1611.14 138	842.30 136	2657.83 138	2056.92 129	1960.62 125	1353.09 134	3080.73 133

CMPMVS	2507.20 10	2083.60 122	1983.13 126	2200.81 124	2582.70 134	3097.30 137	2332.10 128	4364.50 126	1390.00 124	653.68 125	997.75 122	742.65 132	1880.20 124	2298.80 135	2413.60 138	1391.70 135	2941.80 132
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
3Dnovator	2220.89 9	2303.77 128	2037.00 130	2615.00 131	2617.00 135	2967.00 136	2616.00 130	5882.00 139	1928.00 135	589.00 123	907.00 119	528.00 124	2443.00 137	2370.00 137	2392.00 137	1543.00 141	3167.00 134

Vis-MVSNet		2390.77 131	1976.57 125	2874.00 139	2644.00 136	3248.00 140	3040.00 137	7371.00 145	1627.00 130	421.00 117	1200.00 128	622.00 126	2251.00 127	2326.00 136	2052.00 130	1517.00 140	2761.00 131
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
SteuartSystems-ACMMP		2615.00 132	2242.57 133	3049.50 140	2828.00 137	2801.00 135	3323.00 141	6648.00 143	2491.00 141	1023.00 145	1605.00 137	697.00 129	2926.00 142	2502.00 138	2279.00 132	1549.00 142	3323.00 138
Skip Steuart: Steuart Systems R&D Blog.
SD-MVS		2324.36 129	1910.97 124	2806.65 138	2945.31 138	3305.03 142	3267.51 139	5962.25 140	1896.37 134	848.15 134	1224.25 130	661.55 128	2707.30 139	1913.40 124	1871.41 123	1109.38 126	2504.79 126

COLMAP_ROB	3798.28 14	2690.62 138	2704.29 143	2674.67 132	3138.00 139	3522.00 144	3826.00 149	3219.00 121	2702.00 146	1138.00 151	2260.00 150	1212.00 153	2968.00 143	2936.00 146	2571.00 141	1759.00 147	3727.00 146
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
tpm cat1		2652.13 133	2606.66 137	2705.18 133	3151.86 140	6902.39 153	3612.17 144	5463.78 135	1457.76 125	391.31 110	1358.61 131	446.44 120	2360.09 131	2296.48 131	2290.90 133	1251.84 127	3494.04 139

tpmp4_e23		2652.13 133	2606.66 137	2705.18 133	3151.86 140	6902.39 153	3612.17 144	5463.78 135	1457.76 125	391.31 110	1358.61 131	446.44 120	2360.09 131	2296.48 131	2290.90 133	1251.84 127	3494.04 139

CostFormer		2652.13 133	2606.66 137	2705.18 133	3151.86 140	6902.39 153	3612.17 144	5463.78 135	1457.76 125	391.31 110	1358.61 131	446.44 120	2360.09 131	2296.48 131	2290.90 133	1251.84 127	3494.04 139

tpm		2652.13 133	2606.66 137	2705.18 133	3151.86 140	6902.39 153	3612.17 144	5463.78 135	1457.76 125	391.31 110	1358.61 131	446.44 120	2360.09 131	2296.48 131	2290.90 133	1251.84 127	3494.04 139

3Dnovator+	3173.67 12	2938.77 140	2519.43 135	3428.00 142	3256.00 144	3708.00 145	3443.00 142	7516.00 146	2525.00 142	1121.00 149	972.00 121	925.00 141	3192.00 144	2899.00 144	2897.00 146	2040.00 149	3710.00 145

TSAR-MVS + ACMM		3184.92 142	2679.45 142	3774.64 148	3302.51 145	4168.07 147	4256.74 151	8947.31 151	2634.53 145	1026.25 146	1723.72 144	1043.87 150	3387.29 146	2794.29 142	2687.41 142	1727.73 146	3704.25 144

MVS_111021_HR		3192.50 143	2773.91 144	3680.86 145	3515.58 146	3815.81 146	4020.82 150	7766.11 147	2775.23 148	1300.96 155	2221.19 149	1117.25 152	3420.01 147	2873.98 143	2835.60 145	2061.69 150	3778.31 147

OPM-MVS		3051.54 141	2661.57 141	3506.50 143	3532.00 147	3332.00 143	3744.00 148	7839.00 149	2772.00 147	985.00 136	1919.00 147	738.00 131	3319.00 145	2901.00 145	2715.00 143	1620.00 144	4254.00 148

TAPA-MVS	5463.68 16	2764.21 139	2434.28 134	3149.14 141	3645.15 148	3257.60 141	3452.71 143	6526.32 142	2591.85 144	651.36 124	1964.77 148	947.44 142	2924.41 141	2523.36 139	2452.68 139	1694.86 145	3302.28 137
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
TSAR-MVS + MP.		4216.58 147	4674.68 149	3682.13 146	3752.63 149	4315.48 149	4264.77 152	7782.51 148	2583.81 143	1125.68 150	16722.30 160	882.60 138	3589.10 148	2523.80 140	2486.45 140	1578.08 143	3208.34 135

HSP-MVS		3241.28 144	2825.26 145	3726.65 147	3945.31 150	4305.03 148	4267.51 153	6962.25 144	2896.37 149	1068.15 147	1824.25 146	1061.55 151	4307.30 150	3013.40 148	3171.41 147	1809.38 148	3504.79 143

PLC	4785.50 15	3275.54 145	3030.86 146	3561.00 144	4093.00 151	4596.00 150	5174.00 156	4267.00 125	3570.00 151	1495.00 156	2940.00 153	1594.00 156	3947.00 149	3817.00 150	3343.00 149	2390.00 151	1356.00 117
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
MAR-MVS		3961.62 146	3726.55 147	4235.86 149	4107.62 152	6522.83 152	4862.93 155	7956.64 150	3380.98 150	1665.13 157	3231.54 154	1650.34 157	4357.29 151	3198.61 149	3209.42 148	2465.52 153	4892.15 150
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	4824.92 149	5020.53 150	4596.70 150	4714.52 153	3205.14 139	3108.50 138	10234.20 154	3823.34 153	1885.23 159	9002.42 157	2045.34 160	4715.23 153	7652.65 154	3993.41 150	2922.51 154	5421.41 151
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
OMC-MVS		4439.92 148	3906.78 148	5061.92 151	4748.70 154	5679.38 151	5855.03 157	9923.00 152	4023.36 154	1740.95 158	1693.78 142	1693.78 158	4658.45 152	4254.77 151	4135.74 151	3445.36 155	5866.63 152

TSAR-MVS + COLMAP		6088.23 150	5315.97 151	6989.21 152	6522.51 155	8025.15 157	7938.31 158	15276.20 155	5401.97 156	1914.31 160	3802.65 155	1979.48 159	6704.11 155	5217.07 152	5137.16 152	3579.82 156	7648.29 153

CLD-MVS		6986.85 151	6222.57 152	7878.50 153	7707.00 156	8884.00 158	9025.00 159	15607.00 156	6148.00 157	2571.00 161	4822.00 156	2082.00 161	7875.00 157	6389.00 153	6449.00 153	4486.00 157	8784.00 155
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
LS3D		7481.83 152	6596.02 153	8515.28 154	9871.71 157	9844.03 159	9225.16 160	18308.40 157	5364.90 155	1267.41 152	2381.61 151	1512.79 155	7225.72 156	8875.69 155	9516.28 154	5193.26 158	8676.83 154

MVE	11086.50 18	13278.69 154	12303.57 155	14416.33 156	9890.00 158	17107.00 161	4634.00 154	59884.00 160	3666.00 152	966.00 135	1792.00 145	896.00 140	5680.00 154	20677.00 159	23030.00 158	5444.00 159	18957.00 157
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
ACMMP		9999.00 153	9999.00 154	9999.00 155	9999.00 159	9999.00 160	9999.00 161	9999.00 153	9999.00 158	9999.00 163	9999.00 158	9999.00 163	9999.00 158	9999.00 156	9999.00 155	9999.00 160	9999.00 156
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
CNLPA		17763.08 155	15907.71 156	19927.67 157	19334.00 160	22387.00 162	22896.00 162	38668.00 158	15772.00 159	7632.00 162	13229.00 159	7123.00 162	19334.00 159	15773.00 157	15700.00 156	11702.00 161	21370.00 158

MSDG		31705.85 156	29167.57 158	34667.17 158	44079.00 161	28314.00 164	44778.00 164	43648.00 159	31045.00 161	14849.00 164	26179.00 161	13752.00 165	38088.00 161	30859.00 160	30835.00 159	22561.00 163	43189.00 160

PHI-MVS		99999.00 158	99999.00 159	99999.00 160	99999.00 162	99999.00 165	99999.00 165	99999.00 161	99999.00 162	99999.00 166	99999.00 162	99999.00 166	99999.00 162	99999.00 161	99999.00 160	99999.00 164	99999.00 161

LTVRE_ROB	38377.89 19	49656.08 157	18936.71 157	85495.33 159	306852.00 163	22526.00 163	29206.00 163	112098.00 162	30022.00 160	17348.00 165	2824.00 152	11239.00 164	29457.00 160	20569.00 158	19941.00 157	18011.00 162	25436.00 159
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
tfpn111		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

conf0.01		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

conf0.002		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

thresconf0.02		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

tfpn_n400		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

tfpnconf		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

tfpnview11		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

tfpn1000		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

tfpn_ndepth		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

conf200view11		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

thres100view900		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

tfpnnormal		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

tfpn200view9		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

view600		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

view800		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

conf0.05thres1000		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

tfpn		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

ESAPD		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

pmmvs6		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

pmmvs5		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

Anonymous20231211		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

pmmvs-eth3d		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

Anonymous20231206		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

canonicalmvs		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

anonymousdsp		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

FC-MVSNet-train		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

UA-Net		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

FC-MVSNet-test		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

sosnet-low-res		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

DI_MVS_plusplus_trai		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

HPM-MVS++		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

pm-mvs1		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

APDe-MVS		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

pmmvs4		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

test-LLR		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

TESTMET0.1,1		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

test-mter		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

testgi		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

test20.03		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

thres600view7		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

1111		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

.test1245		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

MP-MVS		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

testmvs		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

thres400		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

test123		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

thres200		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

test0.0.03 1		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

test12356		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

testus		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

pmmvs3		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

testmv		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

EMVS		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

E-PMN		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

test2356		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

test1235678		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

PGM-MVS		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

MCST-MVS		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

PMMVS2		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

PM-MVS		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

mPP-MVS					10000000.00 164							10000000.00 167

DWT-MVSNet_training		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

testpf		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

LGP-MVS_train		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

EPNet_dtu		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
EPNet		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CNVR-MVS		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

NCCC		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

CP-MVS		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

no-one		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

CPTT-MVS		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

HQP-MVS		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

IS_MVSNet		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

Vis-MVSNet (Re-imp)		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

PatchMatch-RL		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

TDRefinement		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

EPP-MVSNet		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

PMMVS		10000000.00 159	10000000.00 160	10000000.00 161	10000000.00 164	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 167	10000000.00 163	10000000.00 162	10000000.00 161	10000000.00 165	10000000.00 162

APD-MVS		1000000000.00 236	1000000000.00 237	1000000000.00 238	1000000000.00 242	1000000000.00 243	1000000000.00 244	1000000000.00 240	1000000000.00 241	1000000000.00 245	1000000000.00 240	1000000000.00 245	1000000000.00 240	1000000000.00 239	1000000000.00 238	1000000000.00 242	1000000000.00 239
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
MTAPA										41.98 70		28.43 64

MTMP										10000000.00 167		31.71 67

Patchmatch-RL test							10000000.00 166

NP-MVS									10000000.00 163

Patchmtry						1825.90 125	885.90 107	1405.90 106		1285.90 153

DeepMVS_CX						1.00 43	1.00 43	1.00 43	1.00 43	1.00 43	1.00 43	1.00 43	1.00 43	1.00 42		1.00 43	1.00 43

High-resolution multi-view benchmark