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 73	119.40 70	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 73	119.40 70	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 73	119.40 70	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 73	119.40 70	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 71	145.38 74	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 71	145.38 74	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 77	150.67 76	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 77	150.67 76	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 77	150.67 76	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 77	150.67 76	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 77	150.67 76	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 77	150.67 76	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 77	150.67 76	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 84	166.50 83	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 84	166.50 83	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 84	166.50 83	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 87	267.17 86	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 99	241.00 78	159.00 83	204.00 96	479.00 101	308.00 109	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 88	267.30 87	710.53 87	454.42 95	785.72 130	491.23 103	326.12 111	881.92 107	538.27 96	650.05 100	592.08 109	693.94 94

RPSCF		376.53 82	341.80 82	417.05 84	418.60 87	457.01 92	467.46 91	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 93	489.60 93	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 94	558.00 96	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 88	267.30 87	710.53 87	454.42 95	785.72 130	491.23 103	326.12 111	881.92 107	538.27 96	650.05 100	592.08 109	693.94 94

gg-mvs-nofinetune		557.53 93	503.49 91	620.58 94	485.90 90	370.41 88	267.30 87	710.53 87	454.42 95	785.72 130	491.23 103	326.12 111	881.92 107	538.27 96	650.05 100	592.08 109	693.94 94

CR-MVSNet		557.53 93	503.49 91	620.58 94	485.90 90	370.41 88	267.30 87	710.53 87	454.42 95	785.72 130	491.23 103	326.12 111	881.92 107	538.27 96	650.05 100	592.08 109	693.94 94

LP		413.85 84	365.67 84	470.06 86	505.99 93	560.16 95	484.94 92	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 97	578.86 97	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 96	546.00 94	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 98	552.79 95	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		858.01 106	961.99 112	736.69 99	550.05 97	1120.24 119	1212.05 121	463.05 84	485.90 99	550.05 123	580.05 110	890.05 140	559.05 94	1485.90 122	1185.90 120	1085.90 126	985.90 109

CSCG		727.26 103	663.25 104	801.94 104	590.65 98	811.25 104	854.12 107	1805.32 113	816.43 112	388.25 110	612.42 111	345.37 117	621.61 97	507.46 91	471.55 89	551.65 107	1078.31 115

IB-MVS	750.90 3	552.99 91	511.38 95	601.53 91	606.02 99	735.75 103	688.75 101	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 99	674.70 100	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	733.00 102	749.00 102	1245.00 104	525.00 101	269.00 104	445.00 99	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	670.82 100	589.81 100	765.33 103	662.52 102	701.42 100	795.24 103	1698.33 111	598.81 107	226.55 99	403.02 95	187.13 94	786.82 104	724.80 106	646.56 99	422.52 99	866.95 104

dps		534.60 89	472.40 89	607.16 92	690.38 103	718.85 101	636.03 98	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	822.10 105	808.60 104	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

casdiffmvs		654.54 97	583.51 97	737.40 100	721.80 104	822.10 105	808.60 104	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	822.10 105	808.60 104	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		712.65 101	632.59 101	806.05 106	787.79 107	936.25 111	882.47 108	1795.72 112	528.60 102	244.29 100	471.90 100	257.36 102	681.47 99	705.16 105	659.05 104	444.55 100	869.82 105

IterMVS-LS		714.97 102	638.00 103	804.77 105	793.60 108	914.20 109	886.50 110	1612.70 110	588.30 106	285.30 105	491.20 102	278.40 107	759.20 103	677.40 104	681.30 105	491.30 104	835.20 103
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
ACMH	935.68 4	948.23 108	857.00 108	1054.67 113	946.00 109	970.00 112	1125.00 118	2467.00 115	823.00 113	330.00 108	622.00 112	211.00 98	891.00 111	970.00 111	1061.00 117	569.00 108	1342.00 117
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
MVSTER		834.63 104	737.03 106	948.49 107	988.86 110	1140.51 121	1129.34 119	1832.80 114	682.42 108	319.01 106	550.98 109	311.35 110	872.51 106	763.95 107	757.83 106	548.41 106	952.20 107

ambc			999.00 113		999.00 111	999.00 113	999.00 111		999.00 117	999.00 138	999.00 124	999.00 145	999.00 113	999.00 112	999.00 112	999.00 121	999.00 110

EPMVS		999.00 110	999.00 113	999.00 109	999.00 111	999.00 113	999.00 111	999.00 96	999.00 117	999.00 138	999.00 124	999.00 145	999.00 113	999.00 112	999.00 112	999.00 121	999.00 110

sosnet		1000.00 111	1000.00 115	1000.00 110	1000.00 113	1000.00 115	1000.00 113	1000.00 97	1000.00 119	1000.00 140	1000.00 126	1000.00 147	1000.00 115	1000.00 114	1000.00 114	1000.00 123	1000.00 112

USDC		1000.00 111	1000.00 115	1000.00 110	1000.00 113	1000.00 115	1000.00 113	1000.00 97	1000.00 119	1000.00 140	1000.00 126	1000.00 147	1000.00 115	1000.00 114	1000.00 114	1000.00 123	1000.00 112

TinyColmap		1000.00 111	1000.00 115	1000.00 110	1000.00 113	1000.00 115	1000.00 113	1000.00 97	1000.00 119	1000.00 140	1000.00 126	1000.00 147	1000.00 115	1000.00 114	1000.00 114	1000.00 123	1000.00 112

ACMM	1129.18 5	1047.56 114	912.90 109	1204.67 115	1040.21 116	1016.71 118	1105.32 116	2918.67 120	813.91 111	327.22 107	665.34 113	267.72 106	1192.58 119	1091.35 118	991.88 111	643.99 114	1543.40 124
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
PatchT		878.42 107	785.05 107	987.36 108	1050.05 117	922.05 110	1111.05 117	677.05 86	950.05 115	1285.90 154	750.05 117	640.05 128	850.05 105	950.05 109	950.05 109	950.05 120	333.05 84

ACMP	1170.86 6	1091.37 116	943.23 111	1264.21 117	1112.10 118	1138.94 120	1276.90 122	2675.36 119	989.62 116	426.15 119	742.77 116	349.09 119	1454.51 124	1047.36 117	969.90 110	640.22 113	1364.94 119
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
MVS_111021_LR		1055.24 115	916.36 110	1217.27 116	1129.93 119	1268.26 122	1313.88 123	2635.76 118	923.19 114	396.92 115	704.88 115	327.66 115	1136.32 118	965.38 110	946.95 108	690.83 117	1278.20 116

TSAR-MVS + GP.		1239.27 117	1094.74 120	1407.89 119	1220.99 120	1845.47 128	1680.98 127	3191.81 121	1098.41 122	362.98 109	679.12 114	339.31 116	1323.06 121	1173.24 121	1093.83 118	667.49 115	1433.78 120

PMVS	743.55 2	836.66 105	637.90 102	1068.55 114	1306.50 121	875.12 108	1166.70 120	2629.00 117	512.24 100	196.22 94	282.69 90	237.15 100	597.87 95	842.47 108	765.54 107	514.99 105	950.09 106
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
DeepC-MVS_fast	2081.98 8	1311.87 119	1172.50 121	1474.47 120	1411.78 122	1397.23 125	1519.03 125	3401.40 124	1201.29 123	417.90 117	801.95 118	976.25 144	1409.37 122	1114.52 119	1201.12 121	687.33 116	1515.14 123
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
ACMMPR		1265.65 118	1083.59 119	1478.06 121	1441.06 123	1438.61 126	1540.68 126	3284.05 123	1219.68 124	458.81 120	803.22 119	346.91 118	1421.66 123	1126.11 120	1150.51 119	722.08 118	1500.09 122

MSLP-MVS++		993.91 109	732.21 105	1299.24 118	1631.22 124	1345.26 123	1480.05 124	2524.20 116	735.65 109	463.57 121	499.89 107	302.78 108	1292.66 120	675.99 103	612.79 95	403.71 98	953.11 108

FPMVS		1356.65 120	1072.60 118	1688.04 122	1840.79 125	1397.01 124	1793.24 128	4397.86 128	804.66 110	408.78 116	538.65 108	407.36 120	894.84 112	1587.73 123	1286.38 122	792.73 119	1486.39 121

OpenMVS	2049.89 7	1895.92 121	1721.29 122	2099.67 123	2064.00 126	2419.00 131	2138.00 129	4572.00 129	1541.00 130	548.00 122	937.00 121	580.00 126	1983.00 126	1971.00 129	1993.00 127	1293.00 133	2608.00 128

MVS-HIRNet		1975.98 122	1797.02 124	2184.76 124	2111.07 127	2443.03 132	2503.43 131	4063.71 125	1684.46 133	711.34 128	1456.05 136	848.70 138	2396.26 136	1900.93 124	1915.01 125	1322.75 134	2330.99 125

CHOSEN 280x420		2225.10 125	1992.66 128	2496.28 126	2192.10 128	2641.81 133	2621.41 133	5345.34 133	2116.46 138	1002.26 143	1683.84 140	837.43 134	2338.65 129	1920.94 126	2020.28 128	1477.92 138	2727.86 129

CHOSEN 1792x2688		2225.10 125	1992.66 128	2496.28 126	2192.10 128	2641.81 133	2621.41 133	5345.34 133	2116.46 138	1002.26 143	1683.84 140	837.43 134	2338.65 129	1920.94 126	2020.28 128	1477.92 138	2727.86 129

HyFIR lowres test		2225.10 125	1992.66 128	2496.28 126	2192.10 128	2641.81 133	2621.41 133	5345.34 133	2116.46 138	1002.26 143	1683.84 140	837.43 134	2338.65 129	1920.94 126	2020.28 128	1477.92 138	2727.86 129

PCF-MVS	3738.24 13	2129.60 124	1746.89 123	2576.10 131	2258.22 131	2263.67 129	2650.06 136	6361.78 142	1676.15 132	695.66 127	1209.77 130	737.88 131	2237.28 127	2083.02 131	1835.31 123	1253.58 132	2422.45 126
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
DeepPCF-MVS	3033.31 11	2362.79 131	2183.15 133	2572.38 130	2349.28 132	2383.16 130	2740.92 137	5212.97 132	2043.02 137	751.44 129	1466.47 137	1327.42 155	2904.33 141	2573.45 142	2227.77 132	1475.33 137	3260.73 137

tpmrst		2688.71 138	2604.46 137	2787.00 138	2472.96 133	3190.36 140	3313.69 142	5003.06 131	1837.26 134	1097.38 149	1721.89 144	1012.20 150	2415.09 137	2970.27 148	2736.80 145	2419.79 153	4762.44 150

AdaColmap		2288.90 128	2080.73 132	2531.77 129	2485.98 134	2757.87 136	2974.47 138	4914.62 130	2255.54 141	804.63 134	1611.14 139	842.30 137	2657.83 139	2056.92 130	1960.62 126	1353.09 135	3080.73 134

CMPMVS	2507.20 10	2083.60 123	1983.13 127	2200.81 125	2582.70 135	3097.30 139	2332.10 130	4364.50 127	1390.00 125	653.68 126	997.75 123	742.65 133	1880.20 125	2298.80 136	2413.60 139	1391.70 136	2941.80 133
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
3Dnovator	2220.89 9	2303.77 129	2037.00 131	2615.00 132	2617.00 136	2967.00 138	2616.00 132	5882.00 140	1928.00 136	589.00 124	907.00 120	528.00 125	2443.00 138	2370.00 138	2392.00 138	1543.00 142	3167.00 135

Vis-MVSNet		2390.77 132	1976.57 126	2874.00 140	2644.00 137	3248.00 142	3040.00 139	7371.00 146	1627.00 131	421.00 118	1200.00 129	622.00 127	2251.00 128	2326.00 137	2052.00 131	1517.00 141	2761.00 132
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
SteuartSystems-ACMMP		2615.00 133	2242.57 134	3049.50 141	2828.00 138	2801.00 137	3323.00 143	6648.00 144	2491.00 142	1023.00 146	1605.00 138	697.00 130	2926.00 143	2502.00 139	2279.00 133	1549.00 143	3323.00 139
Skip Steuart: Steuart Systems R&D Blog.
SD-MVS		2324.36 130	1910.97 125	2806.65 139	2945.31 139	3305.03 144	3267.51 141	5962.25 141	1896.37 135	848.15 135	1224.25 131	661.55 129	2707.30 140	1913.40 125	1871.41 124	1109.38 127	2504.79 127

COLMAP_ROB	3798.28 14	2690.62 139	2704.29 144	2674.67 133	3138.00 140	3522.00 146	3826.00 151	3219.00 122	2702.00 147	1138.00 152	2260.00 151	1212.00 154	2968.00 144	2936.00 147	2571.00 142	1759.00 148	3727.00 147
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
tpm cat1		2652.13 134	2606.66 138	2705.18 134	3151.86 141	6902.39 155	3612.17 146	5463.78 136	1457.76 126	391.31 111	1358.61 132	446.44 121	2360.09 132	2296.48 132	2290.90 134	1251.84 128	3494.04 140

tpmp4_e23		2652.13 134	2606.66 138	2705.18 134	3151.86 141	6902.39 155	3612.17 146	5463.78 136	1457.76 126	391.31 111	1358.61 132	446.44 121	2360.09 132	2296.48 132	2290.90 134	1251.84 128	3494.04 140

CostFormer		2652.13 134	2606.66 138	2705.18 134	3151.86 141	6902.39 155	3612.17 146	5463.78 136	1457.76 126	391.31 111	1358.61 132	446.44 121	2360.09 132	2296.48 132	2290.90 134	1251.84 128	3494.04 140

tpm		2652.13 134	2606.66 138	2705.18 134	3151.86 141	6902.39 155	3612.17 146	5463.78 136	1457.76 126	391.31 111	1358.61 132	446.44 121	2360.09 132	2296.48 132	2290.90 134	1251.84 128	3494.04 140

3Dnovator+	3173.67 12	2938.77 141	2519.43 136	3428.00 143	3256.00 145	3708.00 147	3443.00 144	7516.00 147	2525.00 143	1121.00 150	972.00 122	925.00 142	3192.00 145	2899.00 145	2897.00 147	2040.00 150	3710.00 146

TSAR-MVS + ACMM		3184.92 143	2679.45 143	3774.64 149	3302.51 146	4168.07 149	4256.74 153	8947.31 152	2634.53 146	1026.25 147	1723.72 145	1043.87 151	3387.29 147	2794.29 143	2687.41 143	1727.73 147	3704.25 145

MVS_111021_HR		3192.50 144	2773.91 145	3680.86 146	3515.58 147	3815.81 148	4020.82 152	7766.11 148	2775.23 149	1300.96 156	2221.19 150	1117.25 153	3420.01 148	2873.98 144	2835.60 146	2061.69 151	3778.31 148

OPM-MVS		3051.54 142	2661.57 142	3506.50 144	3532.00 148	3332.00 145	3744.00 150	7839.00 150	2772.00 148	985.00 137	1919.00 148	738.00 132	3319.00 146	2901.00 146	2715.00 144	1620.00 145	4254.00 149

TAPA-MVS	5463.68 16	2764.21 140	2434.28 135	3149.14 142	3645.15 149	3257.60 143	3452.71 145	6526.32 143	2591.85 145	651.36 125	1964.77 149	947.44 143	2924.41 142	2523.36 140	2452.68 140	1694.86 146	3302.28 138
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
TSAR-MVS + MP.		4216.58 148	4674.68 150	3682.13 147	3752.63 150	4315.48 151	4264.77 154	7782.51 149	2583.81 144	1125.68 151	16722.30 161	882.60 139	3589.10 149	2523.80 141	2486.45 141	1578.08 144	3208.34 136

HSP-MVS		3241.28 145	2825.26 146	3726.65 148	3945.31 151	4305.03 150	4267.51 155	6962.25 145	2896.37 150	1068.15 148	1824.25 147	1061.55 152	4307.30 151	3013.40 149	3171.41 148	1809.38 149	3504.79 144

PLC	4785.50 15	3275.54 146	3030.86 147	3561.00 145	4093.00 152	4596.00 152	5174.00 158	4267.00 126	3570.00 152	1495.00 157	2940.00 154	1594.00 157	3947.00 150	3817.00 151	3343.00 150	2390.00 152	1356.00 118
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
MAR-MVS		3961.62 147	3726.55 148	4235.86 150	4107.62 153	6522.83 154	4862.93 157	7956.64 151	3380.98 151	1665.13 158	3231.54 155	1650.34 158	4357.29 152	3198.61 150	3209.42 149	2465.52 154	4892.15 151
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	4824.92 150	5020.53 151	4596.70 151	4714.52 154	3205.14 141	3108.50 140	10234.20 155	3823.34 154	1885.23 160	9002.42 158	2045.34 161	4715.23 154	7652.65 155	3993.41 151	2922.51 155	5421.41 152
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
OMC-MVS		4439.92 149	3906.78 149	5061.92 152	4748.70 155	5679.38 153	5855.03 159	9923.00 153	4023.36 155	1740.95 159	1693.78 143	1693.78 159	4658.45 153	4254.77 152	4135.74 152	3445.36 156	5866.63 153

TSAR-MVS + COLMAP		6088.23 151	5315.97 152	6989.21 153	6522.51 156	8025.15 159	7938.31 160	15276.20 156	5401.97 157	1914.31 161	3802.65 156	1979.48 160	6704.11 156	5217.07 153	5137.16 153	3579.82 157	7648.29 154

CLD-MVS		6986.85 152	6222.57 153	7878.50 154	7707.00 157	8884.00 160	9025.00 161	15607.00 157	6148.00 158	2571.00 162	4822.00 157	2082.00 162	7875.00 158	6389.00 154	6449.00 154	4486.00 158	8784.00 156
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
LS3D		7481.83 153	6596.02 154	8515.28 155	9871.71 158	9844.03 161	9225.16 162	18308.40 158	5364.90 156	1267.41 153	2381.61 152	1512.79 156	7225.72 157	8875.69 156	9516.28 155	5193.26 159	8676.83 155

MVE	11086.50 18	13278.69 155	12303.57 156	14416.33 157	9890.00 159	17107.00 163	4634.00 156	59884.00 161	3666.00 153	966.00 136	1792.00 146	896.00 141	5680.00 155	20677.00 160	23030.00 159	5444.00 160	18957.00 158
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
our_test_3					9999.00 160	99.00 70	99.00 69

ACMMP		9999.00 154	9999.00 155	9999.00 156	9999.00 160	9999.00 162	9999.00 163	9999.00 154	9999.00 159	9999.00 164	9999.00 159	9999.00 164	9999.00 159	9999.00 157	9999.00 156	9999.00 161	9999.00 157
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		17763.08 156	15907.71 157	19927.67 158	19334.00 162	22387.00 164	22896.00 164	38668.00 159	15772.00 160	7632.00 163	13229.00 160	7123.00 163	19334.00 160	15773.00 158	15700.00 157	11702.00 162	21370.00 159

MSDG		31705.85 157	29167.57 159	34667.17 159	44079.00 163	28314.00 166	44778.00 166	43648.00 160	31045.00 162	14849.00 165	26179.00 162	13752.00 166	38088.00 162	30859.00 161	30835.00 160	22561.00 164	43189.00 161

PHI-MVS		99999.00 159	99999.00 160	99999.00 161	99999.00 164	99999.00 167	99999.00 167	99999.00 162	99999.00 163	99999.00 167	99999.00 163	99999.00 167	99999.00 163	99999.00 162	99999.00 161	99999.00 165	99999.00 162

LTVRE_ROB	38377.89 19	49656.08 158	18936.71 158	85495.33 160	306852.00 165	22526.00 165	29206.00 165	112098.00 163	30022.00 161	17348.00 166	2824.00 153	11239.00 165	29457.00 161	20569.00 159	19941.00 158	18011.00 163	25436.00 160
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
Anonymous20240521		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

tfpn111		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

conf0.01		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

conf0.002		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

thresconf0.02		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

tfpn_n400		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

tfpnconf		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

tfpnview11		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

tfpn1000		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

tfpn_ndepth		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

conf200view11		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

thres100view900		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

tfpnnormal		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

tfpn200view9		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

view600		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

view800		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

conf0.05thres1000		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

tfpn		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

ESAPD		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

pmmvs6		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

pmmvs5		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

Anonymous20231211		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

pmmvs-eth3d		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

Anonymous20231206		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

canonicalmvs		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

anonymousdsp		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

FC-MVSNet-train		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

UA-Net		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

FC-MVSNet-test		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

sosnet-low-res		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

DI_MVS_plusplus_trai		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

HPM-MVS++		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

pm-mvs1		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

APDe-MVS		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

pmmvs4		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

test-LLR		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

TESTMET0.1,1		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

test-mter		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

testgi		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

test20.03		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

thres600view7		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

1111		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

.test1245		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

MP-MVS		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
testmvs		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

thres400		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

test123		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

thres200		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

test0.0.03 1		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

test12356		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

testus		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

pmmvs3		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

testmv		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

EMVS		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

E-PMN		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

test2356		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

test1235678		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

PGM-MVS		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

MCST-MVS		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

PMMVS2		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

PM-MVS		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

mPP-MVS					10000000.00 166							10000000.00 168

DWT-MVSNet_training		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

testpf		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

LGP-MVS_train		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

EPNet_dtu		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
EPNet		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CNVR-MVS		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

NCCC		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

CP-MVS		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

no-one		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

CPTT-MVS		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

HQP-MVS		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

IS_MVSNet		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

Vis-MVSNet (Re-imp)		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

PatchMatch-RL		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

TDRefinement		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

EPP-MVSNet		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

PMMVS		10000000.00 160	10000000.00 161	10000000.00 162	10000000.00 166	10000000.00 168	10000000.00 168	10000000.00 164	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 168	10000000.00 164	10000000.00 163	10000000.00 162	10000000.00 166	10000000.00 163

APD-MVS		1000000000.00 238	1000000000.00 239	1000000000.00 240	1000000000.00 245	1000000000.00 246	1000000000.00 247	1000000000.00 242	1000000000.00 243	1000000000.00 247	1000000000.00 242	1000000000.00 247	1000000000.00 242	1000000000.00 241	1000000000.00 240	1000000000.00 244	1000000000.00 241
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
MTAPA										41.98 70		28.43 64

MTMP										10000000.00 168		31.71 67

Patchmatch-RL test							10000000.00 168

NP-MVS									10000000.00 164

Patchmtry						1825.90 127	885.90 109	1405.90 106		1285.90 154

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