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

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

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
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

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

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

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

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

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

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

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.
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
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

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	785.72 131	491.23 104	326.12 112	881.92 108	538.27 96	650.05 101	592.08 110	693.94 94

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.
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	785.72 131	491.23 104	326.12 112	881.92 108	538.27 96	650.05 101	592.08 110	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	785.72 131	491.23 104	326.12 112	881.92 108	538.27 96	650.05 101	592.08 110	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	785.72 131	491.23 104	326.12 112	881.92 108	538.27 96	650.05 101	592.08 110	693.94 94

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	269.00 105	445.00 100	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
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

casdiffmvs1		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

ACMH+	702.88 1	670.82 101	589.81 101	765.33 104	662.52 102	701.42 100	795.24 103	1698.33 112	598.81 108	226.55 99	403.02 95	187.13 94	786.82 105	724.80 107	646.56 100	422.52 99	866.95 105

new-patchmatchnet		712.65 102	632.59 102	806.05 107	787.79 108	936.25 112	882.47 109	1795.72 113	528.60 102	244.29 100	471.90 101	257.36 102	681.47 99	705.16 106	659.05 105	444.55 100	869.82 106

IterMVS-LS		714.97 103	638.00 104	804.77 106	793.60 109	914.20 110	886.50 111	1612.70 111	588.30 107	285.30 106	491.20 103	278.40 108	759.20 104	677.40 105	681.30 106	491.30 105	835.20 104
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CSCG		727.26 104	663.25 105	801.94 105	590.65 98	811.25 104	854.12 108	1805.32 114	816.43 113	388.25 111	612.42 112	345.37 118	621.61 97	507.46 91	471.55 89	551.65 108	1078.31 116

MVSTER		834.63 105	737.03 107	948.49 108	988.86 111	1140.51 122	1129.34 120	1832.80 115	682.42 109	319.01 107	550.98 110	311.35 111	872.51 107	763.95 108	757.83 107	548.41 107	952.20 108

PMVS	743.55 2	836.66 106	637.90 103	1068.55 115	1306.50 122	875.12 109	1166.70 121	2629.00 118	512.24 100	196.22 94	282.69 90	237.15 100	597.87 95	842.47 109	765.54 108	514.99 106	950.09 107
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
RPMNet		858.01 107	961.99 113	736.69 99	550.05 97	1120.24 120	1212.05 122	463.05 84	485.90 99	550.05 124	580.05 111	890.05 141	559.05 94	1485.90 123	1185.90 121	1085.90 127	985.90 110

PatchT		878.42 108	785.05 108	987.36 109	1050.05 118	922.05 111	1111.05 118	677.05 86	950.05 116	1285.90 155	750.05 118	640.05 129	850.05 106	950.05 110	950.05 110	950.05 121	333.05 84

ACMH	935.68 4	948.23 109	857.00 109	1054.67 114	946.00 110	970.00 113	1125.00 119	2467.00 116	823.00 114	330.00 109	622.00 113	211.00 98	891.00 112	970.00 112	1061.00 118	569.00 109	1342.00 118
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
MSLP-MVS++		993.91 110	732.21 106	1299.24 119	1631.22 125	1345.26 124	1480.05 125	2524.20 117	735.65 110	463.57 122	499.89 108	302.78 109	1292.66 121	675.99 104	612.79 95	403.71 98	953.11 109

EPMVS		999.00 111	999.00 114	999.00 110	999.00 112	999.00 114	999.00 112	999.00 96	999.00 118	999.00 139	999.00 125	999.00 146	999.00 114	999.00 113	999.00 113	999.00 122	999.00 111

sosnet		1000.00 112	1000.00 116	1000.00 111	1000.00 114	1000.00 116	1000.00 114	1000.00 97	1000.00 120	1000.00 141	1000.00 127	1000.00 148	1000.00 116	1000.00 115	1000.00 115	1000.00 124	1000.00 113

USDC		1000.00 112	1000.00 116	1000.00 111	1000.00 114	1000.00 116	1000.00 114	1000.00 97	1000.00 120	1000.00 141	1000.00 127	1000.00 148	1000.00 116	1000.00 115	1000.00 115	1000.00 124	1000.00 113

TinyColmap		1000.00 112	1000.00 116	1000.00 111	1000.00 114	1000.00 116	1000.00 114	1000.00 97	1000.00 120	1000.00 141	1000.00 127	1000.00 148	1000.00 116	1000.00 115	1000.00 115	1000.00 124	1000.00 113

ACMM	1129.18 5	1047.56 115	912.90 110	1204.67 116	1040.21 117	1016.71 119	1105.32 117	2918.67 121	813.91 112	327.22 108	665.34 114	267.72 107	1192.58 120	1091.35 119	991.88 112	643.99 115	1543.40 125
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
MVS_111021_LR		1055.24 116	916.36 111	1217.27 117	1129.93 120	1268.26 123	1313.88 124	2635.76 119	923.19 115	396.92 116	704.88 116	327.66 116	1136.32 119	965.38 111	946.95 109	690.83 118	1278.20 117

ACMP	1170.86 6	1091.37 117	943.23 112	1264.21 118	1112.10 119	1138.94 121	1276.90 123	2675.36 120	989.62 117	426.15 120	742.77 117	349.09 120	1454.51 125	1047.36 118	969.90 111	640.22 114	1364.94 120
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
TSAR-MVS + GP.		1239.27 118	1094.74 121	1407.89 120	1220.99 121	1845.47 129	1680.98 128	3191.81 122	1098.41 123	362.98 110	679.12 115	339.31 117	1323.06 122	1173.24 122	1093.83 119	667.49 116	1433.78 121

ACMMPR		1265.65 119	1083.59 120	1478.06 122	1441.06 124	1438.61 127	1540.68 127	3284.05 124	1219.68 125	458.81 121	803.22 120	346.91 119	1421.66 124	1126.11 121	1150.51 120	722.08 119	1500.09 123

DeepC-MVS_fast	2081.98 8	1311.87 120	1172.50 122	1474.47 121	1411.78 123	1397.23 126	1519.03 126	3401.40 125	1201.29 124	417.90 118	801.95 119	976.25 145	1409.37 123	1114.52 120	1201.12 122	687.33 117	1515.14 124
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
FPMVS		1356.65 121	1072.60 119	1688.04 123	1840.79 126	1397.01 125	1793.24 129	4397.86 129	804.66 111	408.78 117	538.65 109	407.36 121	894.84 113	1587.73 124	1286.38 123	792.73 120	1486.39 122

OpenMVS	2049.89 7	1895.92 122	1721.29 123	2099.67 124	2064.00 127	2419.00 132	2138.00 130	4572.00 130	1541.00 131	548.00 123	937.00 122	580.00 127	1983.00 127	1971.00 130	1993.00 128	1293.00 134	2608.00 129

MVS-HIRNet		1975.98 123	1797.02 125	2184.76 125	2111.07 128	2443.03 133	2503.43 132	4063.71 126	1684.46 134	711.34 129	1456.05 137	848.70 139	2396.26 137	1900.93 125	1915.01 126	1322.75 135	2330.99 126

CMPMVS	2507.20 10	2083.60 124	1983.13 128	2200.81 126	2582.70 136	3097.30 140	2332.10 131	4364.50 128	1390.00 126	653.68 127	997.75 124	742.65 134	1880.20 126	2298.80 137	2413.60 140	1391.70 137	2941.80 134
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
PCF-MVS	3738.24 13	2129.60 125	1746.89 124	2576.10 132	2258.22 132	2263.67 130	2650.06 137	6361.78 143	1676.15 133	695.66 128	1209.77 131	737.88 132	2237.28 128	2083.02 132	1835.31 124	1253.58 133	2422.45 127
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
CHOSEN 280x420		2225.10 126	1992.66 129	2496.28 127	2192.10 129	2641.81 134	2621.41 134	5345.34 134	2116.46 139	1002.26 144	1683.84 141	837.43 135	2338.65 130	1920.94 127	2020.28 129	1477.92 139	2727.86 130

CHOSEN 1792x2688		2225.10 126	1992.66 129	2496.28 127	2192.10 129	2641.81 134	2621.41 134	5345.34 134	2116.46 139	1002.26 144	1683.84 141	837.43 135	2338.65 130	1920.94 127	2020.28 129	1477.92 139	2727.86 130

HyFIR lowres test		2225.10 126	1992.66 129	2496.28 127	2192.10 129	2641.81 134	2621.41 134	5345.34 134	2116.46 139	1002.26 144	1683.84 141	837.43 135	2338.65 130	1920.94 127	2020.28 129	1477.92 139	2727.86 130

AdaColmap		2288.90 129	2080.73 133	2531.77 130	2485.98 135	2757.87 137	2974.47 139	4914.62 131	2255.54 142	804.63 135	1611.14 140	842.30 138	2657.83 140	2056.92 131	1960.62 127	1353.09 136	3080.73 135

3Dnovator	2220.89 9	2303.77 130	2037.00 132	2615.00 133	2617.00 137	2967.00 139	2616.00 133	5882.00 141	1928.00 137	589.00 125	907.00 121	528.00 126	2443.00 139	2370.00 139	2392.00 139	1543.00 143	3167.00 136

SD-MVS		2324.36 131	1910.97 126	2806.65 140	2945.31 140	3305.03 145	3267.51 142	5962.25 142	1896.37 136	848.15 136	1224.25 132	661.55 130	2707.30 141	1913.40 126	1871.41 125	1109.38 128	2504.79 128

DeepPCF-MVS	3033.31 11	2362.79 132	2183.15 134	2572.38 131	2349.28 133	2383.16 131	2740.92 138	5212.97 133	2043.02 138	751.44 130	1466.47 138	1327.42 156	2904.33 142	2573.45 143	2227.77 133	1475.33 138	3260.73 138

Vis-MVSNet		2390.77 133	1976.57 127	2874.00 141	2644.00 138	3248.00 143	3040.00 140	7371.00 147	1627.00 132	421.00 119	1200.00 130	622.00 128	2251.00 129	2326.00 138	2052.00 132	1517.00 142	2761.00 133
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
SteuartSystems-ACMMP		2615.00 134	2242.57 135	3049.50 142	2828.00 139	2801.00 138	3323.00 144	6648.00 145	2491.00 143	1023.00 147	1605.00 139	697.00 131	2926.00 144	2502.00 140	2279.00 134	1549.00 144	3323.00 140
Skip Steuart: Steuart Systems R&D Blog.
tpm cat1		2652.13 135	2606.66 139	2705.18 135	3151.86 142	6902.39 156	3612.17 147	5463.78 137	1457.76 127	391.31 112	1358.61 133	446.44 122	2360.09 133	2296.48 133	2290.90 135	1251.84 129	3494.04 141

tpmp4_e23		2652.13 135	2606.66 139	2705.18 135	3151.86 142	6902.39 156	3612.17 147	5463.78 137	1457.76 127	391.31 112	1358.61 133	446.44 122	2360.09 133	2296.48 133	2290.90 135	1251.84 129	3494.04 141

CostFormer		2652.13 135	2606.66 139	2705.18 135	3151.86 142	6902.39 156	3612.17 147	5463.78 137	1457.76 127	391.31 112	1358.61 133	446.44 122	2360.09 133	2296.48 133	2290.90 135	1251.84 129	3494.04 141

tpm		2652.13 135	2606.66 139	2705.18 135	3151.86 142	6902.39 156	3612.17 147	5463.78 137	1457.76 127	391.31 112	1358.61 133	446.44 122	2360.09 133	2296.48 133	2290.90 135	1251.84 129	3494.04 141

tpmrst		2688.71 139	2604.46 138	2787.00 139	2472.96 134	3190.36 141	3313.69 143	5003.06 132	1837.26 135	1097.38 150	1721.89 145	1012.20 151	2415.09 138	2970.27 149	2736.80 146	2419.79 154	4762.44 151

COLMAP_ROB	3798.28 14	2690.62 140	2704.29 145	2674.67 134	3138.00 141	3522.00 147	3826.00 152	3219.00 123	2702.00 148	1138.00 153	2260.00 152	1212.00 155	2968.00 145	2936.00 148	2571.00 143	1759.00 149	3727.00 148
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
TAPA-MVS	5463.68 16	2764.21 141	2434.28 136	3149.14 143	3645.15 150	3257.60 144	3452.71 146	6526.32 144	2591.85 146	651.36 126	1964.77 150	947.44 144	2924.41 143	2523.36 141	2452.68 141	1694.86 147	3302.28 139
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
3Dnovator+	3173.67 12	2938.77 142	2519.43 137	3428.00 144	3256.00 146	3708.00 148	3443.00 145	7516.00 148	2525.00 144	1121.00 151	972.00 123	925.00 143	3192.00 146	2899.00 146	2897.00 148	2040.00 151	3710.00 147

OPM-MVS		3051.54 143	2661.57 143	3506.50 145	3532.00 149	3332.00 146	3744.00 151	7839.00 151	2772.00 149	985.00 138	1919.00 149	738.00 133	3319.00 147	2901.00 147	2715.00 145	1620.00 146	4254.00 150

TSAR-MVS + ACMM		3184.92 144	2679.45 144	3774.64 150	3302.51 147	4168.07 150	4256.74 154	8947.31 153	2634.53 147	1026.25 148	1723.72 146	1043.87 152	3387.29 148	2794.29 144	2687.41 144	1727.73 148	3704.25 146

MVS_111021_HR		3192.50 145	2773.91 146	3680.86 147	3515.58 148	3815.81 149	4020.82 153	7766.11 149	2775.23 150	1300.96 157	2221.19 151	1117.25 154	3420.01 149	2873.98 145	2835.60 147	2061.69 152	3778.31 149

HSP-MVS		3241.28 146	2825.26 147	3726.65 149	3945.31 152	4305.03 151	4267.51 156	6962.25 146	2896.37 151	1068.15 149	1824.25 148	1061.55 153	4307.30 152	3013.40 150	3171.41 149	1809.38 150	3504.79 145

PLC	4785.50 15	3275.54 147	3030.86 148	3561.00 146	4093.00 153	4596.00 153	5174.00 159	4267.00 127	3570.00 153	1495.00 158	2940.00 155	1594.00 158	3947.00 151	3817.00 152	3343.00 151	2390.00 153	1356.00 119
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
MAR-MVS		3961.62 148	3726.55 149	4235.86 151	4107.62 154	6522.83 155	4862.93 158	7956.64 152	3380.98 152	1665.13 159	3231.54 156	1650.34 159	4357.29 153	3198.61 151	3209.42 150	2465.52 155	4892.15 152
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
TSAR-MVS + MP.		4216.58 149	4674.68 151	3682.13 148	3752.63 151	4315.48 152	4264.77 155	7782.51 150	2583.81 145	1125.68 152	16722.30 162	882.60 140	3589.10 150	2523.80 142	2486.45 142	1578.08 145	3208.34 137

OMC-MVS		4439.92 150	3906.78 150	5061.92 153	4748.70 156	5679.38 154	5855.03 160	9923.00 154	4023.36 156	1740.95 160	1693.78 144	1693.78 160	4658.45 154	4254.77 153	4135.74 153	3445.36 157	5866.63 154

DeepC-MVS	5581.15 17	4824.92 151	5020.53 152	4596.70 152	4714.52 155	3205.14 142	3108.50 141	10234.20 156	3823.34 155	1885.23 161	9002.42 159	2045.34 162	4715.23 155	7652.65 156	3993.41 152	2922.51 156	5421.41 153
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
TSAR-MVS + COLMAP		6088.23 152	5315.97 153	6989.21 154	6522.51 157	8025.15 160	7938.31 161	15276.20 157	5401.97 158	1914.31 162	3802.65 157	1979.48 161	6704.11 157	5217.07 154	5137.16 154	3579.82 158	7648.29 155

CLD-MVS		6986.85 153	6222.57 154	7878.50 155	7707.00 158	8884.00 161	9025.00 162	15607.00 158	6148.00 159	2571.00 163	4822.00 158	2082.00 163	7875.00 159	6389.00 155	6449.00 155	4486.00 159	8784.00 157
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
LS3D		7481.83 154	6596.02 155	8515.28 156	9871.71 159	9844.03 162	9225.16 163	18308.40 159	5364.90 157	1267.41 154	2381.61 153	1512.79 157	7225.72 158	8875.69 157	9516.28 156	5193.26 160	8676.83 156

ACMMP		9999.00 155	9999.00 156	9999.00 157	9999.00 161	9999.00 163	9999.00 164	9999.00 155	9999.00 160	9999.00 165	9999.00 160	9999.00 165	9999.00 160	9999.00 158	9999.00 157	9999.00 162	9999.00 158
Qingshan Xu, Weihang Kong, Wenbing Tao, Marc Pollefeys: Multi-Scale Geometric Consistency Guided and Planar Prior Assisted Multi-View Stereo. IEEE Transactions on Pattern Analysis and Machine Intelligence
MVE	11086.50 18	13278.69 156	12303.57 157	14416.33 158	9890.00 160	17107.00 164	4634.00 157	59884.00 162	3666.00 154	966.00 137	1792.00 147	896.00 142	5680.00 156	20677.00 161	23030.00 160	5444.00 161	18957.00 159
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
CNLPA		17763.08 157	15907.71 158	19927.67 159	19334.00 163	22387.00 165	22896.00 165	38668.00 160	15772.00 161	7632.00 164	13229.00 161	7123.00 164	19334.00 161	15773.00 159	15700.00 158	11702.00 163	21370.00 160

MSDG		31705.85 158	29167.57 160	34667.17 160	44079.00 164	28314.00 167	44778.00 167	43648.00 161	31045.00 163	14849.00 166	26179.00 163	13752.00 167	38088.00 163	30859.00 162	30835.00 161	22561.00 165	43189.00 162

LTVRE_ROB	38377.89 19	49656.08 159	18936.71 159	85495.33 161	306852.00 166	22526.00 166	29206.00 166	112098.00 164	30022.00 162	17348.00 167	2824.00 154	11239.00 166	29457.00 162	20569.00 160	19941.00 159	18011.00 164	25436.00 161
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
PHI-MVS		99999.00 160	99999.00 161	99999.00 162	99999.00 165	99999.00 168	99999.00 168	99999.00 163	99999.00 164	99999.00 168	99999.00 164	99999.00 168	99999.00 164	99999.00 163	99999.00 162	99999.00 166	99999.00 163

Anonymous20240521		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

tfpn111		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

conf0.01		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

ESAPD		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

conf0.002		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

thresconf0.02		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

tfpn_n400		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

tfpnconf		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

tfpnview11		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

tfpn1000		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

tfpn_ndepth		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

conf200view11		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

thres100view900		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

tfpnnormal		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

tfpn200view9		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

view600		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

view800		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

conf0.05thres1000		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

tfpn		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

v1.0		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

pmmvs6		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

pmmvs5		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

Anonymous20231211		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

pmmvs-eth3d		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

Anonymous20231206		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

canonicalmvs		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

anonymousdsp		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

FC-MVSNet-train		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

UA-Net		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

FC-MVSNet-test		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

sosnet-low-res		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

DI_MVS_plusplus_trai		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

HPM-MVS++		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

pm-mvs1		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

APDe-MVS		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

pmmvs4		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

test-LLR		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

TESTMET0.1,1		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

test-mter		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

testgi		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

test20.03		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

thres600view7		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

1111		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

.test1245		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

MP-MVS		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
testmvs		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

thres400		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

test123		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

thres200		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

test0.0.03 1		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

test12356		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

testus		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

pmmvs3		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

testmv		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

EMVS		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

E-PMN		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

test2356		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

test1235678		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

PGM-MVS		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

MCST-MVS		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

PMMVS2		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

PM-MVS		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

DWT-MVSNet_training		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

testpf		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

LGP-MVS_train		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

EPNet_dtu		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
EPNet		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CNVR-MVS		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

NCCC		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

CP-MVS		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

no-one		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

CPTT-MVS		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

HQP-MVS		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

IS_MVSNet		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

Vis-MVSNet (Re-imp)		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

PatchMatch-RL		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

TDRefinement		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

EPP-MVSNet		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

PMMVS		10000000.00 161	10000000.00 162	10000000.00 163	10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

APD-MVS		1000000000.00 240	1000000000.00 242	1000000000.00 242	1000000000.00 248	1000000000.00 249	1000000000.00 250	1000000000.00 245	1000000000.00 246	1000000000.00 249	1000000000.00 245	1000000000.00 250	1000000000.00 245	1000000000.00 244	1000000000.00 243	1000000000.00 247	1000000000.00 244
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
Anonymous202405211			10000000.00 162		10000000.00 167	10000000.00 169	10000000.00 169	10000000.00 165	10000000.00 165		10000000.00 165	10000000.00 169	10000000.00 165	10000000.00 164	10000000.00 163	10000000.00 167	10000000.00 164

our_test_3					9999.00 161	99.00 70	99.00 69

ambc			999.00 114		999.00 112	999.00 114	999.00 112		999.00 118	999.00 139	999.00 125	999.00 146	999.00 114	999.00 113	999.00 113	999.00 122	999.00 111

MTAPA										41.98 70		28.43 64

MTMP										10000000.00 169		31.71 67

Patchmatch-RL test							10000000.00 169

tmp_tt				299.50 83	365.00 85	54.00 67	649.00 99	241.00 78	159.00 83	204.00 96	479.00 102	308.00 110	243.00 84	246.00 83	82.00 65	95.00 85

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

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

mPP-MVS					10000000.00 167							10000000.00 169

NP-MVS									10000000.00 165

Patchmtry						1825.90 128	885.90 110	1405.90 106		1285.90 155

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