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
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

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

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	785.72 132	491.23 105	326.12 113	881.92 109	538.27 96	650.05 102	592.08 111	693.94 94

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	785.72 132	491.23 105	326.12 113	881.92 109	538.27 96	650.05 102	592.08 111	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	785.72 132	491.23 105	326.12 113	881.92 109	538.27 96	650.05 102	592.08 111	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	785.72 132	491.23 105	326.12 113	881.92 109	538.27 96	650.05 102	592.08 111	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
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	269.00 106	445.00 101	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

diffmvs1		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	670.82 102	589.81 102	765.33 105	662.52 102	701.42 100	795.24 103	1698.33 113	598.81 109	226.55 99	403.02 95	187.13 94	786.82 106	724.80 108	646.56 101	422.52 99	866.95 106

new-patchmatchnet		712.65 103	632.59 103	806.05 108	787.79 109	936.25 113	882.47 110	1795.72 114	528.60 102	244.29 100	471.90 102	257.36 102	681.47 99	705.16 107	659.05 106	444.55 100	869.82 107

PMVS	743.55 2	836.66 107	637.90 104	1068.55 116	1306.50 123	875.12 110	1166.70 122	2629.00 119	512.24 100	196.22 94	282.69 90	237.15 100	597.87 95	842.47 110	765.54 109	514.99 107	950.09 108
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
IterMVS-LS		714.97 104	638.00 105	804.77 107	793.60 110	914.20 111	886.50 112	1612.70 112	588.30 108	285.30 107	491.20 104	278.40 109	759.20 105	677.40 106	681.30 107	491.30 106	835.20 105
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CSCG		727.26 105	663.25 106	801.94 106	590.65 98	811.25 104	854.12 109	1805.32 115	816.43 114	388.25 112	612.42 113	345.37 119	621.61 97	507.46 91	471.55 89	551.65 109	1078.31 117

MSLP-MVS++		993.91 111	732.21 107	1299.24 120	1631.22 126	1345.26 125	1480.05 126	2524.20 118	735.65 111	463.57 123	499.89 109	302.78 110	1292.66 122	675.99 105	612.79 95	403.71 98	953.11 110

MVSTER		834.63 106	737.03 108	948.49 109	988.86 112	1140.51 123	1129.34 121	1832.80 116	682.42 110	319.01 108	550.98 111	311.35 112	872.51 108	763.95 109	757.83 108	548.41 108	952.20 109

PatchT		878.42 109	785.05 109	987.36 110	1050.05 119	922.05 112	1111.05 119	677.05 86	950.05 117	1285.90 156	750.05 119	640.05 130	850.05 107	950.05 111	950.05 111	950.05 122	333.05 84

ACMH	935.68 4	948.23 110	857.00 110	1054.67 115	946.00 111	970.00 114	1125.00 120	2467.00 117	823.00 115	330.00 110	622.00 114	211.00 98	891.00 113	970.00 113	1061.00 119	569.00 110	1342.00 119
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
ACMM	1129.18 5	1047.56 116	912.90 111	1204.67 117	1040.21 118	1016.71 120	1105.32 118	2918.67 122	813.91 113	327.22 109	665.34 115	267.72 108	1192.58 121	1091.35 120	991.88 113	643.99 116	1543.40 126
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
MVS_111021_LR		1055.24 117	916.36 112	1217.27 118	1129.93 121	1268.26 124	1313.88 125	2635.76 120	923.19 116	396.92 117	704.88 117	327.66 117	1136.32 120	965.38 112	946.95 110	690.83 119	1278.20 118

ACMP	1170.86 6	1091.37 118	943.23 113	1264.21 119	1112.10 120	1138.94 122	1276.90 124	2675.36 121	989.62 118	426.15 121	742.77 118	349.09 121	1454.51 126	1047.36 119	969.90 112	640.22 115	1364.94 121
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
RPMNet		858.01 108	961.99 114	736.69 99	550.05 97	1120.24 121	1212.05 123	463.05 84	485.90 99	550.05 125	580.05 112	890.05 142	559.05 94	1485.90 124	1185.90 122	1085.90 128	985.90 111

ambc			999.00 115		999.00 113	999.00 115	999.00 113		999.00 119	999.00 140	999.00 126	999.00 147	999.00 115	999.00 114	999.00 114	999.00 123	999.00 112

EPMVS		999.00 112	999.00 115	999.00 111	999.00 113	999.00 115	999.00 113	999.00 96	999.00 119	999.00 140	999.00 126	999.00 147	999.00 115	999.00 114	999.00 114	999.00 123	999.00 112

sosnet		1000.00 113	1000.00 117	1000.00 112	1000.00 115	1000.00 117	1000.00 115	1000.00 97	1000.00 121	1000.00 142	1000.00 128	1000.00 149	1000.00 117	1000.00 116	1000.00 116	1000.00 125	1000.00 114

USDC		1000.00 113	1000.00 117	1000.00 112	1000.00 115	1000.00 117	1000.00 115	1000.00 97	1000.00 121	1000.00 142	1000.00 128	1000.00 149	1000.00 117	1000.00 116	1000.00 116	1000.00 125	1000.00 114

TinyColmap		1000.00 113	1000.00 117	1000.00 112	1000.00 115	1000.00 117	1000.00 115	1000.00 97	1000.00 121	1000.00 142	1000.00 128	1000.00 149	1000.00 117	1000.00 116	1000.00 116	1000.00 125	1000.00 114

FPMVS		1356.65 122	1072.60 120	1688.04 124	1840.79 127	1397.01 126	1793.24 130	4397.86 130	804.66 112	408.78 118	538.65 110	407.36 122	894.84 114	1587.73 125	1286.38 124	792.73 121	1486.39 123

ACMMPR		1265.65 120	1083.59 121	1478.06 123	1441.06 125	1438.61 128	1540.68 128	3284.05 125	1219.68 126	458.81 122	803.22 121	346.91 120	1421.66 125	1126.11 122	1150.51 121	722.08 120	1500.09 124

TSAR-MVS + GP.		1239.27 119	1094.74 122	1407.89 121	1220.99 122	1845.47 130	1680.98 129	3191.81 123	1098.41 124	362.98 111	679.12 116	339.31 118	1323.06 123	1173.24 123	1093.83 120	667.49 117	1433.78 122

DeepC-MVS_fast	2081.98 8	1311.87 121	1172.50 123	1474.47 122	1411.78 124	1397.23 127	1519.03 127	3401.40 126	1201.29 125	417.90 119	801.95 120	976.25 146	1409.37 124	1114.52 121	1201.12 123	687.33 118	1515.14 125
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
OpenMVS	2049.89 7	1895.92 123	1721.29 124	2099.67 125	2064.00 128	2419.00 133	2138.00 131	4572.00 131	1541.00 132	548.00 124	937.00 123	580.00 128	1983.00 128	1971.00 131	1993.00 129	1293.00 135	2608.00 130

PCF-MVS	3738.24 13	2129.60 126	1746.89 125	2576.10 133	2258.22 133	2263.67 131	2650.06 138	6361.78 144	1676.15 134	695.66 129	1209.77 132	737.88 133	2237.28 129	2083.02 133	1835.31 125	1253.58 134	2422.45 128
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
MVS-HIRNet		1975.98 124	1797.02 126	2184.76 126	2111.07 129	2443.03 134	2503.43 133	4063.71 127	1684.46 135	711.34 130	1456.05 138	848.70 140	2396.26 138	1900.93 126	1915.01 127	1322.75 136	2330.99 127

SD-MVS		2324.36 132	1910.97 127	2806.65 141	2945.31 141	3305.03 146	3267.51 143	5962.25 143	1896.37 137	848.15 137	1224.25 133	661.55 131	2707.30 142	1913.40 127	1871.41 126	1109.38 129	2504.79 129

Vis-MVSNet		2390.77 134	1976.57 128	2874.00 142	2644.00 139	3248.00 144	3040.00 141	7371.00 148	1627.00 133	421.00 120	1200.00 131	622.00 129	2251.00 130	2326.00 139	2052.00 133	1517.00 143	2761.00 134
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
CMPMVS	2507.20 10	2083.60 125	1983.13 129	2200.81 127	2582.70 137	3097.30 141	2332.10 132	4364.50 129	1390.00 127	653.68 128	997.75 125	742.65 135	1880.20 127	2298.80 138	2413.60 141	1391.70 138	2941.80 135
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
CHOSEN 280x420		2225.10 127	1992.66 130	2496.28 128	2192.10 130	2641.81 135	2621.41 135	5345.34 135	2116.46 140	1002.26 145	1683.84 142	837.43 136	2338.65 131	1920.94 128	2020.28 130	1477.92 140	2727.86 131

CHOSEN 1792x2688		2225.10 127	1992.66 130	2496.28 128	2192.10 130	2641.81 135	2621.41 135	5345.34 135	2116.46 140	1002.26 145	1683.84 142	837.43 136	2338.65 131	1920.94 128	2020.28 130	1477.92 140	2727.86 131

HyFIR lowres test		2225.10 127	1992.66 130	2496.28 128	2192.10 130	2641.81 135	2621.41 135	5345.34 135	2116.46 140	1002.26 145	1683.84 142	837.43 136	2338.65 131	1920.94 128	2020.28 130	1477.92 140	2727.86 131

3Dnovator	2220.89 9	2303.77 131	2037.00 133	2615.00 134	2617.00 138	2967.00 140	2616.00 134	5882.00 142	1928.00 138	589.00 126	907.00 122	528.00 127	2443.00 140	2370.00 140	2392.00 140	1543.00 144	3167.00 137

AdaColmap		2288.90 130	2080.73 134	2531.77 131	2485.98 136	2757.87 138	2974.47 140	4914.62 132	2255.54 143	804.63 136	1611.14 141	842.30 139	2657.83 141	2056.92 132	1960.62 128	1353.09 137	3080.73 136

DeepPCF-MVS	3033.31 11	2362.79 133	2183.15 135	2572.38 132	2349.28 134	2383.16 132	2740.92 139	5212.97 134	2043.02 139	751.44 131	1466.47 139	1327.42 157	2904.33 143	2573.45 144	2227.77 134	1475.33 139	3260.73 139

SteuartSystems-ACMMP		2615.00 135	2242.57 136	3049.50 143	2828.00 140	2801.00 139	3323.00 145	6648.00 146	2491.00 144	1023.00 148	1605.00 140	697.00 132	2926.00 145	2502.00 141	2279.00 135	1549.00 145	3323.00 141
Skip Steuart: Steuart Systems R&D Blog.
TAPA-MVS	5463.68 16	2764.21 142	2434.28 137	3149.14 144	3645.15 151	3257.60 145	3452.71 147	6526.32 145	2591.85 147	651.36 127	1964.77 151	947.44 145	2924.41 144	2523.36 142	2452.68 142	1694.86 148	3302.28 140
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
3Dnovator+	3173.67 12	2938.77 143	2519.43 138	3428.00 145	3256.00 147	3708.00 149	3443.00 146	7516.00 149	2525.00 145	1121.00 152	972.00 124	925.00 144	3192.00 147	2899.00 147	2897.00 149	2040.00 152	3710.00 148

tpmrst		2688.71 140	2604.46 139	2787.00 140	2472.96 135	3190.36 142	3313.69 144	5003.06 133	1837.26 136	1097.38 151	1721.89 146	1012.20 152	2415.09 139	2970.27 150	2736.80 147	2419.79 155	4762.44 152

tpm cat1		2652.13 136	2606.66 140	2705.18 136	3151.86 143	6902.39 157	3612.17 148	5463.78 138	1457.76 128	391.31 113	1358.61 134	446.44 123	2360.09 134	2296.48 134	2290.90 136	1251.84 130	3494.04 142

tpmp4_e23		2652.13 136	2606.66 140	2705.18 136	3151.86 143	6902.39 157	3612.17 148	5463.78 138	1457.76 128	391.31 113	1358.61 134	446.44 123	2360.09 134	2296.48 134	2290.90 136	1251.84 130	3494.04 142

CostFormer		2652.13 136	2606.66 140	2705.18 136	3151.86 143	6902.39 157	3612.17 148	5463.78 138	1457.76 128	391.31 113	1358.61 134	446.44 123	2360.09 134	2296.48 134	2290.90 136	1251.84 130	3494.04 142

tpm		2652.13 136	2606.66 140	2705.18 136	3151.86 143	6902.39 157	3612.17 148	5463.78 138	1457.76 128	391.31 113	1358.61 134	446.44 123	2360.09 134	2296.48 134	2290.90 136	1251.84 130	3494.04 142

OPM-MVS		3051.54 144	2661.57 144	3506.50 146	3532.00 150	3332.00 147	3744.00 152	7839.00 152	2772.00 150	985.00 139	1919.00 150	738.00 134	3319.00 148	2901.00 148	2715.00 146	1620.00 147	4254.00 151

TSAR-MVS + ACMM		3184.92 145	2679.45 145	3774.64 151	3302.51 148	4168.07 151	4256.74 155	8947.31 154	2634.53 148	1026.25 149	1723.72 147	1043.87 153	3387.29 149	2794.29 145	2687.41 145	1727.73 149	3704.25 147

COLMAP_ROB	3798.28 14	2690.62 141	2704.29 146	2674.67 135	3138.00 142	3522.00 148	3826.00 153	3219.00 124	2702.00 149	1138.00 154	2260.00 153	1212.00 156	2968.00 146	2936.00 149	2571.00 144	1759.00 150	3727.00 149
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
MVS_111021_HR		3192.50 146	2773.91 147	3680.86 148	3515.58 149	3815.81 150	4020.82 154	7766.11 150	2775.23 151	1300.96 158	2221.19 152	1117.25 155	3420.01 150	2873.98 146	2835.60 148	2061.69 153	3778.31 150

HSP-MVS		3241.28 147	2825.26 148	3726.65 150	3945.31 153	4305.03 152	4267.51 157	6962.25 147	2896.37 152	1068.15 150	1824.25 149	1061.55 154	4307.30 153	3013.40 151	3171.41 150	1809.38 151	3504.79 146

PLC	4785.50 15	3275.54 148	3030.86 149	3561.00 147	4093.00 154	4596.00 154	5174.00 160	4267.00 128	3570.00 154	1495.00 159	2940.00 156	1594.00 159	3947.00 152	3817.00 153	3343.00 152	2390.00 154	1356.00 120
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
MAR-MVS		3961.62 149	3726.55 150	4235.86 152	4107.62 155	6522.83 156	4862.93 159	7956.64 153	3380.98 153	1665.13 160	3231.54 157	1650.34 160	4357.29 154	3198.61 152	3209.42 151	2465.52 156	4892.15 153
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
OMC-MVS		4439.92 151	3906.78 151	5061.92 154	4748.70 157	5679.38 155	5855.03 161	9923.00 155	4023.36 157	1740.95 161	1693.78 145	1693.78 161	4658.45 155	4254.77 154	4135.74 154	3445.36 158	5866.63 155

TSAR-MVS + MP.		4216.58 150	4674.68 152	3682.13 149	3752.63 152	4315.48 153	4264.77 156	7782.51 151	2583.81 146	1125.68 153	16722.30 163	882.60 141	3589.10 151	2523.80 143	2486.45 143	1578.08 146	3208.34 138

DeepC-MVS	5581.15 17	4824.92 152	5020.53 153	4596.70 153	4714.52 156	3205.14 143	3108.50 142	10234.20 157	3823.34 156	1885.23 162	9002.42 160	2045.34 163	4715.23 156	7652.65 157	3993.41 153	2922.51 157	5421.41 154
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		6088.23 153	5315.97 154	6989.21 155	6522.51 158	8025.15 161	7938.31 162	15276.20 158	5401.97 159	1914.31 163	3802.65 158	1979.48 162	6704.11 158	5217.07 155	5137.16 155	3579.82 159	7648.29 156

CLD-MVS		6986.85 154	6222.57 155	7878.50 156	7707.00 159	8884.00 162	9025.00 163	15607.00 159	6148.00 160	2571.00 164	4822.00 159	2082.00 164	7875.00 160	6389.00 156	6449.00 156	4486.00 160	8784.00 158
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
LS3D		7481.83 155	6596.02 156	8515.28 157	9871.71 160	9844.03 163	9225.16 164	18308.40 160	5364.90 158	1267.41 155	2381.61 154	1512.79 158	7225.72 159	8875.69 158	9516.28 157	5193.26 161	8676.83 157

ACMMP		9999.00 156	9999.00 157	9999.00 158	9999.00 162	9999.00 164	9999.00 165	9999.00 156	9999.00 161	9999.00 166	9999.00 161	9999.00 166	9999.00 161	9999.00 159	9999.00 158	9999.00 163	9999.00 159
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	13278.69 157	12303.57 158	14416.33 159	9890.00 161	17107.00 165	4634.00 158	59884.00 163	3666.00 155	966.00 138	1792.00 148	896.00 143	5680.00 157	20677.00 162	23030.00 161	5444.00 162	18957.00 160
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
CNLPA		17763.08 158	15907.71 159	19927.67 160	19334.00 164	22387.00 166	22896.00 166	38668.00 161	15772.00 162	7632.00 165	13229.00 162	7123.00 165	19334.00 162	15773.00 160	15700.00 159	11702.00 164	21370.00 161

LTVRE_ROB	38377.89 19	49656.08 160	18936.71 160	85495.33 162	306852.00 167	22526.00 167	29206.00 167	112098.00 165	30022.00 163	17348.00 168	2824.00 155	11239.00 167	29457.00 163	20569.00 161	19941.00 160	18011.00 165	25436.00 162
Andreas Kuhn, Heiko HirschmÃ¼ller, Daniel Scharstein, Helmut Mayer: A TV Prior for High-Quality Scalable Multi-View Stereo Reconstruction. International Journal of Computer Vision 2016
MSDG		31705.85 159	29167.57 161	34667.17 161	44079.00 165	28314.00 168	44778.00 168	43648.00 162	31045.00 164	14849.00 167	26179.00 164	13752.00 168	38088.00 164	30859.00 163	30835.00 162	22561.00 166	43189.00 163

PHI-MVS		99999.00 161	99999.00 162	99999.00 163	99999.00 166	99999.00 169	99999.00 169	99999.00 164	99999.00 165	99999.00 169	99999.00 165	99999.00 169	99999.00 165	99999.00 164	99999.00 163	99999.00 167	99999.00 164

Anonymous202405211			10000000.00 163		10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166		10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

Anonymous20240521		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

tttt0517		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

thisisatest0515		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

tfpn111		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

conf0.01		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

ESAPD		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

conf0.002		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

thresconf0.02		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

tfpn_n400		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

tfpnconf		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

tfpnview11		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

tfpn1000		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

tfpn_ndepth		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

conf200view11		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

thres100view900		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

tfpnnormal		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

tfpn200view9		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

view600		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

view800		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

conf0.05thres1000		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

tfpn		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

v1.0		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

pmmvs6		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

pmmvs5		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

Anonymous20231211		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

pmmvs-eth3d		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

Anonymous20231206		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

canonicalmvs		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

anonymousdsp		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

FC-MVSNet-train		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

UA-Net		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

FC-MVSNet-test		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

sosnet-low-res		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

DI_MVS_plusplus_trai		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

HPM-MVS++		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

pm-mvs1		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

APDe-MVS		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

pmmvs4		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

test-LLR		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

TESTMET0.1,1		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

test-mter		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

testgi		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

test20.03		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

thres600view7		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

1111		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

.test1245		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

MP-MVS		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
testmvs		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

thres400		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

test123		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

thres200		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

test0.0.03 1		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

test12356		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

testus		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

pmmvs3		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

testmv		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

EMVS		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

E-PMN		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

test2356		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

test1235678		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

PGM-MVS		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

MCST-MVS		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

PMMVS2		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

PM-MVS		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

DWT-MVSNet_training		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

testpf		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

LGP-MVS_train		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

EPNet_dtu		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
EPNet		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CNVR-MVS		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

NCCC		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

CP-MVS		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

no-one		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

CPTT-MVS		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

HQP-MVS		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

IS_MVSNet		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

Vis-MVSNet (Re-imp)		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

PatchMatch-RL		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

TDRefinement		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

EPP-MVSNet		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

PMMVS		10000000.00 162	10000000.00 163	10000000.00 164	10000000.00 168	10000000.00 170	10000000.00 170	10000000.00 166	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 170	10000000.00 166	10000000.00 165	10000000.00 164	10000000.00 168	10000000.00 165

APD-MVS		1000000000.00 243	1000000000.00 245	1000000000.00 245	1000000000.00 251	1000000000.00 252	1000000000.00 253	1000000000.00 248	1000000000.00 249	1000000000.00 252	1000000000.00 248	1000000000.00 253	1000000000.00 248	1000000000.00 247	1000000000.00 246	1000000000.00 250	1000000000.00 247
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
our_test_3					9999.00 162	99.00 70	99.00 69

MTAPA										41.98 70		28.43 64

MTMP										10000000.00 170		31.71 67

Patchmatch-RL test							10000000.00 170

tmp_tt				299.50 83	365.00 85	54.00 67	649.00 99	241.00 78	159.00 83	204.00 96	479.00 103	308.00 111	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					10000000.00 168							10000000.00 170

NP-MVS									10000000.00 166

Patchmtry						1825.90 129	885.90 111	1405.90 106		1285.90 156

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