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.

ETV-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

EIA-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

CS-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

SMA-MVS		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

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

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

train_agg		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

HFP-MVS		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

abl_6				0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1			0.00 1	0.00 1

QAPM		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

v144192		0.40 10	0.40 10	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 10	0.40 10	0.40 11	0.40 11

v1921920		0.40 10	0.40 10	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 10	0.40 10	0.40 11	0.40 11

v1192		0.40 10	0.40 10	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 10	0.40 10	0.40 11	0.40 11

v1144		0.40 10	0.40 10	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 10	0.40 10	0.40 11	0.40 11

v148		0.40 10	0.40 10	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 10	0.40 10	0.40 11	0.40 11

v7n		0.40 10	0.40 10	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 10	0.40 10	0.40 11	0.40 11

v1240		0.40 10	0.40 10	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 10	0.40 10	0.40 11	0.40 11

v8		0.40 10	0.40 10	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 10	0.40 10	0.40 11	0.40 11

v10		0.40 10	0.40 10	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 10	0.40 10	0.40 11	0.40 11

v2v482		0.40 10	0.40 10	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 10	0.40 10	0.40 11	0.40 11

V42		0.40 10	0.40 10	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 10	0.40 10	0.40 11	0.40 11

GA-MVS		0.40 10	0.40 10	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 11	0.40 10	0.40 10	0.40 11	0.40 11

Fast-Effi-MVS+		0.41 22	0.41 22	0.41 23	0.41 23	0.41 23	0.41 23	0.41 23	0.41 23	0.41 23	0.41 23	0.41 23	0.41 23	0.41 22	0.41 22	0.41 23	0.41 23

Effi-MVS+		0.53 23	0.53 23	0.53 24	0.53 24	0.53 24	0.53 24	0.53 24	0.53 24	0.53 24	0.53 24	0.53 24	0.53 24	0.53 23	0.53 23	0.53 24	0.53 24

CDS-MVSNet		0.88 24	0.88 24	0.88 25	0.88 25	0.88 25	0.88 25	0.88 25	0.88 25	0.88 25	0.88 25	0.88 25	0.88 25	0.88 24	0.88 24	0.88 25	0.88 25
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
TAMVS		0.88 24	0.88 24	0.88 25	0.88 25	0.88 25	0.88 25	0.88 25	0.88 25	0.88 25	0.88 25	0.88 25	0.88 25	0.88 24	0.88 24	0.88 25	0.88 25

MDA-MVSNet-bldmvs		1.20 26	1.20 26	1.20 27	1.20 27	1.20 28	1.20 28	1.20 28	1.20 28	1.20 28	1.20 28	1.20 28	1.20 28	1.20 27	1.20 26	1.20 28	1.20 28

CVMVSNet		1.42 27	1.42 27	1.42 28	1.42 28	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 28	1.42 27	1.42 29	1.42 29

EU-MVSNet		1.42 27	1.42 27	1.42 28	1.42 28	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 28	1.42 27	1.42 29	1.42 29

PS-CasMVS		1.42 27	1.42 27	1.42 28	1.42 28	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 28	1.42 27	1.42 29	1.42 29

UniMVSNet_NR-MVSNet		1.42 27	1.42 27	1.42 28	1.42 28	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 28	1.42 27	1.42 29	1.42 29

PEN-MVS		1.42 27	1.42 27	1.42 28	1.42 28	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 28	1.42 27	1.42 29	1.42 29

TransMVSNet (Re)		1.42 27	1.42 27	1.42 28	1.42 28	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 28	1.42 27	1.42 29	1.42 29

DTE-MVSNet		1.42 27	1.42 27	1.42 28	1.42 28	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 28	1.42 27	1.42 29	1.42 29

DU-MVS		1.42 27	1.42 27	1.42 28	1.42 28	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 28	1.42 27	1.42 29	1.42 29

UniMVSNet (Re)		1.42 27	1.42 27	1.42 28	1.42 28	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 28	1.42 27	1.42 29	1.42 29

CP-MVSNet		1.42 27	1.42 27	1.42 28	1.42 28	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 28	1.42 27	1.42 29	1.42 29

WR-MVS_H		1.42 27	1.42 27	1.42 28	1.42 28	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 28	1.42 27	1.42 29	1.42 29

WR-MVS		1.42 27	1.42 27	1.42 28	1.42 28	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 28	1.42 27	1.42 29	1.42 29

NR-MVSNet		1.42 27	1.42 27	1.42 28	1.42 28	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 28	1.42 27	1.42 29	1.42 29

Baseline_NR-MVSNet		1.42 27	1.42 27	1.42 28	1.42 28	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 28	1.42 27	1.42 29	1.42 29

TranMVSNet+NR-MVSNet		1.42 27	1.42 27	1.42 28	1.42 28	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 29	1.42 28	1.42 27	1.42 29	1.42 29

CDPH-MVS		6.66 42	6.66 42	6.66 43	6.66 43	6.66 44	6.66 44	6.66 44	6.66 44	6.66 44	6.66 44	6.66 44	6.66 44	6.66 43	6.66 42	6.66 44	6.66 44

MDTV_nov1_ep13_2view		9.99 43	9.99 43	9.99 44	9.99 44	9.99 45	9.99 45	9.99 45	9.99 45	9.99 45	9.99 45	9.99 45	9.99 45	9.99 44	9.99 43	9.99 45	9.99 45

MDTV_nov1_ep13		9.99 43	9.99 43	9.99 44	9.99 44	9.99 45	9.99 45	9.99 45	9.99 45	9.99 45	9.99 45	9.99 45	9.99 45	9.99 44	9.99 43	9.99 45	9.99 45

GBi-Net		39.84 45	35.75 45	44.63 46	43.04 46	49.88 47	51.06 47	86.51 48	35.34 47	17.20 47	29.83 47	15.85 47	43.43 49	35.35 46	35.70 45	26.51 49	48.28 49

XVS					52.20 47	52.20 48	52.20 48			52.20 57		52.20 66				52.20 50

X-MVStestdata					52.20 47	52.20 48	52.20 48			52.20 57		52.20 66				52.20 50

X-MVS		52.20 46	52.20 46	52.20 47	52.20 47	52.20 48	52.20 48	52.20 47	52.20 48	52.20 57	52.20 48	52.20 66	52.20 50	52.20 47	52.20 46	52.20 50	52.20 50

new_pmnet		75.00 47	74.67 47	75.39 48	85.42 50	96.03 52	98.77 51	173.23 49	69.57 49	36.19 48	56.93 49	117.43 70	32.98 47	85.38 55	68.41 47	25.74 47	28.95 47

N_pmnet		75.00 47	74.67 47	75.39 48	85.42 50	96.03 52	98.77 51	173.23 49	69.57 49	36.19 48	56.93 49	117.43 70	32.98 47	85.38 55	68.41 47	25.74 47	28.95 47

CANet		100.44 49	93.07 49	109.04 50	111.90 52	131.06 57	119.40 54	222.42 58	80.48 51	36.93 50	70.80 51	40.92 52	89.90 51	100.59 57	101.42 50	73.68 55	126.25 51

CANet_DTU		100.44 49	93.07 49	109.04 50	111.90 52	131.06 57	119.40 54	222.42 58	80.48 51	36.93 50	70.80 51	40.92 52	89.90 51	100.59 57	101.42 50	73.68 55	126.25 51

MVS_0304		100.44 49	93.07 49	109.04 50	111.90 52	131.06 57	119.40 54	222.42 58	80.48 51	36.93 50	70.80 51	40.92 52	89.90 51	100.59 57	101.42 50	73.68 55	126.25 51

UGNet		100.44 49	93.07 49	109.04 50	111.90 52	131.06 57	119.40 54	222.42 58	80.48 51	36.93 50	70.80 51	40.92 52	89.90 51	100.59 57	101.42 50	73.68 55	126.25 51
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_NAP		119.64 60	106.58 53	134.88 61	123.82 56	127.44 55	145.38 58	298.43 66	116.16 65	43.72 55	77.82 55	29.30 49	131.24 62	117.82 64	106.21 54	66.69 53	171.29 65

zzz-MVS		119.64 60	106.58 53	134.88 61	123.82 56	127.44 55	145.38 58	298.43 66	116.16 65	43.72 55	77.82 55	29.30 49	131.24 62	117.82 64	106.21 54	66.69 53	171.29 65

FMVSNet5		116.86 53	110.47 55	124.32 54	131.47 58	157.41 61	150.67 60	199.64 51	115.30 58	56.61 63	97.70 60	51.77 56	117.26 55	77.26 48	113.14 56	90.25 62	160.68 58

test1		116.86 53	110.47 55	124.32 54	131.47 58	157.41 61	150.67 60	199.64 51	115.30 58	56.61 63	97.70 60	51.77 56	117.26 55	77.26 48	113.14 56	90.25 62	160.68 58

FMVSNet3		116.86 53	110.47 55	124.32 54	131.47 58	157.41 61	150.67 60	199.64 51	115.30 58	56.61 63	97.70 60	51.77 56	117.26 55	77.26 48	113.14 56	90.25 62	160.68 58

FMVSNet2		116.86 53	110.47 55	124.32 54	131.47 58	157.41 61	150.67 60	199.64 51	115.30 58	56.61 63	97.70 60	51.77 56	117.26 55	77.26 48	113.14 56	90.25 62	160.68 58

FMVSNet1		116.86 53	110.47 55	124.32 54	131.47 58	157.41 61	150.67 60	199.64 51	115.30 58	56.61 63	97.70 60	51.77 56	117.26 55	77.26 48	113.14 56	90.25 62	160.68 58

MIMVSNet1		116.86 53	110.47 55	124.32 54	131.47 58	157.41 61	150.67 60	199.64 51	115.30 58	56.61 63	97.70 60	51.77 56	117.26 55	77.26 48	113.14 56	90.25 62	160.68 58

MIMVSNet		116.86 53	110.47 55	124.32 54	131.47 58	157.41 61	150.67 60	199.64 51	115.30 58	56.61 63	97.70 60	51.77 56	117.26 55	77.26 48	113.14 56	90.25 62	160.68 58

PVSNet_Blended_VisFu		129.22 62	115.76 62	144.92 63	140.60 65	162.80 68	166.50 67	281.20 63	114.70 55	55.50 60	96.20 57	51.80 63	140.60 64	114.70 61	114.70 63	85.10 59	155.40 55

PVSNet_BlendedMVS		129.22 62	115.76 62	144.92 63	140.60 65	162.80 68	166.50 67	281.20 63	114.70 55	55.50 60	96.20 57	51.80 63	140.60 64	114.70 61	114.70 63	85.10 59	155.40 55

PVSNet_Blended		129.22 62	115.76 62	144.92 63	140.60 65	162.80 68	166.50 67	281.20 63	114.70 55	55.50 60	96.20 57	51.80 63	140.60 64	114.70 61	114.70 63	85.10 59	155.40 55

SixPastTwentyTwo		210.90 65	189.75 65	235.58 66	225.41 68	284.88 71	267.17 70	485.88 69	164.28 68	76.51 70	137.62 67	76.69 69	214.49 67	206.28 66	208.00 66	144.02 70	250.52 67

tmp_tt				299.50 67	365.00 69	54.00 51	649.00 82	241.00 62	159.00 67	204.00 79	479.00 87	308.00 95	243.00 68	246.00 67	82.00 49	95.00 69

gm-plane-assit		551.84 73	503.49 74	608.24 76	411.90 70	370.41 72	267.30 71	710.53 72	454.42 78	785.72 115	491.23 89	326.12 97	881.92 93	538.27 79	650.05 86	592.08 95	693.94 77

RPSCF		376.53 66	341.80 66	417.05 68	418.60 71	457.01 76	467.46 75	825.25 76	336.12 70	159.32 74	260.40 70	151.13 74	386.94 69	364.25 68	352.10 67	244.72 71	471.62 69

EG-PatchMatch MVS		402.98 67	364.36 67	448.05 69	435.50 72	473.00 77	489.60 76	910.20 77	338.60 71	127.30 71	205.10 68	123.50 72	434.60 70	450.70 72	447.70 70	291.10 73	511.90 70

MS-PatchMatch		438.85 68	388.71 68	497.33 70	479.00 73	527.00 78	558.00 79	988.00 78	379.00 73	174.00 76	278.00 72	162.00 75	494.00 74	418.00 69	412.00 68	291.00 72	545.00 73

GG-mvs-BLEND		557.53 76	503.49 74	620.58 77	485.90 74	370.41 72	267.30 71	710.53 72	454.42 78	785.72 115	491.23 89	326.12 97	881.92 93	538.27 79	650.05 86	592.08 95	693.94 77

gg-mvs-nofinetune		557.53 76	503.49 74	620.58 77	485.90 74	370.41 72	267.30 71	710.53 72	454.42 78	785.72 115	491.23 89	326.12 97	881.92 93	538.27 79	650.05 86	592.08 95	693.94 77

CR-MVSNet		557.53 76	503.49 74	620.58 77	485.90 74	370.41 72	267.30 71	710.53 72	454.42 78	785.72 115	491.23 89	326.12 97	881.92 93	538.27 79	650.05 86	592.08 95	693.94 77

DELS-MVS		458.84 71	423.31 71	500.30 71	511.99 77	616.59 80	578.86 80	991.10 79	355.79 72	158.99 73	319.09 74	190.62 78	453.64 73	437.73 71	439.52 69	307.20 74	603.81 74
Christian Sormann, Emanuele Santellani, Mattia Rossi, Andreas Kuhn, Friedrich Fraundorfer: DELS-MVS: Deep Epipolar Line Search for Multi-View Stereo. Winter Conference on Applications of Computer Vision (WACV), 2023
PatchmatchNet		452.63 70	410.20 70	502.13 72	520.70 78	614.40 79	546.00 77	1018.80 85	379.00 73	167.50 75	277.10 71	169.40 76	437.10 71	437.10 70	457.50 71	322.70 75	536.90 72
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
ADS-MVSNet		452.36 69	406.02 69	506.42 73	534.76 79	628.22 81	552.79 78	1009.99 84	333.98 69	149.26 72	246.67 69	149.01 73	447.03 72	465.35 73	501.18 73	344.69 76	517.75 71

RPMNet		858.01 92	961.99 98	736.69 82	550.05 80	1120.24 105	1212.05 107	463.05 68	485.90 82	550.05 108	580.05 96	890.05 128	559.05 77	1485.90 108	1185.90 106	1085.90 112	985.90 95

CSCG		727.26 89	663.25 90	801.94 90	590.65 81	811.25 87	854.12 93	1805.32 100	816.43 98	388.25 96	612.42 97	345.37 103	621.61 80	507.46 74	471.55 72	551.65 93	1078.31 101

IB-MVS	750.90 3	552.99 74	511.38 78	601.53 74	606.02 82	735.75 86	688.75 84	1183.86 86	436.09 77	210.63 81	397.40 77	233.85 82	551.05 76	521.77 76	533.78 76	368.88 77	721.05 82
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
SR-MVS					610.10 83			610.10 70				610.10 112

IterMVS		554.60 75	488.63 73	631.57 80	636.90 84	700.80 82	674.70 83	1271.10 89	430.50 76	207.10 80	370.50 76	202.70 80	611.80 79	534.20 78	545.30 77	387.80 79	636.40 76
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
Gipuma		587.77 79	529.57 79	655.67 81	637.00 85	733.00 85	749.00 85	1245.00 88	525.00 84	269.00 90	445.00 85	253.00 84	637.00 81	525.00 77	525.00 75	397.00 80	701.00 81
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
ACMH+	702.88 1	670.82 86	589.81 86	765.33 89	662.52 86	701.42 83	795.24 86	1698.33 98	598.81 93	226.55 82	403.02 78	187.13 77	786.82 90	724.80 92	646.56 85	422.52 82	866.95 90

dps		534.60 72	472.40 72	607.16 75	690.38 87	718.85 84	636.03 81	1231.66 87	422.74 75	198.65 78	325.68 75	194.97 79	512.90 75	509.81 75	513.65 74	373.33 78	621.11 75

MVS_Test		654.54 80	583.51 80	737.40 83	721.80 88	822.10 88	808.60 87	1494.00 91	542.20 86	259.90 84	441.60 79	257.70 86	689.10 83	620.80 83	617.70 79	451.00 84	782.50 83

casdiffmvs		654.54 80	583.51 80	737.40 83	721.80 88	822.10 88	808.60 87	1494.00 91	542.20 86	259.90 84	441.60 79	257.70 86	689.10 83	620.80 83	617.70 79	451.00 84	782.50 83

diffmvs		654.54 80	583.51 80	737.40 83	721.80 88	822.10 88	808.60 87	1494.00 91	542.20 86	259.90 84	441.60 79	257.70 86	689.10 83	620.80 83	617.70 79	451.00 84	782.50 83

baseline2		654.54 80	583.51 80	737.40 83	721.80 88	822.10 88	808.60 87	1494.00 91	542.20 86	259.90 84	441.60 79	257.70 86	689.10 83	620.80 83	617.70 79	451.00 84	782.50 83

baseline1		654.54 80	583.51 80	737.40 83	721.80 88	822.10 88	808.60 87	1494.00 91	542.20 86	259.90 84	441.60 79	257.70 86	689.10 83	620.80 83	617.70 79	451.00 84	782.50 83

baseline		654.54 80	583.51 80	737.40 83	721.80 88	822.10 88	808.60 87	1494.00 91	542.20 86	259.90 84	441.60 79	257.70 86	689.10 83	620.80 83	617.70 79	451.00 84	782.50 83

new-patchmatchnet		712.65 87	632.59 87	806.05 92	787.79 94	936.25 97	882.47 94	1795.72 99	528.60 85	244.29 83	471.90 86	257.36 85	681.47 82	705.16 91	659.05 90	444.55 83	869.82 91

IterMVS-LS		714.97 88	638.00 89	804.77 91	793.60 95	914.20 95	886.50 96	1612.70 97	588.30 92	285.30 91	491.20 88	278.40 93	759.20 89	677.40 90	681.30 91	491.30 90	835.20 89
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
ACMH	935.68 4	948.23 94	857.00 94	1054.67 99	946.00 96	970.00 98	1125.00 104	2467.00 102	823.00 99	330.00 94	622.00 98	211.00 81	891.00 97	970.00 97	1061.00 103	569.00 94	1342.00 103
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
MVSTER		834.63 90	737.03 92	948.49 93	988.86 97	1140.51 107	1129.34 105	1832.80 101	682.42 94	319.01 92	550.98 95	311.35 96	872.51 92	763.95 93	757.83 92	548.41 92	952.20 93

ambc			999.00 99		999.00 98	999.00 99	999.00 97		999.00 103	999.00 125	999.00 110	999.00 133	999.00 99	999.00 98	999.00 98	999.00 107	999.00 96

EPMVS		999.00 96	999.00 99	999.00 95	999.00 98	999.00 99	999.00 97	999.00 80	999.00 103	999.00 125	999.00 110	999.00 133	999.00 99	999.00 98	999.00 98	999.00 107	999.00 96

sosnet		1000.00 97	1000.00 101	1000.00 96	1000.00 100	1000.00 101	1000.00 99	1000.00 81	1000.00 105	1000.00 127	1000.00 112	1000.00 135	1000.00 101	1000.00 100	1000.00 100	1000.00 109	1000.00 98

USDC		1000.00 97	1000.00 101	1000.00 96	1000.00 100	1000.00 101	1000.00 99	1000.00 81	1000.00 105	1000.00 127	1000.00 112	1000.00 135	1000.00 101	1000.00 100	1000.00 100	1000.00 109	1000.00 98

TinyColmap		1000.00 97	1000.00 101	1000.00 96	1000.00 100	1000.00 101	1000.00 99	1000.00 81	1000.00 105	1000.00 127	1000.00 112	1000.00 135	1000.00 101	1000.00 100	1000.00 100	1000.00 109	1000.00 98

ACMM	1129.18 5	1047.56 100	912.90 95	1204.67 101	1040.21 103	1016.71 104	1105.32 102	2918.67 107	813.91 97	327.22 93	665.34 99	267.72 92	1192.58 105	1091.35 104	991.88 97	643.99 100	1543.40 110
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
PatchT		878.42 93	785.05 93	987.36 94	1050.05 104	922.05 96	1111.05 103	677.05 71	950.05 101	1285.90 141	750.05 103	640.05 114	850.05 91	950.05 95	950.05 95	950.05 106	333.05 68

ACMP	1170.86 6	1091.37 102	943.23 97	1264.21 103	1112.10 105	1138.94 106	1276.90 108	2675.36 106	989.62 102	426.15 104	742.77 102	349.09 105	1454.51 110	1047.36 103	969.90 96	640.22 99	1364.94 105
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
MVS_111021_LR		1055.24 101	916.36 96	1217.27 102	1129.93 106	1268.26 108	1313.88 109	2635.76 105	923.19 100	396.92 100	704.88 101	327.66 101	1136.32 104	965.38 96	946.95 94	690.83 103	1278.20 102

TSAR-MVS + GP.		1239.27 103	1094.74 106	1407.89 105	1220.99 107	1845.47 114	1680.98 113	3191.81 108	1098.41 108	362.98 95	679.12 100	339.31 102	1323.06 107	1173.24 107	1093.83 104	667.49 101	1433.78 106

PMVS	743.55 2	836.66 91	637.90 88	1068.55 100	1306.50 108	875.12 94	1166.70 106	2629.00 104	512.24 83	196.22 77	282.69 73	237.15 83	597.87 78	842.47 94	765.54 93	514.99 91	950.09 92
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
DeepC-MVS_fast	2081.98 8	1311.87 105	1172.50 107	1474.47 106	1411.78 109	1397.23 111	1519.03 111	3401.40 111	1201.29 109	417.90 102	801.95 104	976.25 132	1409.37 108	1114.52 105	1201.12 107	687.33 102	1515.14 109
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
ACMMPR		1265.65 104	1083.59 105	1478.06 107	1441.06 110	1438.61 112	1540.68 112	3284.05 110	1219.68 110	458.81 105	803.22 105	346.91 104	1421.66 109	1126.11 106	1150.51 105	722.08 104	1500.09 108

MSLP-MVS++		993.91 95	732.21 91	1299.24 104	1631.22 111	1345.26 109	1480.05 110	2524.20 103	735.65 95	463.57 106	499.89 93	302.78 94	1292.66 106	675.99 89	612.79 78	403.71 81	953.11 94

FPMVS		1356.65 106	1072.60 104	1688.04 108	1840.79 112	1397.01 110	1793.24 114	4397.86 115	804.66 96	408.78 101	538.65 94	407.36 106	894.84 98	1587.73 109	1286.38 108	792.73 105	1486.39 107

OpenMVS	2049.89 7	1895.92 107	1721.29 108	2099.67 109	2064.00 113	2419.00 117	2138.00 115	4572.00 116	1541.00 115	548.00 107	937.00 107	580.00 111	1983.00 112	1971.00 115	1993.00 113	1293.00 118	2608.00 114

MVS-HIRNet		1975.98 108	1797.02 110	2184.76 110	2111.07 114	2443.03 118	2503.43 117	4063.71 112	1684.46 118	711.34 113	1456.05 121	848.70 126	2396.26 121	1900.93 110	1915.01 111	1322.75 119	2330.99 111

CHOSEN 280x420		2225.10 111	1992.66 114	2496.28 112	2192.10 115	2641.81 119	2621.41 119	5345.34 120	2116.46 123	1002.26 130	1683.84 126	837.43 122	2338.65 115	1920.94 112	2020.28 114	1477.92 124	2727.86 115

CHOSEN 1792x2688		2225.10 111	1992.66 114	2496.28 112	2192.10 115	2641.81 119	2621.41 119	5345.34 120	2116.46 123	1002.26 130	1683.84 126	837.43 122	2338.65 115	1920.94 112	2020.28 114	1477.92 124	2727.86 115

HyFIR lowres test		2225.10 111	1992.66 114	2496.28 112	2192.10 115	2641.81 119	2621.41 119	5345.34 120	2116.46 123	1002.26 130	1683.84 126	837.43 122	2338.65 115	1920.94 112	2020.28 114	1477.92 124	2727.86 115

PCF-MVS	3738.24 13	2129.60 110	1746.89 109	2576.10 117	2258.22 118	2263.67 115	2650.06 122	6361.78 128	1676.15 117	695.66 112	1209.77 116	737.88 118	2237.28 113	2083.02 117	1835.31 109	1253.58 117	2422.45 112
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
DeepPCF-MVS	3033.31 11	2362.79 117	2183.15 119	2572.38 116	2349.28 119	2383.16 116	2740.92 123	5212.97 119	2043.02 122	751.44 114	1466.47 122	1327.42 143	2904.33 126	2573.45 128	2227.77 118	1475.33 123	3260.73 123

tpmrst		2688.71 123	2604.46 124	2787.00 123	2472.96 120	3190.36 126	3313.69 128	5003.06 118	1837.26 119	1097.38 136	1721.89 130	1012.20 138	2415.09 122	2970.27 135	2736.80 132	2419.79 140	4762.44 137

AdaColmap		2288.90 114	2080.73 118	2531.77 115	2485.98 121	2757.87 122	2974.47 124	4914.62 117	2255.54 126	804.63 119	1611.14 125	842.30 125	2657.83 124	2056.92 116	1960.62 112	1353.09 121	3080.73 120

CMPMVS	2507.20 10	2083.60 109	1983.13 113	2200.81 111	2582.70 122	3097.30 125	2332.10 116	4364.50 114	1390.00 111	653.68 111	997.75 109	742.65 121	1880.20 111	2298.80 121	2413.60 125	1391.70 122	2941.80 119
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
3Dnovator	2220.89 9	2303.77 115	2037.00 117	2615.00 118	2617.00 123	2967.00 124	2616.00 118	5882.00 126	1928.00 121	589.00 109	907.00 106	528.00 110	2443.00 123	2370.00 123	2392.00 124	1543.00 128	3167.00 121

Vis-MVSNet		2390.77 118	1976.57 112	2874.00 125	2644.00 124	3248.00 128	3040.00 125	7371.00 132	1627.00 116	421.00 103	1200.00 115	622.00 113	2251.00 114	2326.00 122	2052.00 117	1517.00 127	2761.00 118
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
SteuartSystems-ACMMP		2615.00 119	2242.57 120	3049.50 126	2828.00 125	2801.00 123	3323.00 129	6648.00 130	2491.00 128	1023.00 133	1605.00 124	697.00 116	2926.00 128	2502.00 125	2279.00 119	1549.00 129	3323.00 125
Skip Steuart: Steuart Systems R&D Blog.
SD-MVS		2324.36 116	1910.97 111	2806.65 124	2945.31 126	3305.03 130	3267.51 127	5962.25 127	1896.37 120	848.15 120	1224.25 117	661.55 115	2707.30 125	1913.40 111	1871.41 110	1109.38 113	2504.79 113
Zhenlong Yuan, Jiakai Cao, Zhaoxin Li, Hao Jiang and Zhaoqi Wang: SD-MVS: Segmentation-driven Deformation Multi-View Stereo with Spherical Refinement and EM optimization. AAAI2024
COLMAP_ROB	3798.28 14	2690.62 124	2704.29 131	2674.67 119	3138.00 127	3522.00 133	3826.00 137	3219.00 109	2702.00 133	1138.00 139	2260.00 138	1212.00 142	2968.00 129	2936.00 134	2571.00 128	1759.00 135	3727.00 133
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
tpm cat1		2652.13 120	2606.66 125	2705.18 120	3151.86 128	6902.39 143	3612.17 132	5463.78 123	1457.76 112	391.31 97	1358.61 118	446.44 107	2360.09 118	2296.48 118	2290.90 120	1251.84 114	3494.04 126

CostFormer		2652.13 120	2606.66 125	2705.18 120	3151.86 128	6902.39 143	3612.17 132	5463.78 123	1457.76 112	391.31 97	1358.61 118	446.44 107	2360.09 118	2296.48 118	2290.90 120	1251.84 114	3494.04 126

tpm		2652.13 120	2606.66 125	2705.18 120	3151.86 128	6902.39 143	3612.17 132	5463.78 123	1457.76 112	391.31 97	1358.61 118	446.44 107	2360.09 118	2296.48 118	2290.90 120	1251.84 114	3494.04 126

3Dnovator+	3173.67 12	2938.77 126	2519.43 122	3428.00 128	3256.00 131	3708.00 134	3443.00 130	7516.00 133	2525.00 129	1121.00 137	972.00 108	925.00 130	3192.00 130	2899.00 131	2897.00 134	2040.00 137	3710.00 132

TSAR-MVS + ACMM		3184.92 129	2679.45 130	3774.64 135	3302.51 132	4168.07 136	4256.74 139	8947.31 139	2634.53 132	1026.25 134	1723.72 131	1043.87 139	3387.29 133	2794.29 129	2687.41 129	1727.73 134	3704.25 131

MVS_111021_HR		3192.50 130	2773.91 132	3680.86 132	3515.58 133	3815.81 135	4020.82 138	7766.11 134	2775.23 136	1300.96 143	2221.19 137	1117.25 141	3420.01 134	2873.98 130	2835.60 133	2061.69 138	3778.31 134

DPM-MVS		3051.54 127	2661.57 128	3506.50 129	3532.00 134	3332.00 131	3744.00 135	7839.00 136	2772.00 134	985.00 123	1919.00 134	738.00 119	3319.00 131	2901.00 132	2715.00 130	1620.00 131	4254.00 135

OPM-MVS		3051.54 127	2661.57 128	3506.50 129	3532.00 134	3332.00 131	3744.00 135	7839.00 136	2772.00 134	985.00 123	1919.00 134	738.00 119	3319.00 131	2901.00 132	2715.00 130	1620.00 131	4254.00 135

TAPA-MVS	5463.68 16	2764.21 125	2434.28 121	3149.14 127	3645.15 136	3257.60 129	3452.71 131	6526.32 129	2591.85 131	651.36 110	1964.77 136	947.44 131	2924.41 127	2523.36 126	2452.68 126	1694.86 133	3302.28 124
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
TSAR-MVS + MP.		4216.58 135	4674.68 137	3682.13 133	3752.63 137	4315.48 138	4264.77 140	7782.51 135	2583.81 130	1125.68 138	16722.30 148	882.60 127	3589.10 136	2523.80 127	2486.45 127	1578.08 130	3208.34 122
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
MSP-MVS		3241.28 131	2825.26 133	3726.65 134	3945.31 138	4305.03 137	4267.51 141	6962.25 131	2896.37 137	1068.15 135	1824.25 133	1061.55 140	4307.30 138	3013.40 136	3171.41 135	1809.38 136	3504.79 129

DVP-MVS		3258.34 132	2529.80 123	4108.31 136	4005.62 139	4693.14 140	4737.88 143	10195.40 142	2408.38 127	941.44 121	1505.82 123	734.32 117	3438.27 135	2449.15 124	2386.04 123	1331.25 120	3531.75 130

PLC	4785.50 15	3275.54 133	3030.86 134	3561.00 131	4093.00 140	4596.00 139	5174.00 145	4267.00 113	3570.00 139	1495.00 144	2940.00 141	1594.00 145	3947.00 137	3817.00 138	3343.00 137	2390.00 139	1356.00 104
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
MAR-MVS		3961.62 134	3726.55 135	4235.86 137	4107.62 141	6522.83 142	4862.93 144	7956.64 138	3380.98 138	1665.13 145	3231.54 142	1650.34 146	4357.29 139	3198.61 137	3209.42 136	2465.52 141	4892.15 138
Zhenyu Xu, Yiguang Liu, Xuelei Shi, Ying Wang, Yunan Zheng: MARMVS: Matching Ambiguity Reduced Multiple View Stereo for Efficient Large Scale Scene Reconstruction. CVPR 2020
DeepC-MVS	5581.15 17	4824.92 137	5020.53 138	4596.70 138	4714.52 142	3205.14 127	3108.50 126	10234.20 143	3823.34 141	1885.23 147	9002.42 145	2045.34 149	4715.23 141	7652.65 142	3993.41 138	2922.51 142	5421.41 139
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
OMC-MVS		4439.92 136	3906.78 136	5061.92 139	4748.70 143	5679.38 141	5855.03 146	9923.00 140	4023.36 142	1740.95 146	1693.78 129	1693.78 147	4658.45 140	4254.77 139	4135.74 139	3445.36 143	5866.63 140

TSAR-MVS + COLMAP		6088.23 138	5315.97 139	6989.21 140	6522.51 144	8025.15 146	7938.31 147	15276.20 144	5401.97 144	1914.31 148	3802.65 143	1979.48 148	6704.11 143	5217.07 140	5137.16 140	3579.82 144	7648.29 141

CLD-MVS		6986.85 139	6222.57 140	7878.50 141	7707.00 145	8884.00 147	9025.00 148	15607.00 145	6148.00 145	2571.00 149	4822.00 144	2082.00 150	7875.00 145	6389.00 141	6449.00 141	4486.00 145	8784.00 143
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
LS3D		7481.83 140	6596.02 141	8515.28 142	9871.71 146	9844.03 148	9225.16 149	18308.40 146	5364.90 143	1267.41 140	2381.61 139	1512.79 144	7225.72 144	8875.69 143	9516.28 142	5193.26 146	8676.83 142

MVE	11086.50 18	13278.69 142	12303.57 143	14416.33 144	9890.00 147	17107.00 150	4634.00 142	59884.00 149	3666.00 140	966.00 122	1792.00 132	896.00 129	5680.00 142	20677.00 147	23030.00 146	5444.00 147	18957.00 145
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
our_test_3					9999.00 148	99.00 54	99.00 53

ACMMP		9999.00 141	9999.00 142	9999.00 143	9999.00 148	9999.00 149	9999.00 150	9999.00 141	9999.00 146	9999.00 151	9999.00 146	9999.00 152	9999.00 146	9999.00 144	9999.00 143	9999.00 148	9999.00 144
Qingshan Xu, Weihang Kong, Wenbing Tao, Marc Pollefeys: Multi-Scale Geometric Consistency Guided and Planar Prior Assisted Multi-View Stereo. IEEE Transactions on Pattern Analysis and Machine Intelligence
CNLPA		17763.08 143	15907.71 144	19927.67 145	19334.00 150	22387.00 151	22896.00 151	38668.00 147	15772.00 147	7632.00 150	13229.00 147	7123.00 151	19334.00 147	15773.00 145	15700.00 144	11702.00 149	21370.00 146

MSDG		31705.85 144	29167.57 146	34667.17 146	44079.00 151	28314.00 153	44778.00 153	43648.00 148	31045.00 149	14849.00 152	26179.00 149	13752.00 154	38088.00 149	30859.00 148	30835.00 147	22561.00 151	43189.00 148

PHI-MVS		99999.00 146	99999.00 147	99999.00 148	99999.00 152	99999.00 154	99999.00 154	99999.00 150	99999.00 150	99999.00 154	99999.00 150	99999.00 155	99999.00 150	99999.00 149	99999.00 148	99999.00 152	99999.00 149

LTVRE_ROB	38377.89 19	49656.08 145	18936.71 145	85495.33 147	306852.00 153	22526.00 152	29206.00 152	112098.00 151	30022.00 148	17348.00 153	2824.00 140	11239.00 153	29457.00 148	20569.00 146	19941.00 145	18011.00 150	25436.00 147
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
ET-MVSNet_ETH3D		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

UniMVSNet_ETH3D		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

thisisatest0530		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

Anonymous202405211			10000000.00 148		10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151		10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

DCV-MVSNet		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

tttt0517		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

thisisatest0515		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

DPE-MVS		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

thres100view900		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

tfpnnormal		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

tfpn200view9		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

IterMVS-SCA-FT		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

pmmvs6		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

pmmvs5		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

Anonymous20231211		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

pmmvs-eth3d		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

Anonymous20231206		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

SCA		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

canonicalmvs		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

anonymousdsp		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

FC-MVSNet-train		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

UA-Net		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

FC-MVSNet-test		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

sosnet-low-res		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

DI_MVS_plusplus_trai		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

HPM-MVS++		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

pm-mvs1		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

APDe-MVS		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

pmmvs4		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

test-LLR		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

TESTMET0.1,1		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

test-mter		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

testgi		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

test20.03		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

thres600view7		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

MP-MVS		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
testmvs		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

thres400		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

test123		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

thres200		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

test0.0.03 1		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

pmmvs3		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

EMVS		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

E-PMN		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

PGM-MVS		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

MCST-MVS		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

PMMVS2		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

PM-MVS		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

mPP-MVS					10000000.00 154							10000000.00 156

DWT-MVSNet_training		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

LGP-MVS_train		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

EPNet_dtu		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
EPNet		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CNVR-MVS		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

NCCC		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

CP-MVS		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

CPTT-MVS		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

HQP-MVS		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

IS_MVSNet		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

Vis-MVSNet (Re-imp)		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

PatchMatch-RL		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

TDRefinement		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

EPP-MVSNet		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

PMMVS		10000000.00 147	10000000.00 148	10000000.00 149	10000000.00 154	10000000.00 155	10000000.00 155	10000000.00 152	10000000.00 151	10000000.00 155	10000000.00 151	10000000.00 156	10000000.00 151	10000000.00 150	10000000.00 149	10000000.00 153	10000000.00 151

APD-MVS		1000000000.00 209	1000000000.00 211	1000000000.00 211	1000000000.00 218	1000000000.00 218	1000000000.00 219	1000000000.00 215	1000000000.00 215	1000000000.00 218	1000000000.00 214	1000000000.00 220	1000000000.00 214	1000000000.00 213	1000000000.00 212	1000000000.00 216	1000000000.00 214
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
test_part1																	100000.00 150

MTAPA										41.98 54		28.43 48

MTMP										10000000.00 155		31.71 51

Patchmatch-RL test							10000000.00 155

NP-MVS									10000000.00 151

Patchmtry						1825.90 113	885.90 95	1405.90 90		1285.90 141

DeepMVS_CX						1.00 27	1.00 27	1.00 27	1.00 27	1.00 27	1.00 27	1.00 27	1.00 27	1.00 26		1.00 27	1.00 27

High-resolution multi-view benchmark