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.

xxxxxxxxxxxxxcwj		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

SF-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

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

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
Yufeng Yin; Xiaoyan Liu; Zichao Zhang: SMA-MVS: Segmentation-Guided Multi-Scale Anchor Deformation Patch Multi-View Stereo. IEEE Transactions on Circuits and Systems for Video Technology
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 12	0.40 12	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 14	0.40 13	0.40 12	0.40 12	0.40 13	0.40 13

v1921920		0.40 12	0.40 12	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 14	0.40 13	0.40 12	0.40 12	0.40 13	0.40 13

v1192		0.40 12	0.40 12	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 14	0.40 13	0.40 12	0.40 12	0.40 13	0.40 13

v1144		0.40 12	0.40 12	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 14	0.40 13	0.40 12	0.40 12	0.40 13	0.40 13

v148		0.40 12	0.40 12	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 14	0.40 13	0.40 12	0.40 12	0.40 13	0.40 13

v7n		0.40 12	0.40 12	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 14	0.40 13	0.40 12	0.40 12	0.40 13	0.40 13

v1240		0.40 12	0.40 12	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 14	0.40 13	0.40 12	0.40 12	0.40 13	0.40 13

v8		0.40 12	0.40 12	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 14	0.40 13	0.40 12	0.40 12	0.40 13	0.40 13

v10		0.40 12	0.40 12	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 14	0.40 13	0.40 12	0.40 12	0.40 13	0.40 13

v2v482		0.40 12	0.40 12	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 14	0.40 13	0.40 12	0.40 12	0.40 13	0.40 13

V42		0.40 12	0.40 12	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 14	0.40 13	0.40 12	0.40 12	0.40 13	0.40 13

GA-MVS		0.40 12	0.40 12	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 13	0.40 14	0.40 13	0.40 12	0.40 12	0.40 13	0.40 13

Fast-Effi-MVS+		0.41 24	0.41 24	0.41 25	0.41 25	0.41 25	0.41 25	0.41 25	0.41 25	0.41 25	0.41 25	0.41 26	0.41 25	0.41 24	0.41 24	0.41 25	0.41 25

Effi-MVS+		0.53 25	0.53 25	0.53 26	0.53 26	0.53 26	0.53 26	0.53 26	0.53 26	0.53 26	0.53 26	0.53 27	0.53 26	0.53 25	0.53 25	0.53 26	0.53 26

CDS-MVSNet		0.88 26	0.88 26	0.88 27	0.88 27	0.88 27	0.88 27	0.88 27	0.88 27	0.88 27	0.88 27	0.88 28	0.88 27	0.88 26	0.88 26	0.88 27	0.88 27
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
TAMVS		0.88 26	0.88 26	0.88 27	0.88 27	0.88 27	0.88 27	0.88 27	0.88 27	0.88 27	0.88 27	0.88 28	0.88 27	0.88 26	0.88 26	0.88 27	0.88 27

MDA-MVSNet-bldmvs		1.20 28	1.20 28	1.20 29	1.20 29	1.20 30	1.20 30	1.20 30	1.20 30	1.20 30	1.20 30	1.20 31	1.20 30	1.20 29	1.20 28	1.20 30	1.20 30

CVMVSNet		1.42 29	1.42 29	1.42 30	1.42 30	1.42 31	1.42 31	1.42 31	1.42 31	1.42 31	1.42 31	1.42 32	1.42 31	1.42 30	1.42 29	1.42 31	1.42 31

EU-MVSNet		1.42 29	1.42 29	1.42 30	1.42 30	1.42 31	1.42 31	1.42 31	1.42 31	1.42 31	1.42 31	1.42 32	1.42 31	1.42 30	1.42 29	1.42 31	1.42 31

PS-CasMVS		1.42 29	1.42 29	1.42 30	1.42 30	1.42 31	1.42 31	1.42 31	1.42 31	1.42 31	1.42 31	1.42 32	1.42 31	1.42 30	1.42 29	1.42 31	1.42 31

UniMVSNet_NR-MVSNet		1.42 29	1.42 29	1.42 30	1.42 30	1.42 31	1.42 31	1.42 31	1.42 31	1.42 31	1.42 31	1.42 32	1.42 31	1.42 30	1.42 29	1.42 31	1.42 31

PEN-MVS		1.42 29	1.42 29	1.42 30	1.42 30	1.42 31	1.42 31	1.42 31	1.42 31	1.42 31	1.42 31	1.42 32	1.42 31	1.42 30	1.42 29	1.42 31	1.42 31

TransMVSNet (Re)		1.42 29	1.42 29	1.42 30	1.42 30	1.42 31	1.42 31	1.42 31	1.42 31	1.42 31	1.42 31	1.42 32	1.42 31	1.42 30	1.42 29	1.42 31	1.42 31

DTE-MVSNet		1.42 29	1.42 29	1.42 30	1.42 30	1.42 31	1.42 31	1.42 31	1.42 31	1.42 31	1.42 31	1.42 32	1.42 31	1.42 30	1.42 29	1.42 31	1.42 31

DU-MVS		1.42 29	1.42 29	1.42 30	1.42 30	1.42 31	1.42 31	1.42 31	1.42 31	1.42 31	1.42 31	1.42 32	1.42 31	1.42 30	1.42 29	1.42 31	1.42 31

UniMVSNet (Re)		1.42 29	1.42 29	1.42 30	1.42 30	1.42 31	1.42 31	1.42 31	1.42 31	1.42 31	1.42 31	1.42 32	1.42 31	1.42 30	1.42 29	1.42 31	1.42 31

CP-MVSNet		1.42 29	1.42 29	1.42 30	1.42 30	1.42 31	1.42 31	1.42 31	1.42 31	1.42 31	1.42 31	1.42 32	1.42 31	1.42 30	1.42 29	1.42 31	1.42 31

WR-MVS_H		1.42 29	1.42 29	1.42 30	1.42 30	1.42 31	1.42 31	1.42 31	1.42 31	1.42 31	1.42 31	1.42 32	1.42 31	1.42 30	1.42 29	1.42 31	1.42 31

WR-MVS		1.42 29	1.42 29	1.42 30	1.42 30	1.42 31	1.42 31	1.42 31	1.42 31	1.42 31	1.42 31	1.42 32	1.42 31	1.42 30	1.42 29	1.42 31	1.42 31

NR-MVSNet		1.42 29	1.42 29	1.42 30	1.42 30	1.42 31	1.42 31	1.42 31	1.42 31	1.42 31	1.42 31	1.42 32	1.42 31	1.42 30	1.42 29	1.42 31	1.42 31

Baseline_NR-MVSNet		1.42 29	1.42 29	1.42 30	1.42 30	1.42 31	1.42 31	1.42 31	1.42 31	1.42 31	1.42 31	1.42 32	1.42 31	1.42 30	1.42 29	1.42 31	1.42 31

TranMVSNet+NR-MVSNet		1.42 29	1.42 29	1.42 30	1.42 30	1.42 31	1.42 31	1.42 31	1.42 31	1.42 31	1.42 31	1.42 32	1.42 31	1.42 30	1.42 29	1.42 31	1.42 31

CDPH-MVS		6.66 44	6.66 44	6.66 45	6.66 45	6.66 46	6.66 46	6.66 46	6.66 46	6.66 46	6.66 46	6.66 47	6.66 46	6.66 45	6.66 44	6.66 46	6.66 46

MDTV_nov1_ep13_2view		9.99 45	9.99 45	9.99 46	9.99 46	9.99 47	9.99 47	9.99 47	9.99 47	9.99 49	9.99 47	9.99 50	9.99 47	9.99 46	9.99 45	9.99 47	9.99 47

MDTV_nov1_ep13		9.99 45	9.99 45	9.99 46	9.99 46	9.99 47	9.99 47	9.99 47	9.99 47	9.99 49	9.99 47	9.99 50	9.99 47	9.99 46	9.99 45	9.99 47	9.99 47

test_method		18.19 47	15.64 47	21.17 48	19.00 48	22.00 49	22.50 49	38.00 50	15.50 49	7.50 47	13.00 49	7.00 48	19.00 50	15.50 49	15.50 47	21.00 49	21.00 49

GeoE		20.05 48	18.83 48	21.47 49	25.60 49	29.60 50	22.50 49	31.20 49	19.10 50	8.30 48	13.50 50	9.40 49	17.80 49	14.10 48	17.50 48	23.40 50	28.60 50

GBi-Net		39.84 49	35.75 49	44.63 50	43.04 50	49.88 51	51.06 51	86.51 52	35.34 51	17.20 51	29.83 51	15.85 52	43.43 53	35.35 50	35.70 49	26.51 53	48.28 53

X-MVS		52.20 50	52.20 50	52.20 51	52.20 51	52.20 52	52.20 52	52.20 51	52.20 52	52.20 61	52.20 52	52.20 71	52.20 54	52.20 51	52.20 50	52.20 54	52.20 54

new_pmnet		75.00 51	74.67 51	75.39 52	85.42 54	96.03 56	98.77 55	173.23 53	69.57 53	36.19 52	56.93 53	117.43 75	32.98 51	85.38 59	68.41 51	25.74 51	28.95 51

N_pmnet		75.00 51	74.67 51	75.39 52	85.42 54	96.03 56	98.77 55	173.23 53	69.57 53	36.19 52	56.93 53	117.43 75	32.98 51	85.38 59	68.41 51	25.74 51	28.95 51

tmp_tt				299.50 71	365.00 73	54.00 55	649.00 86	241.00 66	159.00 71	204.00 84	479.00 92	308.00 101	243.00 72	246.00 71	82.00 53	95.00 73

CANet		100.44 53	93.07 53	109.04 54	111.90 56	131.06 61	119.40 58	222.42 62	80.48 55	36.93 54	70.80 55	40.92 57	89.90 55	100.59 61	101.42 54	73.68 59	126.25 55

CANet_DTU		100.44 53	93.07 53	109.04 54	111.90 56	131.06 61	119.40 58	222.42 62	80.48 55	36.93 54	70.80 55	40.92 57	89.90 55	100.59 61	101.42 54	73.68 59	126.25 55

MVS_0304		100.44 53	93.07 53	109.04 54	111.90 56	131.06 61	119.40 58	222.42 62	80.48 55	36.93 54	70.80 55	40.92 57	89.90 55	100.59 61	101.42 54	73.68 59	126.25 55

UGNet		100.44 53	93.07 53	109.04 54	111.90 56	131.06 61	119.40 58	222.42 62	80.48 55	36.93 54	70.80 55	40.92 57	89.90 55	100.59 61	101.42 54	73.68 59	126.25 55
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 64	106.58 57	134.88 65	123.82 60	127.44 59	145.38 62	298.43 70	116.16 69	43.72 59	77.82 59	29.30 54	131.24 66	117.82 68	106.21 58	66.69 57	171.29 69

zzz-MVS		119.64 64	106.58 57	134.88 65	123.82 60	127.44 59	145.38 62	298.43 70	116.16 69	43.72 59	77.82 59	29.30 54	131.24 66	117.82 68	106.21 58	66.69 57	171.29 69

FMVSNet5		116.86 57	110.47 59	124.32 58	131.47 62	157.41 65	150.67 64	199.64 55	115.30 62	56.61 67	97.70 64	51.77 61	117.26 59	77.26 52	113.14 60	90.25 66	160.68 62

test1		116.86 57	110.47 59	124.32 58	131.47 62	157.41 65	150.67 64	199.64 55	115.30 62	56.61 67	97.70 64	51.77 61	117.26 59	77.26 52	113.14 60	90.25 66	160.68 62

FMVSNet3		116.86 57	110.47 59	124.32 58	131.47 62	157.41 65	150.67 64	199.64 55	115.30 62	56.61 67	97.70 64	51.77 61	117.26 59	77.26 52	113.14 60	90.25 66	160.68 62

FMVSNet2		116.86 57	110.47 59	124.32 58	131.47 62	157.41 65	150.67 64	199.64 55	115.30 62	56.61 67	97.70 64	51.77 61	117.26 59	77.26 52	113.14 60	90.25 66	160.68 62

FMVSNet1		116.86 57	110.47 59	124.32 58	131.47 62	157.41 65	150.67 64	199.64 55	115.30 62	56.61 67	97.70 64	51.77 61	117.26 59	77.26 52	113.14 60	90.25 66	160.68 62

MIMVSNet1		116.86 57	110.47 59	124.32 58	131.47 62	157.41 65	150.67 64	199.64 55	115.30 62	56.61 67	97.70 64	51.77 61	117.26 59	77.26 52	113.14 60	90.25 66	160.68 62

MIMVSNet		116.86 57	110.47 59	124.32 58	131.47 62	157.41 65	150.67 64	199.64 55	115.30 62	56.61 67	97.70 64	51.77 61	117.26 59	77.26 52	113.14 60	90.25 66	160.68 62

PVSNet_Blended_VisFu		129.22 66	115.76 66	144.92 67	140.60 69	162.80 72	166.50 71	281.20 67	114.70 59	55.50 64	96.20 61	51.80 68	140.60 68	114.70 65	114.70 67	85.10 63	155.40 59

PVSNet_BlendedMVS		129.22 66	115.76 66	144.92 67	140.60 69	162.80 72	166.50 71	281.20 67	114.70 59	55.50 64	96.20 61	51.80 68	140.60 68	114.70 65	114.70 67	85.10 63	155.40 59

PVSNet_Blended		129.22 66	115.76 66	144.92 67	140.60 69	162.80 72	166.50 71	281.20 67	114.70 59	55.50 64	96.20 61	51.80 68	140.60 68	114.70 65	114.70 67	85.10 63	155.40 59

SixPastTwentyTwo		210.90 69	189.75 69	235.58 70	225.41 72	284.88 75	267.17 74	485.88 73	164.28 72	76.51 74	137.62 71	76.69 74	214.49 71	206.28 70	208.00 70	144.02 74	250.52 71

RPSCF		376.53 70	341.80 70	417.05 72	418.60 75	457.01 80	467.46 79	825.25 80	336.12 74	159.32 78	260.40 74	151.13 79	386.94 73	364.25 72	352.10 71	244.72 75	471.62 73

MS-PatchMatch		438.85 72	388.71 72	497.33 74	479.00 77	527.00 82	558.00 83	988.00 82	379.00 77	174.00 80	278.00 76	162.00 80	494.00 78	418.00 73	412.00 72	291.00 76	545.00 77

DELS-MVS		458.84 75	423.31 75	500.30 75	511.99 81	616.59 84	578.86 84	991.10 83	355.79 76	158.99 77	319.09 78	190.62 83	453.64 77	437.73 75	439.52 73	307.20 78	603.81 78
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
EG-PatchMatch MVS		402.98 71	364.36 71	448.05 73	435.50 76	473.00 81	489.60 80	910.20 81	338.60 75	127.30 75	205.10 72	123.50 77	434.60 74	450.70 76	447.70 74	291.10 77	511.90 74

PatchmatchNet		452.63 74	410.20 74	502.13 76	520.70 82	614.40 83	546.00 81	1018.80 90	379.00 77	167.50 79	277.10 75	169.40 81	437.10 75	437.10 74	457.50 75	322.70 79	536.90 76
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
CSCG		727.26 94	663.25 95	801.94 95	590.65 85	811.25 91	854.12 98	1805.32 105	816.43 103	388.25 101	612.42 102	345.37 109	621.61 85	507.46 78	471.55 76	551.65 98	1078.31 107

ADS-MVSNet		452.36 73	406.02 73	506.42 77	534.76 83	628.22 85	552.79 82	1009.99 89	333.98 73	149.26 76	246.67 73	149.01 78	447.03 76	465.35 77	501.18 77	344.69 80	517.75 75

dps		534.60 76	472.40 76	607.16 79	690.38 91	718.85 88	636.03 85	1231.66 92	422.74 79	198.65 83	325.68 79	194.97 84	512.90 80	509.81 79	513.65 78	373.33 82	621.11 79

Gipuma		587.77 83	529.57 83	655.67 85	637.00 89	733.00 89	749.00 90	1245.00 93	525.00 89	269.00 95	445.00 90	253.00 90	637.00 86	525.00 81	525.00 79	397.00 84	701.00 85
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
IB-MVS	750.90 3	552.99 78	511.38 82	601.53 78	606.02 86	735.75 90	688.75 88	1183.86 91	436.09 81	210.63 86	397.40 82	233.85 88	551.05 81	521.77 80	533.78 80	368.88 81	721.05 86
Christian Sormann, Mattia Rossi, Andreas Kuhn and Friedrich Fraundorfer: IB-MVS: An Iterative Algorithm for Deep Multi-View Stereo based on Binary Decisions. BMVC 2021
IterMVS		554.60 79	488.63 77	631.57 84	636.90 88	700.80 86	674.70 87	1271.10 94	430.50 80	207.10 85	370.50 81	202.70 86	611.80 84	534.20 82	545.30 81	387.80 83	636.40 80
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
MSLP-MVS++		993.91 100	732.21 96	1299.24 110	1631.22 117	1345.26 115	1480.05 116	2524.20 109	735.65 100	463.57 111	499.89 98	302.78 100	1292.66 112	675.99 94	612.79 82	403.71 85	953.11 99

MVS_Test		654.54 84	583.51 85	737.40 87	721.80 93	822.10 92	808.60 92	1494.00 96	542.20 91	259.90 89	441.60 84	257.70 92	689.10 88	620.80 88	617.70 83	451.00 89	782.50 88

casdiffmvs		654.54 84	583.51 85	737.40 87	721.80 93	822.10 92	808.60 92	1494.00 96	542.20 91	259.90 89	441.60 84	257.70 92	689.10 88	620.80 88	617.70 83	451.00 89	782.50 88

diffmvs		654.54 84	583.51 85	737.40 87	721.80 93	822.10 92	808.60 92	1494.00 96	542.20 91	259.90 89	441.60 84	257.70 92	689.10 88	620.80 88	617.70 83	451.00 89	782.50 88

baseline2		654.54 84	583.51 85	737.40 87	721.80 93	822.10 92	808.60 92	1494.00 96	542.20 91	259.90 89	441.60 84	257.70 92	689.10 88	620.80 88	617.70 83	451.00 89	782.50 88

baseline1		654.54 84	583.51 85	737.40 87	721.80 93	822.10 92	808.60 92	1494.00 96	542.20 91	259.90 89	441.60 84	257.70 92	689.10 88	620.80 88	617.70 83	451.00 89	782.50 88

baseline		654.54 84	583.51 85	737.40 87	721.80 93	822.10 92	808.60 92	1494.00 96	542.20 91	259.90 89	441.60 84	257.70 92	689.10 88	620.80 88	617.70 83	451.00 89	782.50 88

pmnet_mix02		659.48 90	547.83 84	789.74 94	720.05 92	846.87 98	740.59 89	2153.63 107	456.15 86	191.24 81	336.49 80	200.39 85	511.90 79	608.74 87	634.29 89	421.05 86	751.91 87

ACMH+	702.88 1	670.82 91	589.81 91	765.33 93	662.52 90	701.42 87	795.24 91	1698.33 103	598.81 98	226.55 87	403.02 83	187.13 82	786.82 95	724.80 97	646.56 90	422.52 87	866.95 95

GG-mvs-BLEND		557.53 80	503.49 78	620.58 81	485.90 78	370.41 76	267.30 75	710.53 76	454.42 82	785.72 121	491.23 94	326.12 103	881.92 98	538.27 83	650.05 91	592.08 100	693.94 81

gm-plane-assit		551.84 77	503.49 78	608.24 80	411.90 74	370.41 76	267.30 75	710.53 76	454.42 82	785.72 121	491.23 94	326.12 103	881.92 98	538.27 83	650.05 91	592.08 100	693.94 81

gg-mvs-nofinetune		557.53 80	503.49 78	620.58 81	485.90 78	370.41 76	267.30 75	710.53 76	454.42 82	785.72 121	491.23 94	326.12 103	881.92 98	538.27 83	650.05 91	592.08 100	693.94 81

CR-MVSNet		557.53 80	503.49 78	620.58 81	485.90 78	370.41 76	267.30 75	710.53 76	454.42 82	785.72 121	491.23 94	326.12 103	881.92 98	538.27 83	650.05 91	592.08 100	693.94 81

new-patchmatchnet		712.65 92	632.59 92	806.05 97	787.79 99	936.25 102	882.47 99	1795.72 104	528.60 90	244.29 88	471.90 91	257.36 91	681.47 87	705.16 96	659.05 95	444.55 88	869.82 96

IterMVS-LS		714.97 93	638.00 94	804.77 96	793.60 100	914.20 100	886.50 101	1612.70 102	588.30 97	285.30 96	491.20 93	278.40 99	759.20 94	677.40 95	681.30 96	491.30 95	835.20 94
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
MVSTER		834.63 95	737.03 97	948.49 98	988.86 102	1140.51 113	1129.34 111	1832.80 106	682.42 99	319.01 97	550.98 100	311.35 102	872.51 97	763.95 98	757.83 97	548.41 97	952.20 98

PMVS	743.55 2	836.66 96	637.90 93	1068.55 106	1306.50 114	875.12 99	1166.70 112	2629.00 110	512.24 88	196.22 82	282.69 77	237.15 89	597.87 83	842.47 99	765.54 98	514.99 96	950.09 97
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
MVS_111021_LR		1055.24 107	916.36 101	1217.27 108	1129.93 112	1268.26 114	1313.88 115	2635.76 111	923.19 105	396.92 105	704.88 106	327.66 107	1136.32 110	965.38 101	946.95 99	690.83 108	1278.20 108

PatchT		878.42 98	785.05 98	987.36 99	1050.05 110	922.05 101	1111.05 109	677.05 75	950.05 106	1285.90 148	750.05 108	640.05 120	850.05 96	950.05 100	950.05 100	950.05 111	333.05 72

ACMP	1170.86 6	1091.37 108	943.23 102	1264.21 109	1112.10 111	1138.94 112	1276.90 114	2675.36 112	989.62 107	426.15 109	742.77 107	349.09 111	1454.51 116	1047.36 109	969.90 101	640.22 104	1364.94 111
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
ACMM	1129.18 5	1047.56 106	912.90 100	1204.67 107	1040.21 109	1016.71 110	1105.32 108	2918.67 113	813.91 102	327.22 98	665.34 104	267.72 98	1192.58 111	1091.35 110	991.88 102	643.99 105	1543.40 116
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
ambc			999.00 104		999.00 103	999.00 104	999.00 102		999.00 108	999.00 131	999.00 115	999.00 139	999.00 104	999.00 103	999.00 103	999.00 112	999.00 101

EPMVS		999.00 101	999.00 104	999.00 100	999.00 103	999.00 104	999.00 102	999.00 84	999.00 108	999.00 131	999.00 115	999.00 139	999.00 104	999.00 103	999.00 103	999.00 112	999.00 101

uanet_test		1000.00 102	1000.00 106	1000.00 101	1000.00 105	1000.00 106	1000.00 104	1000.00 85	1000.00 110	1000.00 133	1000.00 117	1000.00 141	1000.00 106	1000.00 105	1000.00 105	1000.00 114	1000.00 103

sosnet		1000.00 102	1000.00 106	1000.00 101	1000.00 105	1000.00 106	1000.00 104	1000.00 85	1000.00 110	1000.00 133	1000.00 117	1000.00 141	1000.00 106	1000.00 105	1000.00 105	1000.00 114	1000.00 103

USDC		1000.00 102	1000.00 106	1000.00 101	1000.00 105	1000.00 106	1000.00 104	1000.00 85	1000.00 110	1000.00 133	1000.00 117	1000.00 141	1000.00 106	1000.00 105	1000.00 105	1000.00 114	1000.00 103

TinyColmap		1000.00 102	1000.00 106	1000.00 101	1000.00 105	1000.00 106	1000.00 104	1000.00 85	1000.00 110	1000.00 133	1000.00 117	1000.00 141	1000.00 106	1000.00 105	1000.00 105	1000.00 114	1000.00 103

ACMH	935.68 4	948.23 99	857.00 99	1054.67 105	946.00 101	970.00 103	1125.00 110	2467.00 108	823.00 104	330.00 99	622.00 103	211.00 87	891.00 102	970.00 102	1061.00 109	569.00 99	1342.00 109
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
TSAR-MVS + GP.		1239.27 109	1094.74 112	1407.89 111	1220.99 113	1845.47 120	1680.98 119	3191.81 114	1098.41 114	362.98 100	679.12 105	339.31 108	1323.06 113	1173.24 113	1093.83 110	667.49 106	1433.78 112

ACMMPR		1265.65 110	1083.59 111	1478.06 113	1441.06 116	1438.61 118	1540.68 118	3284.05 116	1219.68 116	458.81 110	803.22 110	346.91 110	1421.66 115	1126.11 112	1150.51 111	722.08 109	1500.09 114

RPMNet		858.01 97	961.99 103	736.69 86	550.05 84	1120.24 111	1212.05 113	463.05 72	485.90 87	550.05 113	580.05 101	890.05 134	559.05 82	1485.90 114	1185.90 112	1085.90 118	985.90 100

DeepC-MVS_fast	2081.98 8	1311.87 111	1172.50 113	1474.47 112	1411.78 115	1397.23 117	1519.03 117	3401.40 117	1201.29 115	417.90 107	801.95 109	976.25 138	1409.37 114	1114.52 111	1201.12 113	687.33 107	1515.14 115
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
FPMVS		1356.65 112	1072.60 110	1688.04 114	1840.79 118	1397.01 116	1793.24 120	4397.86 121	804.66 101	408.78 106	538.65 99	407.36 112	894.84 103	1587.73 115	1286.38 114	792.73 110	1486.39 113

PCF-MVS	3738.24 13	2129.60 116	1746.89 115	2576.10 123	2258.22 124	2263.67 121	2650.06 128	6361.78 134	1676.15 123	695.66 118	1209.77 122	737.88 124	2237.28 119	2083.02 123	1835.31 115	1253.58 123	2422.45 118
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
SD-MVS		2324.36 122	1910.97 117	2806.65 130	2945.31 132	3305.03 136	3267.51 133	5962.25 133	1896.37 126	848.15 126	1224.25 123	661.55 121	2707.30 131	1913.40 117	1871.41 116	1109.38 119	2504.79 119
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
MVS-HIRNet		1975.98 114	1797.02 116	2184.76 116	2111.07 120	2443.03 124	2503.43 123	4063.71 118	1684.46 124	711.34 119	1456.05 127	848.70 132	2396.26 127	1900.93 116	1915.01 117	1322.75 125	2330.99 117

AdaColmap		2288.90 120	2080.73 124	2531.77 121	2485.98 127	2757.87 128	2974.47 130	4914.62 123	2255.54 132	804.63 125	1611.14 131	842.30 131	2657.83 130	2056.92 122	1960.62 118	1353.09 127	3080.73 126

OpenMVS	2049.89 7	1895.92 113	1721.29 114	2099.67 115	2064.00 119	2419.00 123	2138.00 121	4572.00 122	1541.00 121	548.00 112	937.00 112	580.00 117	1983.00 118	1971.00 121	1993.00 119	1293.00 124	2608.00 120

CHOSEN 280x420		2225.10 117	1992.66 120	2496.28 118	2192.10 121	2641.81 125	2621.41 125	5345.34 126	2116.46 129	1002.26 137	1683.84 132	837.43 128	2338.65 121	1920.94 118	2020.28 120	1477.92 130	2727.86 121

CHOSEN 1792x2688		2225.10 117	1992.66 120	2496.28 118	2192.10 121	2641.81 125	2621.41 125	5345.34 126	2116.46 129	1002.26 137	1683.84 132	837.43 128	2338.65 121	1920.94 118	2020.28 120	1477.92 130	2727.86 121

HyFIR lowres test		2225.10 117	1992.66 120	2496.28 118	2192.10 121	2641.81 125	2621.41 125	5345.34 126	2116.46 129	1002.26 137	1683.84 132	837.43 128	2338.65 121	1920.94 118	2020.28 120	1477.92 130	2727.86 121

Vis-MVSNet		2390.77 124	1976.57 118	2874.00 131	2644.00 130	3248.00 134	3040.00 131	7371.00 138	1627.00 122	421.00 108	1200.00 121	622.00 119	2251.00 120	2326.00 128	2052.00 123	1517.00 133	2761.00 124
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
DeepPCF-MVS	3033.31 11	2362.79 123	2183.15 125	2572.38 122	2349.28 125	2383.16 122	2740.92 129	5212.97 125	2043.02 128	751.44 120	1466.47 128	1327.42 151	2904.33 132	2573.45 134	2227.77 124	1475.33 129	3260.73 129

SteuartSystems-ACMMP		2615.00 125	2242.57 126	3049.50 132	2828.00 131	2801.00 129	3323.00 135	6648.00 136	2491.00 134	1023.00 140	1605.00 130	697.00 122	2926.00 134	2502.00 131	2279.00 125	1549.00 135	3323.00 131
Skip Steuart: Steuart Systems R&D Blog.
tpm cat1		2652.13 126	2606.66 131	2705.18 126	3151.86 134	6902.39 150	3612.17 138	5463.78 129	1457.76 118	391.31 102	1358.61 124	446.44 113	2360.09 124	2296.48 124	2290.90 126	1251.84 120	3494.04 132

CostFormer		2652.13 126	2606.66 131	2705.18 126	3151.86 134	6902.39 150	3612.17 138	5463.78 129	1457.76 118	391.31 102	1358.61 124	446.44 113	2360.09 124	2296.48 124	2290.90 126	1251.84 120	3494.04 132

tpm		2652.13 126	2606.66 131	2705.18 126	3151.86 134	6902.39 150	3612.17 138	5463.78 129	1457.76 118	391.31 102	1358.61 124	446.44 113	2360.09 124	2296.48 124	2290.90 126	1251.84 120	3494.04 132

DVP-MVS		3258.34 138	2529.80 129	4108.31 142	4005.62 145	4693.14 146	4737.88 149	10195.40 149	2408.38 133	941.44 127	1505.82 129	734.32 123	3438.27 141	2449.15 130	2386.04 129	1331.25 126	3531.75 136
Zhenlong Yuan, Jinguo Luo, Fei Shen, Zhaoxin Li, Cong Liu, Tianlu Mao, Zhaoqi Wang: DVP-MVS: Synergize Depth-Edge and Visibility Prior for Multi-View Stereo. AAAI2025
3Dnovator	2220.89 9	2303.77 121	2037.00 123	2615.00 124	2617.00 129	2967.00 130	2616.00 124	5882.00 132	1928.00 127	589.00 114	907.00 111	528.00 116	2443.00 129	2370.00 129	2392.00 130	1543.00 134	3167.00 127

CMPMVS	2507.20 10	2083.60 115	1983.13 119	2200.81 117	2582.70 128	3097.30 131	2332.10 122	4364.50 120	1390.00 117	653.68 117	997.75 114	742.65 127	1880.20 117	2298.80 127	2413.60 131	1391.70 128	2941.80 125
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
TAPA-MVS	5463.68 16	2764.21 131	2434.28 127	3149.14 133	3645.15 142	3257.60 135	3452.71 137	6526.32 135	2591.85 137	651.36 116	1964.77 143	947.44 137	2924.41 133	2523.36 132	2452.68 132	1694.86 139	3302.28 130
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
TSAR-MVS + MP.		4216.58 142	4674.68 144	3682.13 139	3752.63 143	4315.48 144	4264.77 146	7782.51 141	2583.81 136	1125.68 145	16722.30 155	882.60 133	3589.10 142	2523.80 133	2486.45 133	1578.08 136	3208.34 128
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
COLMAP_ROB	3798.28 14	2690.62 130	2704.29 137	2674.67 125	3138.00 133	3522.00 139	3826.00 143	3219.00 115	2702.00 139	1138.00 146	2260.00 145	1212.00 150	2968.00 135	2936.00 141	2571.00 134	1759.00 142	3727.00 139
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
TSAR-MVS + ACMM		3184.92 135	2679.45 136	3774.64 141	3302.51 138	4168.07 142	4256.74 145	8947.31 145	2634.53 138	1026.25 141	1723.72 137	1043.87 147	3387.29 139	2794.29 135	2687.41 135	1727.73 141	3704.25 137

DPM-MVS		3051.54 133	2661.57 134	3506.50 135	3532.00 140	3332.00 137	3744.00 141	7839.00 142	2772.00 140	985.00 129	1919.00 141	738.00 125	3319.00 137	2901.00 138	2715.00 136	1620.00 137	4254.00 142

OPM-MVS		3051.54 133	2661.57 134	3506.50 135	3532.00 140	3332.00 137	3744.00 141	7839.00 142	2772.00 140	985.00 129	1919.00 141	738.00 125	3319.00 137	2901.00 138	2715.00 136	1620.00 137	4254.00 142

tpmrst		2688.71 129	2604.46 130	2787.00 129	2472.96 126	3190.36 132	3313.69 134	5003.06 124	1837.26 125	1097.38 143	1721.89 136	1012.20 146	2415.09 128	2970.27 142	2736.80 138	2419.79 147	4762.44 144

MVS_111021_HR		3192.50 136	2773.91 138	3680.86 138	3515.58 139	3815.81 141	4020.82 144	7766.11 140	2775.23 142	1300.96 151	2221.19 144	1117.25 149	3420.01 140	2873.98 136	2835.60 139	2061.69 145	3778.31 140

3Dnovator+	3173.67 12	2938.77 132	2519.43 128	3428.00 134	3256.00 137	3708.00 140	3443.00 136	7516.00 139	2525.00 135	1121.00 144	972.00 113	925.00 136	3192.00 136	2899.00 137	2897.00 140	2040.00 144	3710.00 138

SED-MVS		3539.47 140	2909.05 140	4274.95 144	4528.93 148	4986.51 147	5003.31 151	8985.31 146	2904.53 144	1294.24 150	1839.12 140	1003.69 145	4135.17 144	2926.32 140	2897.04 141	1702.75 140	3806.13 141

MSP-MVS		3241.28 137	2825.26 139	3726.65 140	3945.31 144	4305.03 143	4267.51 147	6962.25 137	2896.37 143	1068.15 142	1824.25 139	1061.55 148	4307.30 145	3013.40 143	3171.41 142	1809.38 143	3504.79 135
Zhenlong Yuan, Cong Liu, Fei Shen, Zhaoxin Li, Jingguo luo, Tianlu Mao and Zhaoqi Wang: MSP-MVS: Multi-granularity Segmentation Prior Guided Multi-View Stereo. AAAI2025
MAR-MVS		3961.62 141	3726.55 142	4235.86 143	4107.62 147	6522.83 149	4862.93 150	7956.64 144	3380.98 145	1665.13 153	3231.54 149	1650.34 154	4357.29 146	3198.61 144	3209.42 143	2465.52 148	4892.15 145
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
PLC	4785.50 15	3275.54 139	3030.86 141	3561.00 137	4093.00 146	4596.00 145	5174.00 152	4267.00 119	3570.00 146	1495.00 152	2940.00 148	1594.00 153	3947.00 143	3817.00 145	3343.00 144	2390.00 146	1356.00 110
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
DeepC-MVS	5581.15 17	4824.92 144	5020.53 145	4596.70 145	4714.52 149	3205.14 133	3108.50 132	10234.20 150	3823.34 148	1885.23 155	9002.42 152	2045.34 157	4715.23 148	7652.65 149	3993.41 145	2922.51 149	5421.41 146
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
OMC-MVS		4439.92 143	3906.78 143	5061.92 146	4748.70 150	5679.38 148	5855.03 153	9923.00 147	4023.36 149	1740.95 154	1693.78 135	1693.78 155	4658.45 147	4254.77 146	4135.74 146	3445.36 150	5866.63 147

TSAR-MVS + COLMAP		6088.23 145	5315.97 146	6989.21 147	6522.51 151	8025.15 153	7938.31 154	15276.20 151	5401.97 151	1914.31 156	3802.65 150	1979.48 156	6704.11 150	5217.07 147	5137.16 147	3579.82 151	7648.29 148

CLD-MVS		6986.85 146	6222.57 147	7878.50 148	7707.00 152	8884.00 154	9025.00 155	15607.00 152	6148.00 152	2571.00 157	4822.00 151	2082.00 158	7875.00 152	6389.00 148	6449.00 148	4486.00 152	8784.00 150
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
LS3D		7481.83 147	6596.02 148	8515.28 149	9871.71 153	9844.03 155	9225.16 156	18308.40 153	5364.90 150	1267.41 147	2381.61 146	1512.79 152	7225.72 151	8875.69 150	9516.28 149	5193.26 153	8676.83 149

ACMMP		9999.00 148	9999.00 149	9999.00 150	9999.00 155	9999.00 156	9999.00 157	9999.00 148	9999.00 153	9999.00 159	9999.00 153	9999.00 160	9999.00 153	9999.00 151	9999.00 150	9999.00 155	9999.00 151
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		17763.08 150	15907.71 151	19927.67 152	19334.00 157	22387.00 158	22896.00 158	38668.00 154	15772.00 154	7632.00 158	13229.00 154	7123.00 159	19334.00 154	15773.00 152	15700.00 151	11702.00 156	21370.00 153

LTVRE_ROB	38377.89 19	49656.08 152	18936.71 152	85495.33 154	306852.00 160	22526.00 159	29206.00 159	112098.00 158	30022.00 155	17348.00 161	2824.00 147	11239.00 161	29457.00 155	20569.00 153	19941.00 152	18011.00 157	25436.00 154
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
MVE	11086.50 18	13278.69 149	12303.57 150	14416.33 151	9890.00 154	17107.00 157	4634.00 148	59884.00 156	3666.00 147	966.00 128	1792.00 138	896.00 135	5680.00 149	20677.00 154	23030.00 153	5444.00 154	18957.00 152
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
MSDG		31705.85 151	29167.57 153	34667.17 153	44079.00 158	28314.00 160	44778.00 160	43648.00 155	31045.00 156	14849.00 160	26179.00 156	13752.00 162	38088.00 156	30859.00 155	30835.00 154	22561.00 158	43189.00 155

PHI-MVS		99999.00 153	99999.00 154	99999.00 155	99999.00 159	99999.00 161	99999.00 161	99999.00 157	99999.00 157	99999.00 162	99999.00 157	99999.00 163	99999.00 157	99999.00 156	99999.00 155	99999.00 159	99999.00 156

ET-MVSNet_ETH3D		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

UniMVSNet_ETH3D		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

thisisatest0530		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

Anonymous202405211			10000000.00 155		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158		10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

DCV-MVSNet		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

tttt0517		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

thisisatest0515		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

DPE-MVS		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
test_part1		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

thres100view900		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

tfpnnormal		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

tfpn200view9		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

IterMVS-SCA-FT		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

pmmvs6		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

pmmvs5		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

Anonymous20231211		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

pmmvs-eth3d		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

Anonymous20231206		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

SCA		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

canonicalmvs		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

anonymousdsp		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

FC-MVSNet-train		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

UA-Net		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

FC-MVSNet-test		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

sosnet-low-res		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

DI_MVS_plusplus_trai		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

HPM-MVS++		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

pm-mvs1		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

APDe-MVS		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

pmmvs4		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

test-LLR		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

TESTMET0.1,1		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

test-mter		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

testgi		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

test20.03		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

thres600view7		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

MP-MVS		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
testmvs		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

thres400		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

test123		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

thres200		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

test0.0.03 1		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

pmmvs3		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

EMVS		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

E-PMN		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

PGM-MVS		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

MCST-MVS		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

PMMVS2		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

PM-MVS		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

LGP-MVS_train		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

EPNet_dtu		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
EPNet		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CNVR-MVS		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

NCCC		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

CP-MVS		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

CPTT-MVS		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

HQP-MVS		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

IS_MVSNet		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

Vis-MVSNet (Re-imp)		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

PatchMatch-RL		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

TDRefinement		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

EPP-MVSNet		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

PMMVS		10000000.00 154	10000000.00 155	10000000.00 156	10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 159	10000000.00 158	10000000.00 163	10000000.00 158	10000000.00 164	10000000.00 158	10000000.00 157	10000000.00 156	10000000.00 160	10000000.00 157

APD-MVS		1000000000.00 216	1000000000.00 218	1000000000.00 218	1000000000.00 225	1000000000.00 225	1000000000.00 226	1000000000.00 222	1000000000.00 222	1000000000.00 226	1000000000.00 221	1000000000.00 228	1000000000.00 221	1000000000.00 220	1000000000.00 219	1000000000.00 223	1000000000.00 220
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
RE-MVS-def										610.10 115

9.14												0.00 1

SR-MVS					610.10 87			610.10 74				610.10 118

our_test_3					9999.00 155	99.00 58	99.00 57

MTAPA										41.98 58		28.43 53

MTMP										10000000.00 163		31.71 56

Patchmatch-RL test							10000000.00 162

XVS					52.20 51	52.20 52	52.20 52			52.20 61		52.20 71				52.20 54

X-MVStestdata					52.20 51	52.20 52	52.20 52			52.20 61		52.20 71				52.20 54

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					10000000.00 161							10000000.00 164

NP-MVS									10000000.00 158

Patchmtry						1825.90 119	885.90 100	1405.90 95		1285.90 148

DeepMVS_CX						1.00 29	1.00 29	1.00 29	1.00 29	1.00 29	1.00 29	1.00 30	1.00 29	1.00 28		1.00 29	1.00 29

High-resolution multi-view benchmark