This table lists the benchmark results for the low-res two-view scenario. This benchmark evaluates the Middlebury stereo metrics (for all metrics, smaller is better):

The mask determines whether the metric is evaluated for all pixels with ground truth, or only for pixels which are visible in both images (non-occluded).
The coverage selector allows to limit the table to results for all pixels (dense), or a given minimum fraction of pixels.

Methods with suffix _ROB may participate in the Robust Vision Challenge.

Click one or more dataset result cells or column headers to show visualizations. Most visualizations are only available for training datasets. The visualizations may not work with mobile browsers.




Method Infoalllakes. 1llakes. 1ssand box 1lsand box 1sstora. room 1lstora. room 1sstora. room 2lstora. room 2sstora. room 2 1lstora. room 2 1sstora. room 2 2lstora. room 2 2sstora. room 3lstora. room 3stunnel 1ltunnel 1stunnel 2ltunnel 2stunnel 3ltunnel 3s
sorted bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort by
R-Stereo Traintwo views0.15
1
0.03
1
0.77
4
0.00
1
0.00
1
0.74
36
0.00
1
1.36
54
0.09
2
0.02
31
0.00
1
0.01
1
0.00
1
0.01
1
0.00
1
0.00
1
0.00
1
0.00
1
0.00
1
0.00
1
0.01
21
R-Stereotwo views0.15
1
0.03
1
0.77
4
0.00
1
0.00
1
0.74
36
0.00
1
1.36
54
0.09
2
0.02
31
0.00
1
0.01
1
0.00
1
0.01
1
0.00
1
0.00
1
0.00
1
0.00
1
0.00
1
0.00
1
0.01
21
HITNettwo views0.19
3
0.55
59
1.36
18
0.00
1
0.00
1
0.25
5
0.00
1
1.09
44
0.23
15
0.00
1
0.00
1
0.14
13
0.02
14
0.02
3
0.14
25
0.00
1
0.00
1
0.00
1
0.00
1
0.05
36
0.00
1
AdaStereotwo views0.20
4
0.06
3
0.86
6
0.00
1
0.00
1
0.25
5
0.00
1
1.71
68
0.56
27
0.00
1
0.00
1
0.31
27
0.01
8
0.11
7
0.11
21
0.00
1
0.00
1
0.00
1
0.00
1
0.01
10
0.00
1
Xiao Song, Guorun Yang, Xinge Zhu, Hui Zhou, Zhe Wang, Jianping Shi: AdaStereo: A Simple and Efficient Approach for Adaptive Stereo Matching. ArXiv
MLCVtwo views0.23
5
0.46
41
1.15
14
0.00
1
0.00
1
0.45
15
0.00
1
0.57
18
0.15
6
0.09
49
0.00
1
0.27
23
0.03
24
1.09
14
0.25
32
0.00
1
0.00
1
0.00
1
0.00
1
0.05
36
0.00
1
DeepPruner_ROBtwo views0.23
5
0.37
33
1.26
15
0.00
1
0.00
1
1.11
65
0.03
58
0.20
4
0.07
1
0.00
1
0.00
1
0.39
36
0.03
24
1.12
15
0.02
7
0.00
1
0.00
1
0.00
1
0.00
1
0.04
32
0.00
1
StereoDRNet-Refinedtwo views0.24
7
0.08
8
0.68
2
0.00
1
0.00
1
0.83
43
0.00
1
0.66
22
0.61
46
0.00
1
0.00
1
0.50
43
0.02
14
1.28
17
0.08
18
0.00
1
0.00
1
0.00
1
0.00
1
0.10
57
0.04
56
Rohan Chabra, Julian Straub, Chris Sweeney, Richard Newcombe, Henry Fuchs: StereoDRNet. CVPR
MFMNet_retwo views0.24
7
0.74
79
2.31
50
0.53
90
0.00
1
0.17
2
0.01
39
0.02
1
0.59
43
0.01
22
0.03
53
0.12
10
0.00
1
0.07
4
0.01
3
0.00
1
0.00
1
0.00
1
0.00
1
0.19
77
0.01
21
iResNettwo views0.25
9
0.27
19
1.68
30
0.00
1
0.00
1
0.69
33
0.00
1
1.22
51
0.56
27
0.00
1
0.00
1
0.04
4
0.03
24
0.12
8
0.30
35
0.00
1
0.00
1
0.00
1
0.00
1
0.05
36
0.01
21
DN-CSS_ROBtwo views0.26
10
0.75
80
1.33
17
0.00
1
0.00
1
0.99
57
0.00
1
1.04
39
0.61
46
0.01
22
0.00
1
0.19
18
0.02
14
0.07
4
0.01
3
0.00
1
0.00
1
0.00
1
0.00
1
0.22
81
0.01
21
DLCB_ROBtwo views0.27
11
0.16
13
0.71
3
0.00
1
0.00
1
0.44
14
0.00
1
0.43
10
0.57
31
0.02
31
0.04
54
0.63
46
0.04
31
2.18
27
0.24
31
0.00
1
0.00
1
0.00
1
0.00
1
0.00
1
0.00
1
NCCL2two views0.29
12
0.50
46
1.52
24
0.00
1
0.00
1
0.81
41
0.00
1
0.45
11
0.22
13
0.00
1
0.00
1
0.02
3
0.03
24
2.14
25
0.06
14
0.00
1
0.00
1
0.02
85
0.00
1
0.01
10
0.03
45
iResNet_ROBtwo views0.30
13
0.66
71
1.41
20
0.00
1
0.00
1
0.70
34
0.00
1
0.79
29
0.57
31
0.04
43
0.01
37
0.08
6
0.01
8
1.55
18
0.03
9
0.00
1
0.00
1
0.00
1
0.00
1
0.06
42
0.00
1
ETE_ROBtwo views0.31
14
0.34
24
0.89
7
0.00
1
0.00
1
0.97
53
0.01
39
1.45
61
0.57
31
0.02
31
0.00
1
0.17
14
0.02
14
1.75
19
0.07
16
0.00
1
0.00
1
0.00
1
0.00
1
0.00
1
0.00
1
DISCOtwo views0.31
14
0.11
9
1.73
33
0.16
80
0.16
81
0.31
7
0.00
1
0.09
2
0.17
8
0.00
1
0.01
37
1.51
71
0.00
1
1.21
16
0.62
48
0.00
1
0.00
1
0.00
1
0.00
1
0.03
28
0.01
21
LALA_ROBtwo views0.31
14
0.38
34
0.91
10
0.00
1
0.01
48
1.00
58
0.01
39
1.60
63
0.61
46
0.15
55
0.00
1
0.09
8
0.01
8
1.04
13
0.41
39
0.00
1
0.00
1
0.00
1
0.00
1
0.02
20
0.00
1
CFNet_RVCtwo views0.31
14
0.34
24
0.96
11
0.00
1
0.00
1
1.08
62
0.00
1
0.19
3
0.15
6
0.01
22
0.00
1
0.48
41
0.00
1
2.95
40
0.05
13
0.00
1
0.00
1
0.01
79
0.00
1
0.01
10
0.01
21
NLCA_NET_v2_RVCtwo views0.35
18
0.49
45
2.00
40
0.00
1
0.02
55
0.96
51
0.00
1
0.55
17
0.18
11
0.03
37
0.00
1
0.35
32
0.10
44
2.37
30
0.01
3
0.00
1
0.00
1
0.00
1
0.00
1
0.00
1
0.00
1
Zhibo Rao, Mingyi He, Yuchao Dai, Zhidong Zhu, Bo Li, and Renjie He.: NLCA-Net: A non-local context attention network for stereo matching.
iResNetv2_ROBtwo views0.36
19
1.03
88
2.96
63
0.00
1
0.00
1
0.58
22
0.00
1
1.51
62
0.58
39
0.01
22
0.00
1
0.08
6
0.02
14
0.07
4
0.02
7
0.00
1
0.00
1
0.00
1
0.00
1
0.29
89
0.02
35
CC-Net-ROBtwo views0.37
20
0.50
46
2.09
47
0.00
1
0.02
55
0.98
54
0.00
1
0.46
12
0.17
8
0.08
47
0.00
1
0.33
28
0.11
45
2.54
33
0.01
3
0.00
1
0.00
1
0.00
1
0.01
76
0.01
10
0.00
1
XPNet_ROBtwo views0.37
20
0.34
24
1.01
12
0.01
47
0.00
1
0.96
51
0.00
1
1.11
46
0.46
20
0.00
1
0.00
1
0.17
14
0.02
14
2.73
35
0.54
45
0.00
1
0.00
1
0.00
1
0.00
1
0.01
10
0.01
21
PSMNet_ROBtwo views0.41
22
0.54
54
1.69
32
0.00
1
0.00
1
0.92
50
0.00
1
0.27
5
0.53
24
0.00
1
0.00
1
0.25
22
0.03
24
3.43
45
0.47
41
0.00
1
0.00
1
0.00
1
0.00
1
0.05
36
0.03
45
RPtwo views0.42
23
0.44
39
1.52
24
0.00
1
0.01
48
0.61
25
0.02
54
1.06
41
0.39
18
0.03
37
0.01
37
0.99
56
0.16
49
2.89
39
0.18
27
0.00
1
0.00
1
0.00
1
0.00
1
0.10
57
0.00
1
StereoDRNettwo views0.42
23
0.50
46
2.50
54
0.02
53
0.06
72
0.51
17
0.00
1
0.34
7
0.61
46
0.00
1
0.00
1
0.33
28
0.02
14
2.87
38
0.50
44
0.00
1
0.00
1
0.00
1
0.00
1
0.02
20
0.02
35
DRN-Testtwo views0.43
25
0.13
12
1.95
39
0.03
58
0.09
79
0.61
25
0.00
1
1.43
58
0.61
46
0.00
1
0.00
1
0.18
17
0.04
31
3.32
44
0.11
21
0.00
1
0.00
1
0.00
1
0.00
1
0.01
10
0.01
21
NVstereo2Dtwo views0.45
26
0.11
9
1.91
38
0.00
1
0.00
1
0.59
24
0.00
1
1.39
56
0.61
46
0.03
37
0.00
1
0.33
28
0.00
1
3.94
53
0.07
16
0.00
1
0.00
1
0.00
1
0.00
1
0.00
1
0.00
1
ccstwo views0.46
27
0.56
61
1.46
22
0.00
1
0.00
1
0.81
41
0.01
39
0.64
21
0.57
31
0.01
22
0.00
1
0.09
8
0.01
8
4.76
59
0.21
30
0.00
1
0.00
1
0.00
1
0.00
1
0.08
50
0.01
21
ccs_robtwo views0.46
27
0.54
54
1.68
30
0.00
1
0.00
1
0.98
54
0.01
39
0.70
25
0.57
31
0.00
1
0.00
1
0.07
5
0.01
8
4.35
57
0.17
26
0.00
1
0.00
1
0.00
1
0.00
1
0.11
62
0.03
45
CF-Nettwo views0.47
29
0.53
52
2.05
44
0.00
1
0.00
1
0.41
11
0.01
39
1.18
50
0.40
19
0.13
51
0.05
55
1.30
66
0.45
60
2.43
32
0.30
35
0.00
1
0.00
1
0.00
1
0.00
1
0.09
53
0.00
1
TDLMtwo views0.49
30
0.39
35
1.02
13
0.00
1
0.00
1
1.08
62
0.01
39
0.36
8
0.58
39
0.14
53
0.00
1
0.27
23
0.19
50
5.46
69
0.20
29
0.00
1
0.00
1
0.00
1
0.00
1
0.13
66
0.01
21
NCC-stereotwo views0.49
30
0.46
41
2.04
43
0.03
58
0.03
65
1.06
59
0.01
39
0.78
28
0.22
13
0.06
45
0.19
60
0.64
47
0.05
37
3.65
48
0.63
49
0.00
1
0.00
1
0.00
1
0.00
1
0.02
20
0.00
1
stereogantwo views0.49
30
0.22
17
2.39
51
0.00
1
0.00
1
0.63
29
0.02
54
0.79
29
0.72
68
0.06
45
0.00
1
1.68
72
0.46
61
2.63
34
0.04
10
0.00
1
0.00
1
0.00
1
0.00
1
0.14
68
0.00
1
RGCtwo views0.50
33
0.53
52
2.42
52
0.00
1
0.01
48
0.65
30
0.00
1
1.07
42
0.17
8
0.01
22
0.62
67
1.00
57
0.19
50
3.03
41
0.28
34
0.00
1
0.00
1
0.00
1
0.00
1
0.05
36
0.02
35
SHDtwo views0.50
33
0.51
51
3.61
73
0.05
65
0.00
1
0.01
1
0.01
39
0.72
26
0.61
46
1.57
75
0.00
1
0.34
31
0.09
41
1.79
21
0.49
43
0.00
1
0.00
1
0.00
1
0.01
76
0.09
53
0.03
45
PASMtwo views0.51
35
0.32
22
3.07
64
0.00
1
0.00
1
0.31
7
0.00
1
0.46
12
0.12
4
0.03
37
0.00
1
0.44
38
0.02
14
5.22
66
0.04
10
0.00
1
0.00
1
0.00
1
0.00
1
0.12
63
0.03
45
G-Nettwo views0.51
35
0.54
54
2.88
61
0.00
1
0.01
48
0.74
36
0.01
39
0.69
24
0.19
12
0.00
1
0.00
1
1.38
68
0.07
39
3.26
43
0.48
42
0.00
1
0.00
1
0.00
1
0.00
1
0.02
20
0.01
21
HSM-Net_RVCpermissivetwo views0.52
37
0.06
3
1.45
21
0.00
1
0.00
1
0.61
25
0.00
1
3.83
89
0.52
22
0.14
53
0.00
1
0.22
21
0.03
24
3.50
47
0.04
10
0.01
79
0.00
1
0.00
1
0.00
1
0.00
1
0.00
1
Gengshan Yang, Joshua Manela, Michael Happold, and Deva Ramanan: Hierarchical Deep Stereo Matching on High-resolution Images. CVPR 2019
CVANet_RVCtwo views0.53
38
0.32
22
1.26
15
0.00
1
0.00
1
0.98
54
0.00
1
0.72
26
0.55
26
0.35
59
0.12
58
0.36
34
0.14
47
5.53
71
0.08
18
0.00
1
0.00
1
0.00
1
0.00
1
0.16
73
0.00
1
RYNettwo views0.53
38
0.19
15
1.79
35
0.00
1
0.00
1
0.55
20
0.00
1
1.12
47
0.61
46
0.02
31
0.00
1
0.83
51
0.04
31
5.05
64
0.45
40
0.00
1
0.00
1
0.00
1
0.00
1
0.00
1
0.02
35
GANetREF_RVCpermissivetwo views0.54
40
0.70
74
2.06
45
0.00
1
0.00
1
1.14
66
0.00
1
1.61
64
0.58
39
0.00
1
0.01
37
0.29
25
0.04
31
4.21
55
0.06
14
0.00
1
0.00
1
0.00
1
0.00
1
0.03
28
0.02
35
Zhang, Feihu and Prisacariu, Victor and Yang, Ruigang and Torr, Philip HS: GA-Net: Guided Aggregation Net for End- to-end Stereo Matching. CVPR 2019
GANettwo views0.55
41
0.35
29
1.40
19
0.00
1
0.00
1
0.77
40
0.08
61
0.36
8
0.57
31
0.01
22
0.00
1
0.68
48
0.11
45
5.52
70
1.07
53
0.00
1
0.00
1
0.02
85
0.00
1
0.09
53
0.03
45
CFNettwo views0.56
42
0.50
46
1.58
26
0.00
1
0.00
1
1.06
59
0.01
39
1.08
43
0.57
31
0.00
1
0.01
37
0.12
10
0.01
8
5.87
79
0.19
28
0.00
1
0.00
1
0.00
1
0.00
1
0.13
66
0.02
35
PDISCO_ROBtwo views0.56
42
0.57
62
2.07
46
0.17
81
0.00
1
1.56
74
0.01
39
2.27
78
0.51
21
0.08
47
0.01
37
0.74
49
0.28
57
2.37
30
0.13
24
0.00
1
0.00
1
0.00
1
0.00
1
0.33
92
0.00
1
PA-Nettwo views0.57
44
0.50
46
2.73
60
0.03
58
0.06
72
0.89
47
0.02
54
0.66
22
0.63
63
0.00
1
0.00
1
0.43
37
0.07
39
4.82
60
0.55
47
0.01
79
0.00
1
0.00
1
0.00
1
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CBMVpermissivetwo views0.57
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0.22
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1.61
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0.00
1
0.00
1
0.84
44
0.78
79
2.58
82
0.61
46
0.38
62
0.00
1
1.25
63
0.63
65
2.07
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0.38
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0.00
1
0.00
1
0.00
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0.00
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DANettwo views0.58
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0.19
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1.87
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0.26
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0.06
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0.51
17
0.11
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1.41
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0.52
22
0.22
56
0.06
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1.06
59
0.02
14
4.25
56
0.92
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0.00
1
0.00
1
0.00
1
0.00
1
0.02
20
0.06
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Anonymous Stereotwo views0.59
47
0.78
82
2.67
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0.00
1
0.00
1
0.55
20
0.49
72
1.05
40
0.28
16
0.00
1
0.01
37
0.12
10
0.02
14
5.54
72
0.27
33
0.00
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0.00
1
0.00
1
0.00
1
0.07
46
0.00
1
NOSS_ROBtwo views0.61
48
0.17
14
0.63
1
0.19
83
0.00
1
0.67
32
0.00
1
2.38
79
0.57
31
0.13
51
0.00
1
0.94
53
0.00
1
6.27
84
0.10
20
0.00
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0.00
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0.00
1
0.00
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0.04
32
0.10
77
PWC_ROBbinarytwo views0.62
49
0.54
54
3.22
66
0.00
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0.00
1
0.22
4
0.00
1
2.18
76
0.61
46
0.00
1
0.20
61
0.29
25
0.03
24
3.46
46
1.22
55
0.00
1
0.00
1
0.00
1
0.00
1
0.39
93
0.01
21
HSMtwo views0.63
50
0.36
32
0.89
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0.00
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0.00
1
0.52
19
0.01
39
0.98
38
0.56
27
0.00
1
0.01
37
2.27
78
0.65
66
6.18
81
0.11
21
0.00
1
0.00
1
0.00
1
0.00
1
0.01
10
0.00
1
XQCtwo views0.68
51
0.72
78
3.82
75
0.06
68
0.00
1
0.39
10
0.01
39
1.92
70
0.61
46
0.03
37
0.01
37
0.46
40
0.21
52
2.84
37
2.26
66
0.00
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0.00
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0.00
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70
0.05
60
RTSCtwo views0.70
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0.71
76
3.19
65
0.01
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0.00
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0.20
3
0.00
1
0.81
31
0.60
45
0.29
58
0.36
63
0.36
34
0.04
31
2.04
23
4.87
78
0.00
1
0.03
81
0.00
1
0.02
82
0.28
87
0.11
78
PVDtwo views0.73
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0.57
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3.38
70
0.04
62
0.19
86
0.74
36
0.00
1
0.29
6
0.79
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2.37
79
0.00
1
0.53
44
0.09
41
2.19
28
3.20
72
0.00
1
0.05
87
0.00
1
0.02
82
0.08
50
0.15
86
AANet_RVCtwo views0.75
54
0.65
69
2.52
55
0.01
47
0.00
1
0.66
31
0.00
1
0.61
19
0.13
5
0.00
1
1.29
76
0.96
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0.04
31
5.98
80
1.82
62
0.13
90
0.02
78
0.00
1
0.00
1
0.07
46
0.04
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NaN_ROBtwo views0.80
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0.47
43
1.63
29
0.17
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0.19
86
0.58
22
0.38
70
2.11
73
0.80
72
0.53
63
0.33
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0.48
41
1.13
74
4.98
63
1.94
63
0.00
1
0.02
78
0.01
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0.05
88
0.06
42
0.14
85
FBW_ROBtwo views0.83
56
0.31
21
1.48
23
0.10
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0.01
48
0.62
28
0.01
39
1.91
69
0.59
43
0.01
22
0.01
37
1.10
61
0.05
37
7.84
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2.07
65
0.05
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0.01
75
0.03
88
0.01
76
0.01
10
0.47
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SGM-Foresttwo views0.84
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0.07
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0.90
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0.02
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0.07
76
1.10
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0.68
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2.12
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0.61
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1.14
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0.78
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1.36
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0.98
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Johannes L. Schönberger, Sudipta Sinha, Marc Pollefeys: Learning to Fuse Proposals from Multiple Scanline Optimizations in Semi-Global Matching. ECCV 2018
CBMV_ROBtwo views0.84
57
0.06
3
1.73
33
0.00
1
0.00
1
1.37
70
0.47
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2.57
81
0.58
39
2.13
77
0.76
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1.06
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1.38
76
4.04
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0.54
45
0.00
1
0.00
1
0.00
1
0.00
1
0.03
28
0.05
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SPS-STEREOcopylefttwo views0.88
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0.40
37
2.01
41
0.00
1
0.01
48
0.42
13
0.17
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0.50
15
0.61
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2.19
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0.79
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2.04
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0.27
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ADCReftwo views0.92
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0.48
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3.35
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0.02
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0.90
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0.32
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0.61
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0.65
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0.72
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0.17
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0.17
14
0.82
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2.15
26
7.95
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0.00
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0.00
1
0.00
1
0.00
1
0.07
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0.03
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PWCDC_ROBbinarytwo views0.94
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0.91
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2.52
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0.00
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0.00
1
1.15
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0.00
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1.18
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0.35
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0.09
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0.64
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0.40
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0.00
1
0.00
1
0.00
1
0.00
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0.50
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SAMSARAtwo views1.01
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0.70
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3.29
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0.20
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0.06
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1.65
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0.05
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0.48
14
0.53
24
2.91
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0.68
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2.97
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1.08
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3.89
52
1.54
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0.00
1
0.04
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0.00
1
0.02
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0.05
36
0.03
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CSANtwo views1.05
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0.61
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2.46
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0.09
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0.08
78
0.71
35
0.71
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2.20
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0.93
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0.85
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2.92
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0.79
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1.46
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5.37
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1.58
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0.01
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0.01
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0.00
1
0.00
1
0.09
53
0.05
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NVStereoNet_ROBtwo views1.08
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0.39
35
2.15
49
0.08
70
0.02
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0.45
15
0.02
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0.89
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0.67
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0.10
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5.85
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1.90
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1.11
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Nikolai Smolyanskiy, Alexey Kamenev, Stan Birchfield: On the Importance of Stereo for Accurate Depth Estimation: An Efficient Semi-Supervised Deep Neural Network Approach. Arxiv
DispFullNettwo views1.20
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3.58
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1.00
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0.82
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0.41
11
0.00
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1.44
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0.61
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2.55
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0.64
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1.10
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8.95
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0.84
11
1.22
55
0.00
1
0.02
78
0.00
1
0.00
1
0.24
83
0.02
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DPSNettwo views1.25
66
0.28
20
5.34
82
0.28
88
0.07
76
1.50
71
0.00
1
3.53
88
0.69
67
0.03
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0.00
1
0.45
39
2.10
81
5.67
75
4.61
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0.02
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0.04
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0.00
1
0.02
82
0.23
82
0.09
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DeepPrunerFtwo views1.33
67
0.59
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8.62
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0.02
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0.09
79
0.90
48
0.00
1
1.34
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6.72
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0.22
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0.01
37
0.21
19
0.14
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5.64
74
1.99
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0.00
1
0.00
1
0.01
79
0.02
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0.14
68
0.02
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ADCP+two views1.36
68
0.76
81
6.73
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0.01
47
0.02
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1.32
69
0.80
80
0.81
31
0.72
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0.01
22
0.01
37
0.96
54
1.05
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0.33
9
13.50
94
0.00
1
0.00
1
0.00
1
0.00
1
0.06
42
0.02
35
ADCMidtwo views1.38
69
0.90
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6.15
84
0.04
62
0.03
65
1.67
76
0.18
64
1.13
48
0.93
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0.89
67
0.58
66
0.86
52
0.71
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1.03
12
11.96
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0.01
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0.00
1
0.29
96
0.08
91
0.17
76
0.03
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AnyNet_C32two views1.44
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1.47
90
6.09
83
0.12
76
0.19
86
1.74
77
1.11
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0.84
33
0.56
27
1.30
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0.46
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0.21
19
0.59
63
2.74
36
11.09
87
0.02
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0.00
1
0.06
90
0.00
1
0.16
73
0.05
60
ADCPNettwo views1.44
70
0.55
59
7.88
88
0.01
47
0.19
86
2.78
82
0.27
66
0.90
35
0.38
17
0.04
43
0.02
52
1.43
70
1.81
80
2.22
29
9.08
82
0.00
1
0.47
95
0.00
1
0.64
96
0.04
32
0.15
86
ADCLtwo views1.52
72
0.44
39
4.70
79
0.07
69
0.03
65
2.21
79
2.35
87
0.92
36
0.80
72
1.57
75
1.11
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1.25
63
1.55
78
1.77
20
11.53
88
0.01
79
0.00
1
0.00
1
0.00
1
0.10
57
0.01
21
MDST_ROBtwo views1.54
73
0.06
3
3.42
71
0.14
77
0.16
81
5.42
92
0.32
68
4.33
91
0.61
46
6.08
88
1.25
75
1.04
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1.16
75
5.81
78
0.83
50
0.00
1
0.00
1
0.00
1
0.00
1
0.01
10
0.11
78
SGM_RVCbinarytwo views1.54
73
0.35
29
1.60
27
0.15
78
0.17
83
1.25
68
0.77
78
1.97
72
0.88
74
4.31
84
2.46
78
4.36
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2.37
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6.98
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1.78
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0.21
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0.23
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0.20
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0.23
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0.26
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0.31
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Heiko Hirschmueller: Stereo processing by semiglobal matching and mutual information. TPAMI 2008, Volume 30(2), pp. 328-341
ADCStwo views1.72
75
1.22
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8.11
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0.00
1
0.01
48
0.88
46
0.68
75
1.44
59
0.63
63
2.60
81
0.11
57
1.42
69
0.26
55
1.97
22
14.92
96
0.00
1
0.00
1
0.00
1
0.00
1
0.08
50
0.07
70
SANettwo views1.99
76
0.71
76
3.37
69
0.03
58
0.03
65
2.85
83
0.85
81
2.42
80
8.33
95
1.55
74
4.13
81
4.29
82
3.23
84
5.39
68
2.47
68
0.00
1
0.00
1
0.00
1
0.00
1
0.06
42
0.06
66
WCMA_ROBtwo views2.01
77
0.34
24
1.89
37
0.04
62
0.00
1
1.07
61
0.60
73
1.09
44
1.21
80
5.12
86
9.87
92
8.09
90
4.48
86
3.74
50
2.55
69
0.00
1
0.00
1
0.01
79
0.00
1
0.02
20
0.13
83
MSMD_ROBtwo views2.04
78
0.40
37
2.13
48
0.00
1
0.00
1
4.88
91
0.22
65
0.93
37
1.82
86
5.71
87
7.79
88
7.39
89
3.72
85
4.62
58
1.22
55
0.00
1
0.00
1
0.00
1
0.00
1
0.00
1
0.02
35
pmcnntwo views2.10
79
0.59
64
4.52
78
0.27
87
0.86
93
0.34
9
0.29
67
1.69
67
0.75
70
0.36
60
7.50
87
14.39
96
0.56
62
4.90
61
4.69
77
0.00
1
0.00
1
0.00
1
0.00
1
0.16
73
0.04
56
Abc-Nettwo views2.21
80
0.84
83
4.83
80
0.09
71
0.00
1
4.19
90
4.09
90
6.19
93
1.76
85
0.95
68
1.86
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5.20
84
4.77
87
6.26
83
2.72
70
0.00
1
0.00
1
0.00
1
0.00
1
0.31
91
0.22
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AnyNet_C01two views2.33
81
2.14
95
18.59
95
0.15
78
0.18
84
2.43
81
2.34
86
1.29
52
1.24
81
1.03
69
0.83
73
1.25
63
0.78
68
3.75
51
10.06
84
0.05
88
0.00
1
0.07
92
0.00
1
0.30
90
0.12
81
SGM+DAISYtwo views2.38
82
0.98
87
4.37
77
0.48
89
0.33
90
2.24
80
1.94
85
1.16
49
1.47
83
6.62
89
5.89
84
5.77
86
5.09
88
5.76
77
4.39
75
0.16
91
0.15
92
0.06
90
0.14
92
0.26
85
0.40
92
PWCKtwo views2.44
83
1.65
91
7.31
87
0.22
85
0.02
55
3.12
84
4.74
93
3.06
85
3.48
89
0.72
64
4.42
82
3.40
80
1.67
79
9.06
91
3.36
73
0.39
95
0.01
75
0.00
1
0.00
1
2.19
96
0.08
71
MeshStereopermissivetwo views2.61
84
0.65
69
2.71
59
0.02
53
0.02
55
1.55
73
0.94
82
3.02
84
1.29
82
11.21
92
7.34
86
11.54
93
2.74
83
6.34
85
2.43
67
0.00
1
0.00
1
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1
0.00
1
0.28
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0.03
45
C. Zhang, Z. Li, Y. Cheng, R. Cai, H. Chao, Y. Rui: MeshStereo: A Global Stereo Model with Mesh Alignment Regularization for View Interpolation. ICCV 2015
ELAScopylefttwo views2.75
85
0.35
29
2.67
57
0.05
65
0.04
69
6.72
93
1.83
84
2.84
83
3.38
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8.25
91
9.14
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3.95
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6.15
89
3.73
49
5.70
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0.00
1
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0.01
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0.01
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0.10
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0.08
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ELAS_RVCcopylefttwo views2.84
86
0.34
24
3.86
76
0.05
65
0.05
71
1.52
72
5.02
94
1.93
71
5.28
90
7.10
90
6.96
85
6.26
88
8.34
91
4.96
62
4.90
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0.00
1
0.04
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0.01
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0.01
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0.10
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0.09
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Nwc_Nettwo views2.87
87
0.63
67
5.17
81
0.00
1
0.04
69
3.84
87
4.22
91
8.06
94
0.93
75
0.37
61
0.44
64
5.87
87
6.66
90
7.87
90
12.93
91
0.00
1
0.00
1
0.00
1
0.00
1
0.24
83
0.12
81
FC-DCNNcopylefttwo views3.42
88
0.11
9
2.03
42
0.00
1
0.00
1
3.18
85
0.60
73
3.13
86
2.98
87
11.40
93
12.28
93
13.93
94
8.68
92
5.70
76
4.27
74
0.00
1
0.00
1
0.00
1
0.00
1
0.01
10
0.06
66
RTStwo views4.10
89
1.68
92
43.40
96
0.09
71
0.02
55
3.95
88
0.00
1
1.61
64
0.61
46
1.09
70
0.01
37
1.97
75
0.22
53
16.87
93
10.15
85
0.00
1
0.09
89
0.00
1
0.00
1
0.20
78
0.05
60
RTSAtwo views4.10
89
1.68
92
43.40
96
0.09
71
0.02
55
3.95
88
0.00
1
1.61
64
0.61
46
1.09
70
0.01
37
1.97
75
0.22
53
16.87
93
10.15
85
0.00
1
0.09
89
0.00
1
0.00
1
0.20
78
0.05
60
LSMtwo views4.58
91
0.88
84
17.79
94
3.73
97
38.79
98
0.85
45
2.37
88
0.54
16
1.64
84
2.88
82
3.09
80
0.62
45
0.60
64
3.16
42
1.06
52
0.00
1
0.00
1
0.00
1
0.00
1
0.12
63
13.55
98
MADNet+two views4.65
92
2.70
96
46.68
98
0.01
47
0.02
55
2.06
78
0.03
58
3.17
87
1.07
78
0.02
31
0.01
37
1.84
73
0.31
58
21.62
97
13.04
92
0.00
1
0.03
81
0.00
1
0.00
1
0.20
78
0.19
88
edge stereotwo views7.09
93
3.32
97
14.31
93
0.96
92
1.13
94
26.20
98
16.27
98
13.37
97
6.61
92
4.33
85
17.00
95
5.35
85
12.69
95
7.34
88
9.08
82
0.61
96
0.19
93
0.02
85
0.04
87
1.40
95
1.58
95
DPSimNet_ROBtwo views7.90
94
5.46
98
13.55
92
3.66
96
5.16
97
7.26
94
9.60
97
6.11
92
7.46
94
13.33
94
9.50
91
11.03
91
11.89
94
10.08
92
12.35
90
4.36
97
5.55
97
5.35
98
5.34
98
4.96
97
5.98
97
SGM-ForestMtwo views8.89
95
0.68
72
3.61
73
0.57
91
0.18
84
14.89
97
5.99
95
9.62
96
10.59
96
20.43
96
17.16
96
39.22
98
20.29
97
20.63
96
13.19
93
0.04
86
0.14
91
0.00
1
0.07
89
0.15
70
0.36
91
MADNet++two views9.87
96
2.12
94
7.11
86
7.99
98
4.58
96
14.38
96
6.90
96
9.23
95
5.88
91
16.88
95
17.47
97
11.07
92
15.72
96
24.26
98
19.76
97
8.52
98
6.39
98
4.85
97
2.69
97
5.96
98
5.73
96
LE_ROBtwo views9.96
97
0.54
54
9.62
91
1.40
95
1.24
95
3.29
86
4.64
92
4.31
90
43.01
98
51.54
98
13.34
94
14.15
95
24.60
99
6.66
86
20.28
98
0.04
86
0.05
87
0.12
94
0.20
93
0.07
46
0.09
74
MANEtwo views9.96
97
0.69
73
2.88
61
1.22
94
0.61
91
13.15
95
3.46
89
15.62
98
22.27
97
22.74
97
30.00
98
29.74
97
23.22
98
17.17
95
13.78
95
0.29
94
0.56
96
0.09
93
0.61
95
0.15
70
1.00
94
DGTPSM_ROBtwo views81.49
99
60.74
99
99.95
101
61.20
99
86.99
101
99.11
101
100.00
101
95.92
100
99.99
101
73.08
99
100.00
100
70.81
99
100.00
101
77.39
99
99.98
101
35.10
99
97.48
102
35.12
99
99.89
102
46.16
99
90.85
99
DPSMNet_ROBtwo views81.54
100
60.77
100
99.95
101
61.42
100
87.05
102
99.11
101
100.00
101
95.93
101
99.99
101
73.11
100
100.00
100
70.84
100
100.00
101
77.43
100
99.98
101
35.39
100
97.54
103
35.21
100
99.89
102
46.30
100
90.94
100
MEDIAN_ROBtwo views93.37
101
98.75
103
96.05
100
90.90
103
90.53
103
85.63
99
76.45
99
92.03
99
89.53
99
95.05
101
94.99
99
96.02
101
93.85
100
90.36
101
87.21
99
98.36
104
95.79
99
99.61
103
98.77
101
98.80
104
98.72
104
DPSMtwo views94.00
102
79.32
101
100.00
103
83.19
101
85.69
99
100.00
103
100.00
101
100.00
102
100.00
103
100.00
102
100.00
100
100.00
102
100.00
101
100.00
103
100.00
103
89.53
101
97.42
100
74.97
101
95.13
99
83.79
101
90.98
101
DPSM_ROBtwo views94.00
102
79.32
101
100.00
103
83.19
101
85.69
99
100.00
103
100.00
101
100.00
102
100.00
103
100.00
102
100.00
100
100.00
102
100.00
101
100.00
103
100.00
103
89.53
101
97.42
100
74.97
101
95.13
99
83.79
101
90.98
101
AVERAGE_ROBtwo views98.45
104
99.13
104
95.46
99
100.00
105
100.00
105
93.36
100
81.95
100
100.00
102
99.97
100
100.00
102
100.00
100
100.00
102
100.00
101
99.72
102
99.40
100
100.00
105
100.00
105
100.00
104
100.00
104
100.00
105
100.00
105
LSM0two views99.11
105
99.97
105
100.00
103
95.93
104
98.59
104
100.00
103
100.00
101
100.00
102
100.00
103
100.00
102
100.00
100
100.00
102
100.00
101
100.00
103
100.00
103
93.89
103
99.97
104
100.00
104
100.00
104
96.64
103
97.25
103
MSMDNettwo views0.34
59