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Advances in Multimedia
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2017
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Article
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Tab 6
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Research Article
Deep Learning for Person Reidentification Using Support Vector Machines
Table 6
Comparison of some other state-of-the-art results reported with VIPeR database. The cumulative matching scores (%) at ranks 1, 5, 10, and 20 are listed.
Method
VIPeR
Top 1
Top 5
Top 10
Top 20
L2-norm
10.89
22.37
32.34
45.19
L1-norm
12.15
26.01
32.09
34.72
aPRDC
16.14
37.72
50.98
65.95
RankSVM
14.00
37.00
51.00
67.00
SSCDL
25.60
54.15
68.10
83.60
eSCD
26.31
46.61
58.86
72.77
PCCA
19.62
51.55
68.23
82.92
rPCCA
21.96
54.78
70.95
85.29
SVMML
30.07
63.17
77.44
88.08
MFA
32.24
65.99
79.66
90.64
KLFDA
32.33
65.78
79.72
90.95
Ours
34.15
67.86
80.95
90.63