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Table 7 Comparison of network accuracy (mAP and rank-1) and complexity (M: memory (parameters) and time: T (GFLOPS)) with different pruning compression ratios of different scenarios on all the ReID datasets

From: Exploiting prunability for person re-identification

Datasets

Scenario

M

T

L1

Auto-Balanced

PSFP

 

(compression)

  

mAP

rank-1

mAP

rank-1

mAP

rank-1

Market-1501

1 (C1)

11.90

2.96

67.04

84.71

65.46

83.64

65.92

83.72

 

2 (C1)

11.90

2.96

47.46

69.36

47.57

70.46

65.55

82.69

 

3 (C1)

11.90

2.96

53.22

72.21

54.73

74.05

65.88

82.19

 

1 (C2)

8.95

2.09

63.63

81.95

63.16

81.29

63.58

82.47

 

2 (C2)

8.95

2.09

49.18

70.67

47.36

68.74

65.03

80.85

 

3 (C2)

8.95

2.09

41.93

62.62

48.30

69.00

65.88

82.91

Duke-MTMC

1 (C1)

11.90

2.96

57.51

75.00

56.64

74.64

56.96

74.66

 

2 (C1)

11.90

2.96

40.60

59.47

41.09

61.09

53.71

71.90

 

3 (C1)

11.90

2.96

46.88

65.93

45.54

66.16

56.62

74.09

 

1 (C2)

8.95

2.09

55.35

74.69

55.10

72.94

55.22

73.57

 

2 (C2)

8.95

2.09

40.91

61.67

43.19

64.14

53.05

73.20

 

3 (C2)

8.95

2.09

39.17

58.71

34.80

54.58

56.77

73.38

CUHK03-NP

1 (C1)

11.90

2.96

44.08

46.50

41.85

44.21

42.38

45.58

 

2 (C1)

11.90

2.96

27.23

28.43

27.44

29.57

40.47

45.00

 

3 (C1)

11.90

2.96

33.57

36.07

33.34

35.29

40.66

44.57

 

1 (C2)

8.95

2.09

37.83

39.71

38.51

40.57

38.76

40.52

 

2 (C2)

8.95

2.09

26.29

27.36

26.69

27.36

42.19

43.86

 

3 (C2)

8.95

2.09

26.79

28.29

26.50

27.14

40.31

40.14