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Table 2 Result scores for all main methods on the test set

From: Object detection for automotive radar point clouds – a comparison

Method

IOU=0.3

IOU=0.5

 

APped

APgrp

APcyc

APcar

APtrk

mAP

mLAMR

F1,pt

F1,obj

APped

APgrp

APcyc

APcar

APtrk

mAP

mLAMR

F1,pt

F1,obj

Metric

DBSCAN/LSTM

22.96

42.95

62.51

65.21

59.07

50.54

53.10

53.06

58.92

22.94

41.07

62.51

63.13

56.36

49.20

54.90

53.08

57.60

DBSCAN/RandomForest

20.67

37.28

53.98

59.63

56.53

45.62

59.68

49.48

52.43

20.60

35.23

53.76

55.91

50.97

43.29

61.58

49.50

51.10

PointNet++/DBSCAN

29.42

53.06

56.37

53.15

26.19

43.64

61.10

54.55

51.67

27.47

47.56

54.85

49.16

21.10

40.03

64.17

54.37

49.24

YOLOv3

28.28

57.51

64.87

75.54

62.18

57.67

48.92

53.04

61.87

26.96

54.88

63.68

67.99

56.31

53.96

52.61

52.86

59.46

PointPillars

15.13

32.28

46.40

61.19

47.48

40.50

65.46

47.62

45.92

14.67

30.42

45.08

54.38

39.87

36.89

68.55

47.70

43.75

PointPillars++

24.69

47.32

55.39

68.72

53.08

49.84

57.01

53.91

55.61

23.93

44.66

53.58

61.33

45.62

45.82

60.36

53.93

53.36

PointNet++/LSTM

27.28

56.28

64.94

68.44

60.21

55.43

50.10

54.13

60.99

27.17

51.70

64.88

63.74

57.00

52.90

52.06

54.12

59.64

  1. For all scores except mLAMR higher means better. The methods are listed in the order of appearance in the text. The best scores are indicated in bold font