Table 2 Pose Estimation results of different models on YCB-video dataset.

From: Enhanced RGB-D feature extraction for 6D pose estimation

Object

PoseCNN

DenseFusion

PVN3D

FFB6D

Ours

A

S

A

S

A

S

A

S

A

S

Master_chef_can

83.9

50.2

95.3

70.7

96.0

80.5

96.3

80.6

97.5

83.6

Craker_box

76.9

53.1

92.5

86.9

96.1

94.8

96.3

94.6

97.7

96.2

Sugar_box

84.2

68.4

95.1

90.8

97.4

96.3

97.6

96.6

98.6

97.8

Tomato_soup_can

81.0

66.2

93.8

84.7

96.2

88.5

95.6

89.6

96.5

90.5

Mustard_bottle

90.4

81.0

95.8

90.9

97.5

96.2

97.8

97.0

98.3

97.9

Tuna_fish_can

88.0

70.7

95.7

79.6

96.0

89.3

96.8

88.9

97.6

92.2

Pudding_box

79.1

62.7

94.3

89.3

97.1

95.7

97.1

94.6

96.4

93.5

Gelatin_box

87.2

75.2

97.2

95.8

97.7

96.1

98.1

96.9

98.9

96.0

Potted_meat_can

78.5

59.5

89.3

79.6

93.3

88.6

94.7

88.1

94.0

91.4

Banana

86.0

72.3

90.0

76.7

96.6

93.7

97.2

94.9

97.9

94.7

Picher_base

77.0

53.3

93.6

87.1

97.4

96.5

97.6

96.9

97.8

97.3

Bleach_cleanser

71.6

50.3

94.4

87.5

96.0

93.2

96.8

94.8

97.0

94.4

Bowl

69.6

69.6

86.0

86.0

90.2

90.2

96.3

96.3

96.7

95.8

Mug

78.2

58.5

95.3

83.8

97.6

95.4

97.3

94.2

97.8

95.7

Power_drill

72.7

55.3

92.1

83.7

96.7

95.1

97.2

95.9

97.8

96.4

Wood_block

64.3

64.3

89.5

89.5

90.4

90.4

92.6

92.6

94.3

94.7

Scissors

56.9

35.8

90.1

77.4

96.7

92.7

97.7

95.7

98.3

97.3

Large_marker

71.7

58.3

95.1

89.1

96.7

91.8

96.6

89.1

97.6

91.3

Large_clamp

50.2

50.2

71.5

71.5

93.6

93.6

96.8

96.8

97.1

97.3

Extra_clamp

44.1

44.1

70.2

70.2

88.4

88.4

96.0

96.0

96.2

96.1

Foam_brick

88.0

88.0

92.2

92.2

96.8

96.8

97.3

97.3

97.9

97.6

Average

75.8

59.9

91.2

82.9

95.5

91.8

96.6

92.7

97.2

94.7

  1. 1“A” represents the ADD given by formula (8).
  2. 2“S” represents the ADD-S given by formula (9).