Point Cloud Analysis Method Based on Feature Negative Feedback Convolution

Method	Input type	Points	Mean class accuracy /%	Overall accuracy /%
Point-CNN^［40］	coords	1k	88.1	91.7
PointNet^［15］	coords	1k	86.0	89.2
A-SCN^［28］	coords	1k		90.0
Kd-Net^［38］	coords	1k		90.6
PointNet++^［16］	coords	1k		90.7
KCNet^［41］	coords	1k		91.0
Spec-GCN^［42］	coords	1k		91.5
DGCNN^［17］	coords	1k	90.2	92.2
RS-CNN^［18］	coords	1k		93.6
KP-Conv^［43］	coords	1k		92.9
PointASNL^［44］	coords	1k		93.2
Proposed	coords	1k	91.0	93.8
SpiderCNN^［45］	coords + norm	5k		92.4
DensePoint^［46］	coords + norm	1k		93.2
SO-NET^［39］	coords + norm	5k	90.8	93.4
PointNet++^［16］	coords + norm	5k		91.9
DGCNN^［17］	coords	2k	90.7	93.5

Table 2. Part segmentation results [mIou (%)] on ShapeNet Part data set

View table

Table 2. Part segmentation results [mIou (%)] on ShapeNet Part data set

Method	PointNet^［15］	PointNet++^［16］	SpiderCNN^［45］	SO-NET^［39］	A-SCN^［28］	P2Sequence^［48］	PCNN^［49］	DGCNN^［17］	RS-CNN^［18］	PointASNL^［44］	Proposed
Overall mIou	83.7	85.1	85.3	84.6	84.6	85.2	85.1	85.2	86.2	86.1	86.4
Air plane	83.4	82.4	83.5	81.9	83.8	82.6	82.4	84.0	83.5	84.1	84.3
Bag	78.7	79.0	81.0	83.5	80.8	81.8	80.1	83.4	84.8	84.7	85.1
Cap	82.5	87.7	87.2	84.8	83.5	87.5	85.5	86.7	88.8	87.9	88.6
Car	74.9	77.3	77.5	78.1	79.3	77.3	79.5	77.8	79.6	79.7	79.9
Chair	89.6	90.8	90.7	90.8	90.5	90.8	90.8	90.6	91.2	92.2	91.3
Ear phone	73.0	71.8	76.8	72.2	69.8	77.1	73.2	74.7	81.1	73.7	79.2
Guitar	91.5	91.0	91.1	90.1	91.7	91.1	91.3	91.2	91.6	91.0	91.8
Knife	85.9	85.9	87.3	83.6	86.5	86.9	86.0	87.5	88.4	87.2	89.0
Lamp	80.8	83.7	83.3	82.3	82.9	83.9	85.0	82.8	86.0	84.2	85.2
Laptop	95.3	95.3	95.8	95.2	96.0	95.7	95.7	95.7	96.0	95.8	95.7
Motobike	65.2	71.6	70.2	69.3	69.2	70.8	73.2	66.3	73.7	74.4	72.3
Mug	93.0	94.1	93.5	94.2	93.8	94.6	94.8	94.9	94.1	95.2	94.5
Pistol	81.2	81.3	82.7	80.0	82.5	79.3	83.3	81.1	83.4	81.0	82.0
Rocket	57.9	58.7	59.7	51.6	62.9	58.1	51.0	63.5	60.5	63.0	60.3
Skate board	72.8	76.4	75.8	72.1	74.4	75.2	75.0	74.5	77.7	76.3	76.4
Table	80.6	82.6	82.8	82.6	80.8	82.8	81.8	82.6	83.6	83.2	84.4

Table 3. Ablation experiments about effects of different network components on ShapeNet part data set
View table
Table 3. Ablation experiments about effects of different network components on ShapeNet part data set
Model SAKNN Attentive pooling Feature negative feedback convolution Global context reasoning module Overall mIou /%
0 84.9
1 √ 85.2
2 √ √ 85.4
3 √ √ √ 85.8
4 √ √ √ √ 86.1

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Lintao Deng, Zhijun Fang. Point Cloud Analysis Method Based on Feature Negative Feedback Convolution[J]. Laser & Optoelectronics Progress, 2022, 59(12): 1210006

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