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This version is not peer-reviewed
Method | Publication | ModelNet40 | Extra Training Data | Deep | |
---|---|---|---|---|---|
OA(%) | mAcc(%) | ||||
PointNet [8] | CVPR 2017 | 89.2 | 86.0 | × | × |
PointNet++ [9] | NeurIPS 2017 | 90.7 | 88.4 | × | × |
PointCNN [10] | NeurIPS 2018 | 92.5 | 88.1 | × | × |
RS-CNN [11] | CVPR 2019 | 92.9 | - | × | × |
PointConv [12] | CVPR 2019 | 92.5 | - | × | × |
DeepGCN [13] | PAMI 2019 | 93.6 | 90.9 | × | √ |
PointASNL [45] | CVPR 2020 | 93.2 | - | × | × |
CurveNet [46] | ICCV 2021 | 93.8 | - | × | × |
Point-BERT [15] | CVPR 2022 | 93.8 | - | √ | × |
PointNorm [17] | CVPR 2022 | 93.7 | 91.3 | × | √ |
PointMLP [18] | ICLR 2022 | 93.7 | 90.9 | × | √ |
PointNeXT [19] | NeurIPS 2022 | 94.4 | 91.1 | × | √ |
RepSurf-U [36] | CVPR 2022 | 94.4 | 91.4 | × | × |
Point-MAE [47] | CVPR 2022 | 94.0 | - | √ | × |
P2P [48] | CVPR 2022 | 94.0 | 91.6 | √ | √ |
Point-PN [49] | CVPR 2023 | 93.8 | - | × | × |
PointConT [50] | IEEE 2023 | 93.5 | - | × | × |
APES [51] | CVPR 2023 | 93.5 | - | × | × |
Point-MDA | 2023 | 94.0 | 91.9 | × | × |
Method | Publication | ScanObjectNN | Extra Training Data | Deep | |
---|---|---|---|---|---|
OA(%) | mAcc(%) | ||||
PointNet [8] | CVPR 2017 | 68.2 | 63.4 | × | × |
PointNet++ [9] PointCNN [10] |
NeurIPS 2017 NeurIPS 2018 |
77.9 78.5 |
75.4 75.1 |
× × |
× × |
DGCNN [34] SpiderCNN [52] DRNet [53] PRA-Net [54] |
ELSEVIER 2018 ECCV 2018 WACV 2021 IEEE 2021 |
78.1 73.7 80.3 82.1 |
73.6 69.8 78.0 79.1 |
× × × × |
× × × × |
Point-BERT [15] PointNorm [17] PointMLP [18] PointNeXt [19] RepSurf-U [36] |
CVPR 2022 CVPR 2022 ICLR 2022 NeurIPS 2022 CVPR 2022 |
83.1 86.8 85.4 88.2 84.6 |
- 85.6 83.9 86.8 81.9 |
√ × × × × |
× √ √ √ × |
Point-MAE [47] | CVPR 2022 | 85.2 | - | √ | × |
P2P [48] | CVPR 2022 | 89.3 | 88.5 | √ | × |
Point-PN [49] PointConT [50] |
CVPR 2023 IEEE 2023 |
87.1 88.0 |
- 86.0 |
× × |
× × |
Point-MDA | 2023 | 85.8 | 83.6 | × | × |
Dataset | Activation Frequency Level | OA(%) | mAcc(%) |
---|---|---|---|
ModelNet40 | L1=1,L2=5,L3=9 | 93.7 | 91.4 |
L1=2,L2=6,L3=10 | 94.0 | 91.9 | |
L1=3,L2=7,L3=11 L1=4,L2=8,L3=12 |
93.9 93.7 |
91.7 91.3 |
|
ScanObjectNN | L1=1,L2=5,L3=9 | 85.4 | 82.9 |
L1=2,L2=6,L3=10 | 85.7 | 83.2 | |
L1=3,L2=7,L3=11 | 85.8 | 83.6 | |
L1=4,L2=8,L3=12 | 85.4 | 83.3 |
Dataset | DA | ResDMLP | Reuse | OA(%) | mAcc(%) |
---|---|---|---|---|---|
ModelNet40 | √ | √ | √ | 94.0 | 91.9 |
√ | × | √ | 93.7 | 91.4 | |
× × |
√ √ |
× √ |
93.7 93.6 |
91.2 91.2 |
|
ScanObjectNN | √ | √ | √ | 85.8 | 83.6 |
√ | × | √ | 84.7 | 82.8 | |
× | √ | × | 85.3 | 83.2 | |
× | √ | √ | 84.8 | 82.8 |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
Submitted:
03 May 2023
Posted:
06 May 2023
You are already at the latest version
This version is not peer-reviewed
Submitted:
03 May 2023
Posted:
06 May 2023
You are already at the latest version
Method | Publication | ModelNet40 | Extra Training Data | Deep | |
---|---|---|---|---|---|
OA(%) | mAcc(%) | ||||
PointNet [8] | CVPR 2017 | 89.2 | 86.0 | × | × |
PointNet++ [9] | NeurIPS 2017 | 90.7 | 88.4 | × | × |
PointCNN [10] | NeurIPS 2018 | 92.5 | 88.1 | × | × |
RS-CNN [11] | CVPR 2019 | 92.9 | - | × | × |
PointConv [12] | CVPR 2019 | 92.5 | - | × | × |
DeepGCN [13] | PAMI 2019 | 93.6 | 90.9 | × | √ |
PointASNL [45] | CVPR 2020 | 93.2 | - | × | × |
CurveNet [46] | ICCV 2021 | 93.8 | - | × | × |
Point-BERT [15] | CVPR 2022 | 93.8 | - | √ | × |
PointNorm [17] | CVPR 2022 | 93.7 | 91.3 | × | √ |
PointMLP [18] | ICLR 2022 | 93.7 | 90.9 | × | √ |
PointNeXT [19] | NeurIPS 2022 | 94.4 | 91.1 | × | √ |
RepSurf-U [36] | CVPR 2022 | 94.4 | 91.4 | × | × |
Point-MAE [47] | CVPR 2022 | 94.0 | - | √ | × |
P2P [48] | CVPR 2022 | 94.0 | 91.6 | √ | √ |
Point-PN [49] | CVPR 2023 | 93.8 | - | × | × |
PointConT [50] | IEEE 2023 | 93.5 | - | × | × |
APES [51] | CVPR 2023 | 93.5 | - | × | × |
Point-MDA | 2023 | 94.0 | 91.9 | × | × |
Method | Publication | ScanObjectNN | Extra Training Data | Deep | |
---|---|---|---|---|---|
OA(%) | mAcc(%) | ||||
PointNet [8] | CVPR 2017 | 68.2 | 63.4 | × | × |
PointNet++ [9] PointCNN [10] |
NeurIPS 2017 NeurIPS 2018 |
77.9 78.5 |
75.4 75.1 |
× × |
× × |
DGCNN [34] SpiderCNN [52] DRNet [53] PRA-Net [54] |
ELSEVIER 2018 ECCV 2018 WACV 2021 IEEE 2021 |
78.1 73.7 80.3 82.1 |
73.6 69.8 78.0 79.1 |
× × × × |
× × × × |
Point-BERT [15] PointNorm [17] PointMLP [18] PointNeXt [19] RepSurf-U [36] |
CVPR 2022 CVPR 2022 ICLR 2022 NeurIPS 2022 CVPR 2022 |
83.1 86.8 85.4 88.2 84.6 |
- 85.6 83.9 86.8 81.9 |
√ × × × × |
× √ √ √ × |
Point-MAE [47] | CVPR 2022 | 85.2 | - | √ | × |
P2P [48] | CVPR 2022 | 89.3 | 88.5 | √ | × |
Point-PN [49] PointConT [50] |
CVPR 2023 IEEE 2023 |
87.1 88.0 |
- 86.0 |
× × |
× × |
Point-MDA | 2023 | 85.8 | 83.6 | × | × |
Dataset | Activation Frequency Level | OA(%) | mAcc(%) |
---|---|---|---|
ModelNet40 | L1=1,L2=5,L3=9 | 93.7 | 91.4 |
L1=2,L2=6,L3=10 | 94.0 | 91.9 | |
L1=3,L2=7,L3=11 L1=4,L2=8,L3=12 |
93.9 93.7 |
91.7 91.3 |
|
ScanObjectNN | L1=1,L2=5,L3=9 | 85.4 | 82.9 |
L1=2,L2=6,L3=10 | 85.7 | 83.2 | |
L1=3,L2=7,L3=11 | 85.8 | 83.6 | |
L1=4,L2=8,L3=12 | 85.4 | 83.3 |
Dataset | DA | ResDMLP | Reuse | OA(%) | mAcc(%) |
---|---|---|---|---|---|
ModelNet40 | √ | √ | √ | 94.0 | 91.9 |
√ | × | √ | 93.7 | 91.4 | |
× × |
√ √ |
× √ |
93.7 93.6 |
91.2 91.2 |
|
ScanObjectNN | √ | √ | √ | 85.8 | 83.6 |
√ | × | √ | 84.7 | 82.8 | |
× | √ | × | 85.3 | 83.2 | |
× | √ | √ | 84.8 | 82.8 |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
Fan Wang
et al.
Sensors,
2022
Meng Wu
et al.
Electronics,
2022
Yufeng Yang
et al.
Sensors,
2020
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