| ULIP + PointNet++(ssg) |
- Overall Accuracy
- 93.4
- Mean Accuracy
- 91.2
|
ULIP: Learning a Unified Representation of Language, Images, and Point Clouds for 3D Understanding 2022-12-10 |
코드 1 |
| PointCutmix |
- Overall Accuracy
- 93.4
|
PointCutMix: Regularization Strategy for Point Cloud Classification 2021-01-05 |
코드 1 · 코드 2 |
| 3DMedPT |
- Overall Accuracy
- 93.4
- Number of params
- 1.54M
|
3D Medical Point Transformer: Introducing Convolution to Attention Networks for Medical Point Cloud Analysis 2021-12-09 |
코드 1 |
| DGCNN + MD |
- Overall Accuracy
- 93.39
- Mean Accuracy
- 89.88
|
Self-supervised Point Cloud Representation Learning via Separating Mixed Shapes 2021-09-01 |
코드 1 |
| OGNet + MD |
- Overall Accuracy
- 93.31
- Mean Accuracy
- 90.71
|
Self-supervised Point Cloud Representation Learning via Separating Mixed Shapes 2021-09-01 |
코드 1 |
| OG-Net-Small |
- Overall Accuracy
- 93.3
- Mean Accuracy
- 90.5
- Number of params
- 1.22M
|
Parameter-Efficient Person Re-identification in the 3D Space 2020-06-08 |
코드 1 |
| PointStack |
- Overall Accuracy
- 93.3
- Mean Accuracy
- 89.6
|
Advanced Feature Learning on Point Clouds using Multi-resolution Features and Learnable Pooling 2022-05-20 |
코드 1 · 코드 2 |
| PointNet++ + SageMix |
- Overall Accuracy
- 93.3
|
SageMix: Saliency-Guided Mixup for Point Clouds 2022-10-13 |
코드 1 |
| PointASNL |
- Overall Accuracy
- 93.2
|
PointASNL: Robust Point Clouds Processing using Nonlocal Neural Networks with Adaptive Sampling 2020-03-01 |
코드 1 |
| Point Cloud Transformer |
- Overall Accuracy
- 93.2
- Number of params
- 2.88M
|
PCT: Point cloud transformer 2020-12-17 |
코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5 · 코드 6 · 코드 7 · 코드 8 · 코드 9 · 코드 10 · 코드 11 |
| DRNet |
- Overall Accuracy
- 93.1
|
Dense-Resolution Network for Point Cloud Classification and Segmentation 2020-05-14 |
코드 1 |
| ShellNet |
- Overall Accuracy
- 93.1
|
ShellNet: Efficient Point Cloud Convolutional Neural Networks using Concentric Shells Statistics 2019-08-17 |
코드 1 |
| STRL + DGCNN |
- Overall Accuracy
- 93.1
|
Spatio-temporal Self-Supervised Representation Learning for 3D Point Clouds 2021-09-01 |
코드 1 |
| PatchAugment+DGCNN |
- Overall Accuracy
- 93.1
|
연결 없음 논문 날짜 미기재 |
연결 없음 |
| AdaCrossNet |
- Overall Accuracy
- 93.1
|
AdaCrossNet: Adaptive Dynamic Loss Weighting for Cross-Modal Contrastive Point Cloud Learning 2025-01-02 |
코드 1 |
| PointManifold |
- Overall Accuracy
- 93.0
- Mean Accuracy
- 90.4
|
PointManifold: Using Manifold Learning for Point Cloud Classification 2020-10-14 |
연결 없음 |
| InterpCNN |
- Overall Accuracy
- 93.0
|
Interpolated Convolutional Networks for 3D Point Cloud Understanding 2019-08-13 |
연결 없음 |
| DGCNN |
- Overall Accuracy
- 92.9
- Mean Accuracy
- 90.2
- Number of params
- 1.81M
|
Dynamic Graph CNN for Learning on Point Clouds 2018-01-24 |
코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5 · 코드 6 · 코드 7 · 코드 8 · 코드 9 · 코드 10 · 코드 11 · 코드 12 · 코드 13 · 코드 14 · 코드 15 · 코드 16 · 코드 17 · 코드 18 · 코드 19 · 코드 20 · 코드 21 |
| KPConv |
- Overall Accuracy
- 92.9
|
KPConv: Flexible and Deformable Convolution for Point Clouds 2019-04-18 |
코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5 · 코드 6 · 코드 7 · 코드 8 · 코드 9 · 코드 10 |
| RS-CNN |
- Overall Accuracy
- 92.9
|
Relation-Shape Convolutional Neural Network for Point Cloud Analysis 2019-04-16 |
코드 1 · 코드 2 · 코드 3 · 코드 4 |
| ASSANet |
- Overall Accuracy
- 92.9
|
ASSANet: An Anisotropic Separable Set Abstraction for Efficient Point Cloud Representation Learning 2021-10-20 |
코드 1 |
| Point-M2AE-SVM |
- Overall Accuracy
- 92.9
|
Point-M2AE: Multi-scale Masked Autoencoders for Hierarchical Point Cloud Pre-training 2022-05-28 |
코드 1 · 코드 2 · 코드 3 |
| Point Transformer |
- Overall Accuracy
- 92.8
|
Point Transformer 2020-11-02 |
코드 1 · 코드 2 |
| A-CNN |
- Overall Accuracy
- 92.6
|
A-CNN: Annularly Convolutional Neural Networks on Point Clouds 2019-04-16 |
코드 1 |
| P2Sequence |
- Overall Accuracy
- 92.6
|
Point2Sequence: Learning the Shape Representation of 3D Point Clouds with an Attention-based Sequence to Sequence Network 2018-11-06 |
연결 없음 |
| Point-TnT |
- Overall Accuracy
- 92.6
- Number of params
- 3.9M
|
Points to Patches: Enabling the Use of Self-Attention for 3D Shape Recognition 2022-04-08 |
코드 1 |
| PointConv |
- Overall Accuracy
- 92.5
|
PointConv: Deep Convolutional Networks on 3D Point Clouds 2018-11-17 |
코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5 · 코드 6 · 코드 7 · 코드 8 · 코드 9 |
| PolyNet |
- Overall Accuracy
- 92.42
|
PolyNet: Polynomial Neural Network for 3D Shape Recognition with PolyShape Representation 2021-10-15 |
코드 1 |
| SpiderCNN |
- Overall Accuracy
- 92.4
|
SpiderCNN: Deep Learning on Point Sets with Parameterized Convolutional Filters 2018-03-30 |
코드 1 |
| PCNN |
- Overall Accuracy
- 92.3
|
Point Convolutional Neural Networks by Extension Operators 2018-03-27 |
코드 1 |