Papers with Code 아카이브

3D Point Cloud Classification

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하위 태스크: 4
평가표: 5
보존된 평가 기록: 216

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/AliBahri94/SVWA_TTA

공식 코드

Test-Time Adaptation in Point Clouds: Leveraging Sampling Variation with Weight Averaging

https://github.com/AutodeskAILab/RobustPointSet

공식 코드

RobustPointSet: A Dataset for Benchmarking Robustness of Point Cloud Classifiers

https://github.com/Ayumu-J-S/Point-JEPA

공식 코드

Point-JEPA: A Joint Embedding Predictive Architecture for Self-Supervised Learning on Point Cloud

https://github.com/CGuangyan-BIT/PointGPT

공식 코드

PointGPT: Auto-regressively Generative Pre-training from Point Clouds

https://github.com/CVMI-Lab/PAConv

공식 코드

PAConv: Position Adaptive Convolution with Dynamic Kernel Assembling on Point Clouds

https://github.com/Chenguoz/PointSCNet

공식 코드

PointSCNet: Point Cloud Structure and Correlation Learning Based on Space Filling Curve-Guided Sampling

https://github.com/Daniel-Liu-c0deb0t/Adversarial-point-perturbations-on-3D-objects

공식 코드

Adversarial shape perturbations on 3D point clouds

https://github.com/DylanWusee/pointconv

공식 코드

PointConv: Deep Convolutional Networks on 3D Point Clouds

https://github.com/EricDai0/3DASC

공식 코드

Transferable 3D Adversarial Shape Completion using Diffusion Models

https://github.com/HaochengWan/PVT

공식 코드

PVT: Point-Voxel Transformer for Point Cloud Learning

https://github.com/HuguesTHOMAS/KPConv

공식 코드

KPConv: Flexible and Deformable Convolution for Point Clouds

https://github.com/JunweiZheng93/APES

공식 코드

Attention-based Point Cloud Edge Sampling

https://github.com/KaidongLi/pytorch-LatticePointClassifier

공식 코드

Robust Structured Declarative Classifiers for 3D Point Clouds: Defending Adversarial Attacks with Implicit Gradients

https://github.com/KangchengLiu/Feature-Geometric-Net-FG-Net

공식 코드

FG-Net: Fast Large-Scale LiDAR Point Clouds Understanding Network Leveraging Correlated Feature Mining and Geometric-Aware Modelling

https://github.com/LifeBeyondExpectations/PointMixer

공식 코드

PointMixer: MLP-Mixer for Point Cloud Understanding

https://github.com/LongerVision/PointStack

공식 코드

Advanced Feature Learning on Point Clouds using Multi-resolution Features and Learnable Pooling

https://github.com/MenghaoGuo/PCT

공식 코드

PCT: Point cloud transformer

https://github.com/Microsoft/O-CNN

공식 코드

O-CNN: Octree-based Convolutional Neural Networks for 3D Shape Analysis

https://github.com/MingyeXu/GS-Net

공식 코드

Geometry Sharing Network for 3D Point Cloud Classification and Segmentation

https://github.com/Pang-Yatian/Point-MAE

공식 코드

Masked Autoencoders for Point Cloud Self-supervised Learning

https://github.com/Pointcept/PointTransformerV2

공식 코드

Point Transformer V2: Grouped Vector Attention and Partition-based Pooling

https://github.com/Pointcept/Pointcept

공식 코드

Point Transformer

https://github.com/RFLeijenaar/AsymDSD

공식 코드

Asymmetric Dual Self-Distillation for 3D Self-Supervised Representation Learning

https://github.com/RosettaWYzhang/AdaPC

공식 코드

On Automatic Data Augmentation for 3D Point Cloud Classification

https://github.com/ShiQiu0419/DRNet

공식 코드

Dense-Resolution Network for Point Cloud Classification and Segmentation

https://github.com/ShiQiu0419/GBNet

공식 코드

Geometric Back-projection Network for Point Cloud Classification

https://github.com/ShunChengWu/3DSSG

공식 코드

SceneGraphFusion: Incremental 3D Scene Graph Prediction from RGB-D Sequences

https://github.com/ShunChengWu/SceneGraphFusion

공식 코드

SceneGraphFusion: Incremental 3D Scene Graph Prediction from RGB-D Sequences

https://github.com/SiyuanHuang95/SUG

공식 코드

SUG: Single-dataset Unified Generalization for 3D Point Cloud Classification

https://github.com/TencentARC/ViT-Lens

공식 코드

ViT-Lens: Initiating Omni-Modal Exploration through 3D Insights

https://github.com/VimsLab/Local3DFeatures

공식 코드

Local Neighborhood Features for 3D Classification

https://github.com/WangYueFt/dgcnn

공식 코드

Dynamic Graph CNN for Learning on Point Clouds

https://github.com/Yebulabula/OpenDlign

공식 코드

OpenDlign: Open-World Point Cloud Understanding with Depth-Aligned Images

https://github.com/Yochengliu/Relation-Shape-CNN

공식 코드

Relation-Shape Convolutional Neural Network for Point Cloud Analysis

https://github.com/aHapBean/PCP-MAE

공식 코드

PCP-MAE: Learning to Predict Centers for Point Masked Autoencoders

https://github.com/adonis-galaxy/dspoint

공식 코드

DSPoint: Dual-scale Point Cloud Recognition with High-frequency Fusion

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.