https://github.com/Ayumu-J-S/Point-JEPA
공식 코드Point-JEPA: A Joint Embedding Predictive Architecture for Self-Supervised Learning on Point Cloud
Papers with Code 아카이브
Few-Shot 3D Point Cloud Classification
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/CGuangyan-BIT/PointGPT
공식 코드PointGPT: Auto-regressively Generative Pre-training from Point Clouds
https://github.com/Pang-Yatian/Point-MAE
공식 코드Masked Autoencoders for Point Cloud Self-supervised Learning
https://github.com/WangYueFt/dgcnn
공식 코드https://github.com/aHapBean/PCP-MAE
공식 코드PCP-MAE: Learning to Predict Centers for Point Masked Autoencoders
https://github.com/cgye96/a_closer_look_at_3dfsl
공식 코드https://github.com/hansen7/OcCo
공식 코드Unsupervised Point Cloud Pre-Training via Occlusion Completion
https://github.com/haotian-liu/maskpoint
공식 코드Masked Discrimination for Self-Supervised Learning on Point Clouds
https://github.com/kabouzeid/point2vec
공식 코드point2vec for Self-Supervised Representation Learning on Point Clouds
https://github.com/liuyyy111/point-rae
공식 코드Regress Before Construct: Regress Autoencoder for Point Cloud Self-supervised Learning
https://github.com/lulutang0608/Point-BERT
공식 코드Point-BERT: Pre-training 3D Point Cloud Transformers with Masked Point Modeling
https://github.com/mohamedafham/crosspoint
공식 코드CrossPoint: Self-Supervised Cross-Modal Contrastive Learning for 3D Point Cloud Understanding
https://github.com/qizekun/ReCon
공식 코드Contrast with Reconstruct: Contrastive 3D Representation Learning Guided by Generative Pretraining
https://github.com/qizekun/ShapeLLM
공식 코드ShapeLLM: Universal 3D Object Understanding for Embodied Interaction
https://github.com/runpeidong/act
공식 코드https://github.com/tejasanvekar/gpr-net
공식 코드GPr-Net: Geometric Prototypical Network for Point Cloud Few-Shot Learning
https://github.com/tensorflow/tensor2tensor
공식 코드https://github.com/yangyanli/PointCNN
공식 코드https://github.com/zrrskywalker/i2p-mae
공식 코드Learning 3D Representations from 2D Pre-trained Models via Image-to-Point Masked Autoencoders
https://github.com/zrrskywalker/point-m2ae
공식 코드Point-M2AE: Multi-scale Masked Autoencoders for Hierarchical Point Cloud Pre-training
https://github.com/zyh16143998882/IDPT
공식 코드Instance-aware Dynamic Prompt Tuning for Pre-trained Point Cloud Models
https://github.com/zyh16143998882/aaai24-pointfemae
공식 코드Towards Compact 3D Representations via Point Feature Enhancement Masked Autoencoders
https://github.com/zyh16143998882/iccv23-idpt
공식 코드Instance-aware Dynamic Prompt Tuning for Pre-trained Point Cloud Models
https://gitee.com/gai-shaoyan/mind3d
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/04RR/SOTA-Vision
https://github.com/1wy/bert
https://github.com/2023-MindSpore-1/ms-code-14/tree/main/Transformer
https://github.com/2023-MindSpore-1/ms-code-223/tree/main/PointNet
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
https://github.com/2023-MindSpore-1/ms-code-223/tree/main/PointNet2
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
https://github.com/2023-MindSpore-1/ms-code-35
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/2023-MindSpore-1/ms-code-7/tree/main/PointNet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/2023-MindSpore-1/ms-code-8/tree/main/PointNet2
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
https://github.com/2023-MindSpore-4/Code10/tree/main/PointNet
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
https://github.com/2023-MindSpore-4/Code10/tree/main/PointNet2
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
https://github.com/2023-MindSpore-4/Code10/tree/main/frustum-pointnet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/2023-MindSpore-4/Code8/tree/main/AttentionCluster
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.