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3D Point Cloud Reconstruction
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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Encoding and reconstruction of 3D point clouds.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/zb12138/sph3d
Spherical Kernel for Efficient Graph Convolution on 3D Point Clouds
https://github.com/zb12138/sph3dR
Spherical Kernel for Efficient Graph Convolution on 3D Point Clouds
https://github.com/zenroad/modifypointnet
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
https://github.com/zer0sh0t/artificial_intelligence/tree/master/transformer
https://github.com/zgx0534/pointnet_win
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/zhang-huihui/git-repository
https://github.com/zhangbo2008/best_pytorch_transformer
https://github.com/zhh6425/MotionPointNet
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
https://github.com/zhirongw/3DShapeNets
https://github.com/zipeiyang/DeepSpeechRecognition
https://github.com/zrrskywalker/point-bind
https://github.com/zrrskywalker/point-nn
Parameter is Not All You Need: Starting from Non-Parametric Networks for 3D Point Cloud Analysis
https://github.com/zsweet/BERT_zsw
https://github.com/zyang-ur/SAT
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
https://github.com/zysite/post
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.