https://github.com/huixiancheng/no-cpgnet
CPGNet: Cascade Point-Grid Fusion Network for Real-Time LiDAR Semantic Segmentation
Papers with Code 아카이브
Robust 3D Semantic Segmentation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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3D Semantic Segmentation under Out-of-Distribution Scenarios
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/isl-org/Open3D-ML
KPConv: Flexible and Deformable Convolution for Point Clouds
https://github.com/isunLt/PolarSeg
PolarNet: An Improved Grid Representation for Online LiDAR Point Clouds Semantic Segmentation
https://github.com/matlab-deep-learning/pretrained-salsanext
https://github.com/mit-han-lab/torchsparse
Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution
https://github.com/open-mmlab/mmdetection3d
CENet: Toward Concise and Efficient LiDAR Semantic Segmentation for Autonomous Driving
https://github.com/pjlab-adg/openpcseg
Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution
https://github.com/pjlab-adg/pcseg
Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution
https://github.com/plusmultiply/mprm
KPConv: Flexible and Deformable Convolution for Point Clouds
https://github.com/shwoo93/minkowskiengine
4D Spatio-Temporal ConvNets: Minkowski Convolutional Neural Networks
https://github.com/tiagocortinhal/titan-next
https://github.com/xuanyuzhou98/SqueezeSeg
https://github.com/xuanyuzhou98/SqueezeSegV2
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.