https://github.com/open-air-sun/pq-transformer
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
Papers with Code 아카이브
3D Semantic Segmentation
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3D Semantic Segmentation is a computer vision task that involves dividing a 3D point cloud or 3D mesh into semantically meaningful parts or regions. The goal of 3D semantic segmentation is to identify and label different objects and parts within a 3D scene, which can be used for applications such as robotics, autonomous driving, and augmented reality.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/open-mmlab/mmdetection3d
CENet: Toward Concise and Efficient LiDAR Semantic Segmentation for Autonomous Driving
https://github.com/pengsongyou/openscene
https://github.com/pjlab-adg/openpcseg
Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution
https://github.com/prasadsawant5/PointNet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/princeton-vl/SimpleView
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/qq456cvb/Point-Transformers
https://github.com/rauleun/point-transformer-tf2
https://github.com/referit3d/referit3d
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
https://github.com/romaintha/pytorch_pointnet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/rsy6318/CorrI2P
Self-supervised Learning of LiDAR 3D Point Clouds via 2D-3D Neural Calibration
https://github.com/rusty1s/pytorch_cluster
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
https://github.com/saaries/PointNet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/sanantoniochili/PointCloud_KNN
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/sarthakTUM/roofn3d
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/scannetpp/scannetpp
https://github.com/sh4175515/PointTransformer
https://github.com/shaygu62/Protein-Classification
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
https://github.com/shwoo93/minkowskiengine
4D Spatio-Temporal ConvNets: Minkowski Convolutional Neural Networks
https://github.com/smfirmin/DeepLearningFinalProject
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/soumik12345/point-cloud-segmentation
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/sshaoshuai/Pointnet2.PyTorch
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
https://github.com/stanfordmimi/merlin
Merlin: A Vision Language Foundation Model for 3D Computed Tomography
https://github.com/sumo-agarwal/submanifold-sparse-conv-sparseconvnet
3D Semantic Segmentation with Submanifold Sparse Convolutional Networks
https://github.com/tao-tao-tao-tao-tao/diffusion_suction
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
https://github.com/tejasanvekar/gpr-net
https://github.com/thangvubk/softgroup
STPLS3D: A Large-Scale Synthetic and Real Aerial Photogrammetry 3D Point Cloud Dataset
https://github.com/theia-4869/semantic-poss-api
SemanticKITTI: A Dataset for Semantic Scene Understanding of LiDAR Sequences
https://github.com/thu17cyz/3DIoUMatch
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
https://github.com/tiagocortinhal/titan-next
https://github.com/tianzhuotao/cac
https://github.com/timothylimyl/PointNet-Pytorch
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/tingxueronghua/dpke
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
https://github.com/tkdguraa/point-transformer-tensorflow
https://github.com/tonysy/pointnet2_tf
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
https://github.com/tosshero/3d_perception
Towards Robust Robot 3D Perception in Urban Environments: The UT Campus Object Dataset
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.