This project is a PyTorch-based framework of deep learning models designed for the classification and semantic segmentation of 3D point cloud data. It provides implementations of the PointNet architecture to perform global category labeling of entire objects and detailed partitioning of large-scale 3D environments. The system handles semantic segmentation across multiple scales, ranging from identifying individual components within a single object to labeling distinct category types within large-scale scenes. The framework includes structural components for processing unordered point sets, s
Open3D is a 3D data processing library, visualization engine, and machine learning library. It provides a framework for manipulating point clouds and meshes through specialized algorithms designed for 3D data science workflows. The project includes a toolkit for 3D scene reconstruction to generate spatial models and align surfaces from raw data. It also functions as a GPU accelerated framework that offloads intensive spatial computations to the graphics processor to increase processing speed. The library covers a broad range of capabilities including physically based light simulations for vi
3DMV jointly combines RGB color and geometric information to perform 3D semantic segmentation of RGB-D scans. This work is based on our ECCV'18 paper, 3DMV: Joint 3D-Multi-View Prediction for 3D Semantic Scene Segmentation.
0. The CUDA and Pytorch version that is used for this work: ~~~ 'CUDA==10.0', 'torch==1.1.0', 'CUDNN==7.5.0' ~~~ Warning: We tried CUDA11.0+Torch1.7.1 on RTX3090, the AP performance is significantly lower than the aforementioned environment setup.
Code for the paper DyCo3D: Robust Instance Segmentation of 3D Point Clouds through Dynamic Convolution, CVPR 2021.
aim-uofa/dyco3d 的主要功能包括：3D Detection and Segmentation。
aim-uofa/dyco3d 的开源替代品包括： yanx27/pointnet_pointnet2_pytorch — This project is a PyTorch-based framework of deep learning models designed for the classification and semantic… intel-isl/open3d — Open3D is a 3D data processing library, visualization engine, and machine learning library. It provides a framework… angeladai/3dmv — 3DMV jointly combines RGB color and geometric information to perform 3D semantic segmentation of RGB-D scans. This… autonomousvision/neat — This repository is for the ICCV 2021 paper NEAT: Neural Attention Fields for End-to-End Autonomous Driving. autovision-cloud/sa-det3d — By Prarthana Bhattacharyya, Chengjie Huang and Krzysztof Czarnecki. anonymous0522/raan — 0. The CUDA and Pytorch version that is used for this work: ~~~ 'CUDA==10.0', 'torch==1.1.0', 'CUDNN==7.5.0' ~~~…