Code for "Sparse Steerable Convolutions: An Efficient Learning of SE(3)-Equivariant Features for Estimation and Tracking of Object Poses in 3D Space", NeurIPS 2021. PaperSuppArxiv
PyTorch implementation of the paper:
PyTorch implementation of our ICCV2021 paper:
The main features of sjtu-visys/structdepth are: Scene Perception and Estimation.
Open-source alternatives to sjtu-visys/structdepth include: bochenys/rope — This repo stores code used in the paper. gorilla-lab-scut/ss-conv — Code for "Sparse Steerable Convolutions: An Efficient Learning of SE(3)-Equivariant Features for Estimation and… halleyjiang/plnet — The Pytorch code for our following paper. haoyu94/coarse-to-fine-correspondences — PyTorch implementation of the paper:. irmvlab/pwclonet — PWCLO-Net: Deep LiDAR Odometry in 3D Point Clouds Using Hierarchical Embedding Mask Optimization (CVPR 2021) This is… jeremywangjz/category-6d-pose — This is the official implementation of the paper: Category-Level 6D Object Pose Estimation via Cascaded Relation and…
