PyTorch3D provides efficient, reusable components for 3D Computer Vision research with PyTorch. Key features include: Data structure for storing and ...
If pytorch3d is not installed, install it using the following cell: ... !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable' ...
3D ResNet. By FAIR PyTorchVideo. Resnet Style Video classification networks pretrained on the Kinetics 400 dataset. View on Github · Open on Google Colab
Jan 24, 2020 · PyTorch3D provides efficient, reusable components for 3D Computer Vision research with PyTorch. Key features include: Data structure for storing and manipulating triangle meshes Efficient operations on triangle meshes (projective transformations, graph convolution, sampling, loss functions) A differentiable mesh renderer
Feb 12, 2020 · 3D-UNet-PyTorch-Implementation. This is the implementation of 3D UNet Proposed by Özgün Çiçek et al., for details please refer to: 3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation. Dataset used: Soft-tissue-Sarcoma, the dataset I used has been processed by other people and due to some reasons I cannot share it here.
Jul 31, 2019 - Convolutional Neural Network for 3D meshes in PyTorch - GitHub - ranahanocka/MeshCNN: Convolutional Neural Network for 3D meshes in PyTorch.
24.01.2020 · Introduction. PyTorch3D provides efficient, reusable components for 3D Computer Vision research with PyTorch. Key features include: Data structure for storing and manipulating triangle meshes. Efficient operations on triangle meshes (projective transformations, graph convolution, sampling, loss functions) A differentiable mesh renderer.
Pytorch-3D-R2N2. Working Pytorch re-implementation of 3D-R2N2: A Unified Approach for Single and Multi-view 3D Object Reconstruction by Choy et.al original repo. Trained only on chair classes alone. Train more on the entire dataset to work on all other classes. Dataset can be found in the paper.