There are 24 repositories under 3d-deep-learning topic.
A PyTorch Library for Accelerating 3D Deep Learning Research
🔥[IEEE TPAMI 2020] Deep Learning for 3D Point Clouds: A Survey
NVIDIA Kaolin Wisp is a PyTorch library powered by NVIDIA Kaolin Core to work with neural fields (including NeRFs, NGLOD, instant-ngp and VQAD).
Python code to fuse multiple RGB-D images into a TSDF voxel volume.
[ECCV'20] Convolutional Occupancy Networks
3DMatch - a 3D ConvNet-based local geometric descriptor for aligning 3D meshes and point clouds.
This repository contains the code for the CVPR 2020 paper "Differentiable Volumetric Rendering: Learning Implicit 3D Representations without 3D Supervision"
Fuse multiple depth frames into a TSDF voxel volume.
This repository contains the source codes for the paper "AtlasNet: A Papier-Mâché Approach to Learning 3D Surface Generation ". The network is able to synthesize a mesh (point cloud + connectivity) from a low-resolution point cloud, or from an image.
[ECCV 2020] Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution
Pytorch code to construct a 3D point cloud model from single RGB image.
KITTI data processing and 3D CNN for Vehicle Detection
3D Object Detection for Autonomous Driving in PyTorch, trained on the KITTI dataset.
[CVPR'23] Learning Neural Parametric Head Models
[ICCVW-2021] SA-Det3D: Self-attention based Context-Aware 3D Object Detection
[Siggraph '23] NeRSemble: Neural Radiance Field Reconstruction of Human Heads
This work is based on our paper "DualConvMesh-Net: Joint Geodesic and Euclidean Convolutions on 3D Meshes", which appeared at the IEEE Conference On Computer Vision And Pattern Recognition (CVPR) 2020.
TextureNet: Consistent Local Parametrizations for Learning from High-Resolution Signals on Meshes
A collection of 3D vision and language (e.g., 3D Visual Grounding, 3D Question Answering and 3D Dense Caption) papers and datasets.
Code base of ParSeNet: ECCV 2020.
Meshing Point Clouds with Predicted Intrinsic-Extrinsic Ratio Guidance (ECCV2020)
DeepMetaHandles: Learning Deformation Meta-Handles of 3D Meshes with Biharmonic Coordinates
This repository contains the source codes for the paper "Unsupervised cycle-consistent deformation for shape matching".
our code for paper 'PointCutMix: Regularization Strategy for Point Cloud Classification', Neurocomputing, 2022
Fast and Robust Registration of Partially Overlapping Point Clouds in Driving Applications
CSGNet for voxel based input
3D Shape Generation Baselines in PyTorch.
Paper list of deep learning on point clouds.
Voint Cloud: Multi-View Point Cloud Representation for 3D Understanding (ICLR 2023)