There are 13 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
Python code to fuse multiple RGB-D images into a TSDF voxel volume.
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'20] Convolutional Occupancy Networks
[ECCV 2020] Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution
A 3D vision library from 2D keypoints: monocular and stereo 3D detection for humans, social distancing, and body orientation.
KITTI data processing and 3D CNN for Vehicle Detection
3D Object Detection for Autonomous Driving in PyTorch, trained on the KITTI dataset.
Pytorch code to construct a 3D point cloud model from single RGB image.
SA-Det3D: Self-attention based Context-Aware 3D Object Detection (ICCV-AvVision-2021)
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
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".
Meshing Point Clouds with Predicted Intrinsic-Extrinsic Ratio Guidance (ECCV2020)
Code base of ParSeNet: ECCV 2020.
Paper list of deep learning on point clouds.
CSGNet for voxel based input
our code for paper 'PointCutMix: Regularization Strategy for Point Cloud Classification'
Fast and Robust Registration of Partially Overlapping Point Clouds in Driving Applications
3D Shape Generation Baselines in PyTorch.
list of papers, code, datasets and other resources
A collection of 3d visual grounding papers and datasets.
PointRCNN configured to Argoverse/Custom dataset
Pytorch Implementation of Learning Local Shape Descriptors from Part Correspondences(ToG 2017, H Huang et al.): https://people.cs.umass.edu/~hbhuang/local_mvcnn/