A suite of scripts and easy-to-follow tutorial to process point cloud data with Python
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Updated
Jun 7, 2024 - Jupyter Notebook
A suite of scripts and easy-to-follow tutorial to process point cloud data with Python
[CVPR'23] Learning Neural Parametric Head Models
[AAAI-2024] Pytorch implementation of "ColNeRF: Collaboration for Generalizable Sparse Input Neural Radiance Field"
A PyTorch Library for Accelerating 3D Deep Learning Research
NVIDIA Kaolin Wisp is a PyTorch library powered by NVIDIA Kaolin Core to work with neural fields (including NeRFs, NGLOD, instant-ngp and VQAD).
A versatile framework for 3D machine learning built on Pytorch Lightning and Hydra [looking for contributors!]
[Siggraph '23] NeRSemble: Neural Radiance Field Reconstruction of Human Heads
Pytorch code to construct a 3D point cloud model from single RGB image.
pyntcloud is a Python library for working with 3D point clouds.
A Framework for Generalized Steady State Neural Fluid Simulations
Code and Datasets for 3D Shape Completion related publications
3DMatch - a 3D ConvNet-based local geometric descriptor for aligning 3D meshes and point clouds.
Explore the World in 3D: 3DPointCloudLab is your gateway to the fascinating universe of 3D depth maps and point clouds. Whether you're a researcher, developer, or 3D enthusiast, our repository offers a treasure trove of tools, techniques, and insights dedicated to the exploration and manipulation of 3D spatial data.
a Pytorch library for multi-view 3D understanding and generation
Research platform for 3D object detection in PyTorch.
[ECCV'20] Convolutional Occupancy Networks
Fast and Robust Registration of Partially Overlapping Point Clouds in Driving Applications
[ECCV 2020] Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution
Octree Transformer: Autoregressive 3D Shape Generation on Hierarchically Structured Sequences - CVPRW: StruCo3D, 2023
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