Clean, Robust, and Unified PyTorch implementation of popular Deep Reinforcement Learning (DRL) algorithms (Q-learning, Duel DDQN, PER, C51, Noisy DQN, PPO, DDPG, TD3, SAC, ASL)

A curated list of visual reinforcement learning resources

Minkowski Engine is an auto-diff neural network library for high-dimensional sparse tensors

Spatial Sparse Convolution Library

A list of papers about deep point cloud compression.

Fast learning-based Point Cloud lossy Compression in our ICME 2023 paper and other improvements

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a fast range coder in C++, using SSE

机器学习大作业-复现KAN网络

Python port to the VTM CABAC engine via pybind11

OctFormer: Octree-based Transformers for 3D Point Clouds

Soruce code of OctAttention: Octree-Based Large-Scale Contexts Model for Point Cloud Compression

PU-Net: Point Cloud Upsampling Network, CVPR, 2018 (https://arxiv.org/abs/1801.06761)

Point Transformers

Differentiable Point Cloud Sampling (CVPR 2020 Oral)

Draco is a library for compressing and decompressing 3D geometric meshes and point clouds. It is intended to improve the storage and transmission of 3D graphics.

My solutions to the assignments in the book: "A Student’s Guide to Bayesian Statistics" by Ben Lambert.

PDF 文本复制自动去换行符，去格式

[Arxiv] Measuring the Discrepancy between 3D Geometric Models using Directional Distance Fields

阿里云盘命令行客户端，支持JavaScript插件，支持同步备份功能。

PointNet and PointNet++ implemented by pytorch (pure python) and on ModelNet, ShapeNet and S3DIS.

Convert any Triangle Mesh to Watertight Manifold

Open3D: A Modern Library for 3D Data Processing

Geometry based point cloud compression (G-PCC) test model

This is the official PyTorch implementation of our paper "Density-preserving Deep Point Cloud Compression" (CVPR 2022).

Sparse Tensor-based Multiscale Representation for Point Cloud Geometry Compression

Multiscale Point Cloud Geometry Compression

Tensor library for machine learning