Stars
Video-based AI memory library. Store millions of text chunks in MP4 files with lightning-fast semantic search. No database needed.
Processed / Cleaned Data for Paper Copilot
Unified framework for robot learning built on NVIDIA Isaac Sim
A particle-based encoding for Neural Radiance Fields
This repo is meant to serve as a guide for Machine Learning/AI technical interviews.
Repository of Jupyter notebook tutorials for teaching the Deep Learning Course at the University of Amsterdam (MSc AI), Fall 2023
This repository contains everything you need to become tech interview Ready with most important tips and techniques
A collection of high-quality models for the MuJoCo physics engine, curated by Google DeepMind.
"Sequential Dexterity: Chaining Dexterous Policies for Long-Horizon Manipulation" code repository
Learning Deformable Object Manipulation from Expert Demonstrations (RA-L, IROS 2022)
Independent PyTorch Implementation of Object Scene Representation Transformer
Understanding Deep Learning - Simon J.D. Prince
An implementation of several unsupervised object discovery models (Slot Attention, SLATE, GNM) in PyTorch with pre-trained models.
[RSS 2023] Diffusion Policy Visuomotor Policy Learning via Action Diffusion
[CoRL 2023] This repository contains data generation and training code for Scaling Up & Distilling Down
[RSS 23] Dynamic-Resolution Model Learning for Object Pile Manipulation
ACID: Action-Conditional Implicit Visual Dynamics for Deformable Object Manipulation
MuJoCo Models for Google's Scanned Objects Dataset
[CoRL '23] Dexterous piano playing with deep reinforcement learning.
A comprehensive list of Implicit Representations and NeRF papers relating to Robotics/RL domain, including papers, codes, and related websites
Code for "Learning to Grasp the Ungraspable with Emergent Extrinsic Dexterity" (CoRL 2022)
IKEA Furniture Assembly Environment for Long-Horizon Complex Manipulation Tasks
A simulation environment and benchmark for human-to-robot object handovers
A MuJoCo/Gym environment for robot control using Reinforcement Learning. The task of agents in this environment is pixel-wise prediction of grasp success chances.
Robot Learning of Shifting Objects for Grasping in Cluttered Environments