Zhang-Chaofan
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HOCopt: Hand-Object Contact Optimization to refine poses
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
Class activation maps for your PyTorch models (CAM, Grad-CAM, Grad-CAM++, Smooth Grad-CAM++, Score-CAM, SS-CAM, IS-CAM, XGrad-CAM, Layer-CAM)
Effortless data labeling with AI support from Segment Anything and other awesome models.
Real-time multi-physics simulation with an emphasis on medical simulation.
The Power of the Senses: Generalizable Manipulation from Vision and Touch through Masked Multimodal Learning
Train robotic agents to learn to plan pushing and grasping actions for manipulation with deep reinforcement learning.
Image augmentation for machine learning experiments.
Tactile Sensing and Simulation; Visual Tactile Manipulation; Open Source.
Official Repo for ManiSkill-ViTac Challenge 2024
[CoRL 2022] Efficient Tactile Simulation with Differentiability for Robotic Manipulation
Downstream insertion tasks with NCF for tracking extrinsic contacts with tactile sensing
Isaac Gym Reinforcement Learning Environments
Using Catalyst.RL to train a robot to perform peg-in-hole insertion in simulation.
Modular reinforcement learning library (on PyTorch and JAX) with support for NVIDIA Isaac Gym, Omniverse Isaac Gym and Isaac Lab
A Minimal Example of Isaac Gym with DQN and PPO.
Reinforcement Learning Environments for Omniverse Isaac Gym
Tools for manipulating 3D meshes within the Menpo project.
This package provides a framework to automatically perform grasp tests on an arbitrary object model of choice.
A playbook for systematically maximizing the performance of deep learning models.
SOFA simulations solving the planning of a soft-rigid hybrid arm.
🏁 More robust checkerboard detection, similar algorithm to libcbdetect