ojh6404 Goto Github PK

arbitrary-hands-3d-reconstruction

🔥(CVPR 2023) ACR: Attention Collaboration-based Regressor for Arbitrary Two-Hand Reconstruction

awesome-robotic-tooling

Tooling for professional robotic development in C++ and Python with a touch of ROS, autonomous driving and aerospace.

collada_urdf

Contains packages for converting collada files into URDF

d3rlpy

An offline deep reinforcement learning library

detic_ros

ROS wrapper for pretrained Detic instance segmentation (and some utils to work with point cloud)

epic-kitchens-100-hand-object-bboxes

:raised_hand: :fork_and_knife: A repo for processing the raw hand object detections to produce releasable pickles + library for using these

eus_imitation

ROS Package for Imitation Learning with Euslisp Robot Interface

eus_vive

ROS package for multi robot teleoperation with HTC Vive/SpaceNav/Oculus/Tablis

force-lorenz63

FORCE Learning example for Lorenz63 system

frankmocap

A Strong and Easy-to-use Single View 3D Hand+Body Pose Estimator

hand_object_detection_ros

ROS Package for Hand-Object-Detection

hand_object_detector

Project and dataset webpage:

honeybee

Official implementation of Honeybee

ihoi

image_transport_plugins

A set of plugins for publishing and subscribing to sensor_msgs/Image topics in representations other than raw pixel data.

imitator

Imitation Learning Library

imu_from_ios_sensorlog

ROS node to publish realtime IMU data from iOS device

isaacgymenvs

jsk_common

common programs for jsk-ros-pkg

jsk_demos

JSK demo programs

jsk_planning

JSK planning packages

jsk_recognition

JSK perception ROS packages

jsk_robot

jsk-ros-pkg/jsk_robot

jsk_visualization

jsk visualization ros packages

kinova_imitation_ros

Imitation ROS workspace for Kinova Gen3

kortex

Code examples and API documentation for KINOVA® KORTEX™ robotic arms

latent-space-priors

Source code release for "Leveraging Demonstrations with Latent Space Priors"

lecture2023

legged_gym

Isaac Gym Environments for Legged Robots

maml_rl

Code for RL experiments in "Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks"