noshaba

Auto-Photoshop-StableDiffusion-Plugin

A user-friendly plug-in that makes it easy to generate stable diffusion images inside Photoshop using either Automatic or ComfyUI as a backend.

deep-reinforcement-learning

Repo for the Deep Reinforcement Learning Nanodegree program

AvatarCLIP

[SIGGRAPH 2022 Journal Track] AvatarCLIP: Zero-Shot Text-Driven Generation and Animation of 3D Avatars

ASE

OmniIsaacGymEnvs

Reinforcement Learning Environments for Omniverse Isaac Gym

neural-blend-shapes

An end-to-end library for automatic character rigging, skinning, and blend shapes generation, as well as a visualization tool [SIGGRAPH 2021]

fairmotion

Tools to load, process and visualize motion capture data

MotioNet

A deep neural network that directly reconstructs the motion of a 3D human skeleton from monocular video [ToG 2020]

Bailando

Code for CVPR 2022 paper "Bailando: 3D dance generation via Actor-Critic GPT with Choreographic Memory"

ddpo-pytorch

DDPO for finetuning diffusion models, implemented in PyTorch with LoRA support

cmaes

Python library for CMA Evolution Strategy.

processing-animations-code

A set of Processing animations, which have commented code

PIP

A real-time system that captures physically correct human motion, joint torques, and ground reaction forces with only 6 inertial measurement units

ddpo

Code for the paper "Training Diffusion Models with Reinforcement Learning"

diffmimic

[ICLR 2023] DiffMimic: Efficient Motion Mimicking with Differentiable Physics https://arxiv.org/abs/2304.03274

DiffRL

[ICLR 2022] Accelerated Policy Learning with Parallel Differentiable Simulation

RFC

[NeurIPS 2020] Official PyTorch Implementation of "Residual Force Control for Agile Human Behavior Imitation and Extended Motion Synthesis". NeurIPS 2020.

Control-VAE

PhysicsVAE

Physics-based Character Controllers Using Conditional VAEs (SIGGRAPH 2022)

cic

CIC: Contrastive Intrinsic Control for Unsupervised Skill Discovery

dataset

choreographer

[ICLR 2023] Choreographer: a model-based agent that discovers and learns unsupervised skills in latent imagination, and it's able to efficiently coordinate and adapt the skills to solve downstream tasks.

MOSS

Official implementation of A Mixture of Surprises for Unsupervised Reinforcement Learning

Contact-Invariant-Optimization-Project

Implementation of Discovery of Complex Behaviors Through Contact-Invariant Optimization

DirectBehaviorSpecification

Code to reproduce the Arena environment experiments from Direct Behavior Specification via Constrained Reinforcement Learning.

CIO

Contact Invariant Optimization Program

TillingPatch

Tiling Motion Patches

REAL2021_starter_kit

Starting kit for the REAL2021 competition on Robot open-Ended Autonomous Learning

InteractionGraphS23

ddpo

Code for the paper "Training Diffusion Models with Reinforcement Learning"