Stars
A latent text-to-image diffusion model
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
StableLM: Stability AI Language Models
High-Resolution Image Synthesis with Latent Diffusion Models
PyTorch code and models for the DINOv2 self-supervised learning method.
Taming Transformers for High-Resolution Image Synthesis
[CVPR 2024] 4D Gaussian Splatting for Real-Time Dynamic Scene Rendering
Structured state space sequence models
Amazon Bedrock Agentcore accelerates AI agents into production with the scale, reliability, and security, critical to real-world deployment.
This repository contains examples for customers to get started using the Amazon Bedrock Service. This contains examples for all available foundational models
An out-of-box human parsing representation extractor.
Official Pytorch Implementation for "MultiDiffusion: Fusing Diffusion Paths for Controlled Image Generation" presenting "MultiDiffusion" (ICML 2023)
3D mesh stylization driven by a text input in PyTorch
VPoser: Variational Human Pose Prior
Data preparation and loader for AMASS
FaceScape (PAMI2023 & CVPR2020)
Code for paper "Which Training Methods for GANs do actually Converge? (ICML 2018)"
A high-fidelity 3D face reconstruction library from monocular RGB image(s)
A simple probabilistic programming language.
Code for "Fast and Robust Multi-Person 3D Pose Estimation from Multiple Views" (CVPR 2019, T-PAMI 2021)
Person Image Synthesis via Denoising Diffusion Model (CVPR 2023)
This Python library makes it easy to display images and videos in a notebook.
Implementation of "Large Steps in Inverse Rendering of Geometry"
Epipolar Transformers (best paper award, CVPR 2020 workshop)
State-of-the-art methods for human trajectory forecasting. Contains code for papers published at ECCV 2020 and ICCV 2021.
Large dataset of hand-object contact, hand- and object-pose, and 2.9 M RGB-D grasp images.