Improved Precision and Recall Metric for Assessing Generative Models - Unofficial Pytorch Implementation

Official implemention for Diffusion Models Are Innate One-Step Generators

text and image to video generation: CogVideoX (2024) and CogVideo (ICLR 2023)

VideoCrafter2: Overcoming Data Limitations for High-Quality Video Diffusion Models

EDM2 and Autoguidance -- Official PyTorch implementation

Get hundred of million of image+url from the crawling at home dataset and preprocess them

Implementation of Particle Guidance: non-I.I.D. Diverse Sampling with Diffusion Models

Implementation of Particle Guidance: non-I.I.D. Diverse Sampling with Diffusion Models

GLIDE: a diffusion-based text-conditional image synthesis model

PyTorch package for the discrete VAE used for DALL·E.

Code for NeurIPS 2023 paper "Restart Sampling for Improving Generative Processes"

Codebase for evaluation of deep generative models as presented in Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion models

Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch

CLIP+MLP Aesthetic Score Predictor

An open source implementation of CLIP.

A playbook for systematically maximizing the performance of deep learning models.

[NeurIPS 2023] ImageReward: Learning and Evaluating Human Preferences for Text-to-image Generation

🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch and FLAX.

Code for ICML 2023 paper, "PFGM++: Unlocking the Potential of Physics-Inspired Generative Models"

Code for ICLR 2023 Paper, "Stable Target Field for Reduced Variance Score Estimation in Diffusion Models”

Solve puzzles. Learn CUDA.

Code for NeurIPS 2022 Paper, "Poisson Flow Generative Models" (PFGM)

This is a PyTorch implementation of Language style transfer using cross-alignment technique

Experiments to rewrite style transfer code from tensorflow to pytorch (not finished yet)

Code for ICLR 2022 Paper, "Controlling Directions Orthogonal to a Classifier"

Code for "Learning data-driven discretizations for partial differential equations"