Open-source alternatives to D2c Model.github.io

Code for Fast Training of Diffusion Models with Masked Transformers

Official implementation of Cold-Diffusion for different transformations in pytorch.

Official implementation for Estimating the Optimal Covariance with Imperfect Mean in Diffusion Probabilistic Models (ICML 2022), and a reimplementation of Analytic-DPM: an Analytic Estimate of the Optimal Reverse Variance in Diffusion Probabilistic Models (ICLR 2022)

Improved diffusion generative models with subspaces

Diffusion Probabilistic Modeling for Video Generation

Latent Diffusion is a framework for high-resolution image synthesis that performs the denoising process within a compressed latent space. It uses variational autoencoders to encode images into a lower-dimensional representation, reducing the computational cost of noise prediction compared to operating on raw pixels. The project enables text-to-image generation by integrating natural language descriptions through cross-attention conditioning. It also supports image inpainting and restoration, filling masked or missing image areas with generated content, and example-based synthesis using retrie

This is the official implementation of Cross-domain Compositing (CDC), a local, inference-time, image editing method which utilizes pretrained diffusion models for image compositing in various domains. We base our method on previous work in global image editing in inference-time, and propose a…

Official code for "Conditional Generation from Unconditional Diffusion Models using Denoiser Representations" (BMVC 2023)

A minimalist implementation of score-based diffusion model

Speed up Stable Diffusion with this one simple trick!

Fast Inference in Denoising Diffusion Models via MMD Finetuning

Code for the Paper "Improving Diffusion Model Efficiency Through Patching"

Jiaming Song, Chenlin Meng and Stefano Ermon, Stanford

This repo contains the official implementation for the NeurIPS 2019 paper Generative Modeling by Estimating Gradients of the Data Distribution,

The official PyTorch implementation for NCSNv2 (NeurIPS 2020)

PyTorch implementation for SDEdit: Image Synthesis and Editing with Stochastic Differential Equations

DiT is a latent diffusion model and transformer-based generative AI framework implemented in PyTorch. It functions as a class-conditional image generator that replaces traditional convolutional backbones with a transformer architecture to synthesize high-fidelity images. The project utilizes patch-based latent processing and latent space compression to operate on low-dimensional image representations. It incorporates class-conditional guidance and adjustable guidance scales to control the visual content of generated images during the sampling process. The framework covers distributed model t

Official PyTorch implementation for FastDPM, a fast sampling algorithm for diffusion probabilistic models

ICML 2023 official implementation for "Input Perturbation Reduces Exposure Bias in Diffusion Models"

ECCV 2022 & IJCV 2025 Accelerating Score-based Generative Models with Preconditioned Diffusion Sampling

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

Official PyTorch implementation of "Denoising MCMC for Accelerating Diffusion-Based Generative Models", ICML 2023 Oral Paper