Python Denoising-diffusion Resources

Bilateral Denoising Diffusion Models (BDDMs) This is the official PyTorch implementation of the following paper: BDDM: BILATERAL DENOISING DIFFUSION M

Planning with Diffusion Training and visualizing of diffusion models from Planning with Diffusion for Flexible Behavior Synthesis. Guided sampling cod

Practical Blind Denoising via Swin-Conv-UNet and Data Synthesis [Paper] [Online Demo] The following results are obtained by our SCUNet with purely syn

Generative Modeling with Optimal Transport Maps The repository contains reproducible PyTorch source code of our paper Generative Modeling with Optimal

GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation [OpenReview] [arXiv] [Code] The official implementation of GeoDiff: A Geome

#360Diffusion automatically upscales your CLIP Guided Diffusion outputs using Real-ESRGAN. Latest Update: Alpha 1.61 [Main Branch] - 01/11/22 Layout a

Retrieval-Augmented Denoising Diffusion Probabilistic Models (wip) Implementation of Retrieval-Augmented Denoising Diffusion Probabilistic Models in P

scAR scAR (single cell Ambient Remover) is a package for denoising multiple single cell omics data. It can be used for multiple tasks, such as, sgRNA

Patch-Diffusion This is an official PyTorch implementation of "Patch Diffusion: A General Module for Face Manipulation Detection" in AAAI2022. Require

Blind2Unblind: Self-Supervised Image Denoising with Visible Blind Spots Blind2Unblind Citing Blind2Unblind @inproceedings{wang2022blind2unblind, tit

DiffGAN-TTS - PyTorch Implementation PyTorch implementation of DiffGAN-TTS: High

Pseudo Numerical Methods for Diffusion Models on Manifolds (PNDM) This repo is the official PyTorch implementation for the paper Pseudo Numerical Meth

MarkovGNN This is the official PyTorch-Geometric implementation of MarkovGNN paper under the title "MarkovGNN: Graph Neural Networks on Markov Diffusi

NTIRE 2022 - Image Inpainting Challenge Important dates 2022.02.01: Release of train data (input and output images) and validation data (only input) 2

traiNNer traiNNer is an open source image and video restoration (super-resolution, denoising, deblurring and others) and image to image translation to

Variational DiffWave Training DiffWave using variational method from Variational Diffusion Models. Quick Start python train_distributed.py discrete_10

VRT: A Video Restoration Transformer Jingyun Liang, Jiezhang Cao, Yuchen Fan, Kai Zhang, Rakesh Ranjan, Yawei Li, Radu Timofte, Luc Van Gool Computer

GNDC For submission to IEEE TKDE. Overview Here we provide the implementation of GND-Nets (Graph Neural Diffusion Networks) in TensorFlow. The reposit

PyTorch Implementation of "Progressive Distillation for Fast Sampling of Diffusion Models(v-diffusion)" Unofficial PyTorch Implementation of Progressi

The trained model and denoising example for paper : Cardiopulmonary Auscultation Enhancement with a Two-Stage Noise Cancellation Approach

Denoising images with Fourier Ring Correlation loss The python code accompanies the working manuscript Image quality measurements and denoising using

UNet-SIDE The undersampled DWI image using Slice-Interleaved Diffusion Encoding (SIDE) method can be reconstructed by the UNet network. For Super Reso

Asynchronous-Anisotropic-Diffusion-Algorithm This is a demo for AAD algorithm. The subroutine of the anisotropic diffusion algorithm is modified from

Vector Quantized Diffusion Model for Text-to-Image Synthesis Due to company policy, I have to set microsoft/VQ-Diffusion to private for now, so I prov

Shape Generation and Completion Through Point-Voxel Diffusion Project | Paper Implementation of Shape Generation and Completion Through Point-Voxel Di

A minimal yet resourceful implementation of diffusion models (along with pretrained models + synthetic images for nine datasets)

Anime4K Anime4K is a set of open-source, high-quality real-time anime upscaling/denoising algorithms that can be implemented in any programming langua

ELD The implementation of CVPR 2020 (Oral) paper "A Physics-based Noise Formation Model for Extreme Low-light Raw Denoising" and its journal (TPAMI) v

CSDI This is the github repository for the NeurIPS 2021 paper "CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series Imputation

Image Denoising with Control over Deep Network Hallucination Paper and arXiv preprint -- Our frequency-domain insights derive from SFM and the concept

libsdae - deep-Autoencoder & denoising autoencoder A simple Tensorflow based library for Deep autoencoder and denoising AE. Library follows sklearn st

PyTorch implementation of 'Denoising Diffusion Probabilistic Models' This reposi

A Tour in the Wonderland of Math with Python A collection of python scripts for drawing beautiful figures and animating interesting algorithms in math

Minimal code and simple experiments to play with Denoising Diffusion Probabilist

Class-Attentive Diffusion Network for Semi-Supervised Classification Official Implementation of AAAI 2021 paper Class-Attentive Diffusion Network for

CCGL: Contrastive Cascade Graph Learning This repo provides a reference implementation of Contrastive Cascade Graph Learning (CCGL) framework as descr

tedana: TE Dependent ANAlysis TE-dependent analysis (tedana) is a Python library for denoising multi-echo functional magnetic resonance imaging (fMRI)

HDRUNet [Paper Link] HDRUNet: Single Image HDR Reconstruction with Denoising and Dequantization By Xiangyu Chen, Yihao Liu, Zhengwen Zhang, Yu Qiao an

jumpdiff jumpdiff is a python library with non-parametric Nadaraya─Watson estimators to extract the parameters of jump-diffusion processes. With jumpd

Text-Glided-Diffusion Installation First clone this repository: git clone https://github.com/afiaka87/text-glided-diffusion.git cd text-glided-diffusi

Latent Diffusion Models arXiv | BibTeX High-Resolution Image Synthesis with Latent Diffusion Models Robin Rombach*, Andreas Blattmann*, Dominik Lorenz

ReaDDy (Reaction Diffusion Dynamics) is an open source particle based reaction-diffusion simulator that can be configured and run via Python. Currentl

GLIDE This is the official codebase for running the small, filtered-data GLIDE model from GLIDE: Towards Photorealistic Image Generation and Editing w

Latent Diffusion Models Requirements A suitable conda environment named ldm can be created and activated with: conda env create -f environment.yaml co

DiffSinger: Singing Voice Synthesis via Shallow Diffusion Mechanism This repository is the official PyTorch implementation of our AAAI-2022 paper, in

v-diffusion-pytorch v objective diffusion inference code for PyTorch, by Katherine Crowson (@RiversHaveWings) and Chainbreakers AI (@jd_pressman). The

DiffSinger: Singing Voice Synthesis via Shallow Diffusion Mechanism This repository is the official PyTorch implementation of our AAAI-2022 paper, in

DeepDiffusion Introduction This repository provides the code of the DeepDiffusion algorithm for unsupervised learning of retrieval-adapted representat

Self-Supervised Image Denoising via Iterative Data Refinement Yi Zhang1, Dasong Li1, Ka Lung Law2, Xiaogang Wang1, Hongwei Qin2, Hongsheng Li1 1CUHK-S

Maximum Likelihood Training of Score-Based Diffusion Models This repo contains the official implementation for the paper Maximum Likelihood Training o

A Conditional Point Diffusion-Refinement Paradigm for 3D Point Cloud Completion This repo intends to release code for our work: Zhaoyang Lyu*, Zhifeng

ImageBART NeurIPS 2021 Patrick Esser*, Robin Rombach*, Andreas Blattmann*, Björn Ommer * equal contribution arXiv | BibTeX | Poster Requirements A sui

Disimpy Disimpy is a Python package for generating simulated diffusion-weighted MR signals that can be useful in the development and validation of dat

Label-Efficient Semantic Segmentation with Diffusion Models Official implementation of the paper Label-Efficient Semantic Segmentation with Diffusion

DenoisingRec Adaptive Denoising Training for Recommendation. This is the pytorch implementation of our paper at WSDM 2021: Denoising Implicit Feedback

Code for the Paper "Diffusion Models for Handwriting Generation"

WaveGrad Implementation (PyTorch) of Google Brain's high-fidelity WaveGrad vocoder (paper). First implementation on GitHub with high-quality generatio

Symbolic Music Generation with Diffusion Models Supplementary code release for our work Symbolic Music Generation with Diffusion Models. Installation

Diffusion Probabilistic Models This repository provides a reference implementation of the method described in the paper: Deep Unsupervised Learning us

Improved Techniques for Training Score-Based Generative Models This repo contains the official implementation for the paper Improved Techniques for Tr

PyTorch pretrained Diffusion Models A PyTorch reimplementation of Denoising Diffusion Probabilistic Models with checkpoints converted from the author'

Denoising Diffusion Probabilistic Models Jonathan Ho, Ajay Jain, Pieter Abbeel Paper: https://arxiv.org/abs/2006.11239 Website: https://hojonathanho.g

Denoising Diffusion Implicit Models (DDIM) Jiaming Song, Chenlin Meng and Stefano Ermon, Stanford Implements sampling from an implicit model that is t

Diffusion Probabilistic Models for 3D Point Cloud Generation [Paper] [Code] The official code repository for our CVPR 2021 paper "Diffusion Probabilis

jax-variational-diffwave Jax/Flax implementation of Variational-DiffWave. (Zhifeng Kong et al., 2020, Diederik P. Kingma et al., 2021.) DiffWave with

Score-Based Point Cloud Denoising (ICCV'21) [Paper] https://arxiv.org/abs/2107.10981 Installation Recommended Environment The code has been tested in

This repository contains a collection of resources and papers on Diffusion Models and Score-based Models. If there are any missing valuable resources

Stationary Diffusion State Neural Estimation Although many graph-based clustering methods attempt to model the stationary diffusion state in their obj

Self-Supervised Image Denoising via Iterative Data Refinement Yi Zhang1, Dasong Li1, Ka Lung Law2, Xiaogang Wang1, Hongwei Qin2, Hongsheng Li1 1CUHK-S

Denoising Normalizing Flow Christian Horvat and Jean-Pascal Pfister 2021 We combine Normalizing Flows (NFs) and Denoising Auto Encoder (DAE) by introd

PyMPDATA PyMPDATA is a high-performance Numba-accelerated Pythonic implementation of the MPDATA algorithm of Smolarkiewicz et al. used in geophysical

Official implementation of VQ-Diffusion: Vector Quantized Diffusion Model for Text-to-Image Synthesis

Unsupervised Image Denoising with Frequency Domain Knowledge (BMVC 2021 Oral) : Official Project Page This repository provides the official PyTorch im

Vector Quantized Diffusion Model for Text-to-Image Synthesis Overview This is the official repo for the paper: [Vector Quantized Diffusion Model for T

Blended Diffusion for Text-driven Editing of Natural Images Blended Diffusion for Text-driven Editing of Natural Images Omri Avrahami, Dani Lischinski

Unsupervised Image Denoising with Frequency Domain Knowledge (BMVC 2021 Oral) : Official Project Page This repository provides the official PyTorch im

Fast mesh denoising with data driven normal filtering using deep variational autoencoders This is an implementation for the paper entitled "Fast mesh

SwinIR: Image Restoration Using Swin Transformer This repository is the official PyTorch implementation of SwinIR: Image Restoration Using Shifted Win

Unleashing Transformers: Parallel Token Prediction with Discrete Absorbing Diffusion for Fast High-Resolution Image Generation from Vector-Quantized C

DivNoising: Diversity Denoising with Fully Convolutional Variational Autoencoders Mangal Prakash1, Alexander Krull1,2, Florian Jug2 1Authors contribut

Score-Based Generative Modeling through Stochastic Differential Equations This repo contains a PyTorch implementation for the paper Score-Based Genera

Restormer: Efficient Transformer for High-Resolution Image Restoration Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan,

faceswap-GAN Adding Adversarial loss and perceptual loss (VGGface) to deepfakes'(reddit user) auto-encoder architecture. Updates Date Update 2018-08-2

Restormer: Efficient Transformer for High-Resolution Image Restoration Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan,

diffusion-channels Source code for paper "Deep Diffusion Models for Robust Channel Estimation". Generic flow: Use 'matlab/main.mat' to generate traini

Climate Modeling with Neural Diffusion Equation Introduction This is the repository of our accepted ICDM 2021 paper "Climate Modeling with Neural Diff

Aydin is a user-friendly, feature-rich, and fast image denoising tool that provides a number of self-supervised, auto-tuned, and unsupervised image denoising algorithms.

Invertible Image Denoising This is the PyTorch implementation of paper: Invertible Denoising Network: A Light Solution for Real Noise Removal (CVPR 20

v-diffusion-jax v objective diffusion inference code for JAX, by Katherine Crowson (@RiversHaveWings) and Chainbreakers AI (@jd_pressman). The models

DIP-denosing This is a code repo for Rethinking Deep Image Prior for Denoising (ICCV 2021). Addressing the relationship between Deep image prior and e

Demo of using Auto Encoder for Image Denoising

Deep-Rep-MFIR Official implementation of Deep Reparametrization of Multi-Frame Super-Resolution and Denoising Publication: Deep Reparametrization of M

Discrete Denoising Flows This repository contains the code for the experiments presented in the paper Discrete Denoising Flows [1]. To give a short ov

DiffuseAnimals: Reaction-Diffusion Models for the Generation of Biological Patterns Introduction Reaction-diffusion equations can be utilized in order

Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising

Realistic galaxy simulation via score-based generative models Official code for 'Realistic galaxy simulation via score-based generative models'. We us

sdeflow-light This is a minimalist codebase for training score-based diffusion models (supporting MNIST and CIFAR-10) used in the following paper "A V

toy_gradlogp This repo implements some toy examples of the following score matching algorithms in PyTorch: ssm-vr: sliced score matching with variance

Fast Laplacian Eigenmaps in python Open-source Laplacian Eigenmaps for dimensionality reduction of large data in python. Comes with an wrapper for NMS

DeepXDE Voting on whether we should have a Slack channel for discussion. DeepXDE is a library for scientific machine learning. Use DeepXDE if you need