Python Denoising-normalizing-flow Resources

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

E2FGVI (CVPR 2022) English | 简体中文 This repository contains the official implementation of the following paper: Towards An End-to-End Framework for Flo

Deep Equilibrium Optical Flow Estimation This is the official repo for the paper Deep Equilibrium Optical Flow Estimation (CVPR 2022), by Shaojie Bai*

03_Python_Flow_Control Introduction 👋 The control flow statements are an essential part of the Python programming language. A control flow statement

90_Python_Exercises_and_Challenges The best way to learn Python is by practicing examples. This repository contains the examples on basic and advance

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

SOFIMA SOFIMA (Scalable Optical Flow-based Image Montaging and Alignment) is a tool for stitching, aligning and warping large 2d, 3d and 4d microscopy

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

Note: This repo is adpoted from https://github.com/UNIMIBInside/Smart-Mobility-Prediction. Due to technical reasons, I did not fork their code. Introd

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

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

RIFE - Real-Time Intermediate Flow Estimation for Video Frame Interpolation YouTube | BiliBili 16X interpolation results from two input images: Introd

FILM: Frame Interpolation for Large Scene Motion Project | Paper | YouTube | Benchmark Scores Tensorflow 2 implementation of our high quality frame in

Energy-based GFlowNets Code for Generative Flow Networks for Discrete Probabilistic Modeling by Dinghuai Zhang, Nikolay Malkin, Zhen Liu, Alexandra Vo

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

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

Neural Scene Flow Fields PyTorch implementation of paper "Neural Scene Flow Fields for Space-Time View Synthesis of Dynamic Scenes", CVPR 2021 [Projec

Tensorflow Implementation of A Generative Flow for Text-to-Speech via Monotonic Alignment Search

MFD-ILP Fast and exact ILP-based solvers for the Minimum Flow Decomposition (MFD) problem, and variants of it. The solvers are implemented using Pytho

E-RAFT: Dense Optical Flow from Event Cameras This is the code for the paper E-RAFT: Dense Optical Flow from Event Cameras by Mathias Gehrig, Mario Mi

NCSR: Noise Conditional Flow Model for Learning the Super-Resolution Space Official NCSR training PyTorch Code for the CVPR2021 workshop paper "Noise

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

A simple visual node editor for Python Ryven combines flow-based visual scripting with Python. It gives you absolute freedom for your nodes and a simp

Dimension Reduced Turbulent Flow Data From Deep Vector Quantizers This is an implementation of A Physics-Informed Vector Quantized Autoencoder for Dat

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

ENSO (El Niño - Southern Oscillation) analysis in northeast Brazil É comprovada a influência dos fenômenos El Niño e La Niña nas secas no nordesde bra

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

json-schema-codegen Generate code from JSON schema files. Table of contents Introduction Currently supported languages Requirements Installation Usage

Self-Normalizing Networks Tutorials and implementations for "Self-normalizing networks"(SNNs) as suggested by Klambauer et al. (arXiv pre-print). Vers

PySDM PySDM is a package for simulating the dynamics of population of particles. It is intended to serve as a building block for simulation systems mo

raylab Reinforcement learning algorithms in RLlib and PyTorch. Installation pip install raylab Quickstart Raylab provides agents and environments to b

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

Net2Net Code accompanying the NeurIPS 2020 oral paper Network-to-Network Translation with Conditional Invertible Neural Networks Robin Rombach*, Patri

PyTorch implementation of 'Denoising Diffusion Probabilistic Models' This reposi

Minimal code and simple experiments to play with Denoising Diffusion Probabilist

[ICCV 2021] GyroFlow: Gyroscope-Guided Unsupervised Optical Flow Learning This is the official implementation of our ICCV2021 paper GyroFlow. Our pres

Flow Gaussian Mixture Model (FlowGMM) This repository contains a PyTorch implementation of the Flow Gaussian Mixture Model (FlowGMM) model from our pa

Notebooks A NASA MEaSUREs project to provide automated, low latency, global glacier flow and elevation change datasets This repository provides tools

r.sim.terrain A short-term landscape evolution model that simulates topographic change for both steady state and dynamic flow regimes across a range o

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

VQGAN-CLIP-Video cat.mp4 policeman.mp4 schoolboy.mp4 forsenBOG.mp4

signac-flow - manage workflows with signac The signac framework helps users manage and scale file-based workflows, facilitating data reuse, sharing, a

aiometer aiometer is a Python 3.6+ concurrency scheduling library compatible with asyncio and trio and inspired by Trimeter. It makes it easier to exe

🌎 JSONClasses JSONClasses is a declarative data flow pipeline and data graph framework. Official Website: https://www.jsonclasses.com Official Docume

VCN: Volumetric correspondence networks for optical flow [project website] Requirements python 3.6 pytorch 1.1.0-1.3.0 pytorch correlation module (opt

Occupancy Flow This repository contains the code for the project Occupancy Flow - 4D Reconstruction by Learning Particle Dynamics. You can find detail

Flow Flow is a computational framework for deep RL and control experiments for traffic microsimulation. See our website for more information on the ap

A repository built on the Flow software package to explore cyber-security attacks on intelligent transportation systems.

PyTorch implementation of normalizing flow models

PyPowSyBl The PyPowSyBl project gives access PowSyBl Java framework to Python developers. This Python integration relies on GraalVM to compile Java co

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 modular PyTorch library for optical flow estimation using neural networks

[AAAI 2022] Low-Light Image Enhancement with Normalizing Flow Paper | Project Page Low-Light Image Enhancement with Normalizing Flow Yufei Wang, Renji

yandex-shifts-weather The repository contains information about my solution for the Weather Prediction track in the Yandex Shifts challenge https://re

SSVC The source code for paper [Suppressing Static Visual Cues via Normalizing Flows for Self-Supervised Video Representation Learning] samples of the

Self-Supervised Learning of Event-based Optical Flow with Spiking Neural Networks Work accepted at NeurIPS'21 [paper, video]. If you use this code in

Katana ML Skipper This is a simple and flexible ML workflow engine. It helps to orchestrate events across a set of microservices and create executable

Spotify API Apps 🎷 🎶 🎼 This repository consists of many strange codes that make you think why the hell this guy doing this. Well... I got some reas

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

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

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

Densely connected normalizing flows This repository is the official implementation of NeurIPS 2021 paper Densely connected normalizing flows. Poster a

Annealed Flow Transport Monte Carlo Open source implementation accompanying ICML 2021 paper by Michael Arbel*, Alexander G. D. G. Matthews* and Arnaud

I3D models transfered from Tensorflow to PyTorch This repo contains several scripts that allow to transfer the weights from the tensorflow implementat

pytm: A Pythonic framework for threat modeling Introduction Traditional threat modeling too often comes late to the party, or sometimes not at all. In

UnFlow: Unsupervised Learning of Optical Flow with a Bidirectional Census Loss This repository contains the TensorFlow implementation of the paper UnF

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

A Flow-based latent state generative model of neural population responses to natural images Code for "A Flow-based latent state generative model of ne

FlowTorch is a PyTorch library for learning and sampling from complex probability distributions using a class of methods called Normalizing Flows.

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

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

Variational Gibbs inference (VGI) This repository contains the research code for Simkus, V., Rhodes, B., Gutmann, M. U., 2021. Variational Gibbs infer

GMFlow GMFlow: Learning Optical Flow via Global Matching Authors: Haofei Xu, Jing Zhang, Jianfei Cai, Hamid Rezatofighi, Dacheng Tao We streamline the

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

Power Grid Lib - Optimal Power Flow This benchmark library is curated and maintained by the IEEE PES Task Force on Benchmarks for Validation of Emergi

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

Sylvester normalizing flows for variational inference Pytorch implementation of Sylvester normalizing flows, based on our paper: Sylvester normalizing

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

nsff_pl Neural Scene Flow Fields using pytorch-lightning. This repo reimplements the NSFF idea, but modifies several operations based on observation o

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,

Traffic Flow Test Platform Traffic flow test platform, especially for reinforcement learning, named TFTP. A traffic signal control framework that can

O365DevicePhish Microsoft365_devicePhish Abusing Microsoft 365 OAuth Authorization Flow for Phishing Attack This is a simple proof-of-concept script t

DeepSTD: Mining Spatio-temporal Disturbances of Multiple Context Factors for Citywide Traffic Flow Prediction This is the implementation of DeepSTD in

Documentation: https://mmflow.readthedocs.io/ Introduction English | 简体中文 MMFlow is an open source optical flow toolbox based on PyTorch. It is a part

Identifies the faulty wafer before it can be used for the fabrication of integrated circuits and, in photovoltaics, to manufacture solar cells. The project retrains itself after every prediction, making it more robust and generalized over time.

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

Overview Metrinome is an all-purpose tool for working with code complexity metrics. It can be used as both a REPL and API, and includes: Converters to