175 Repositories
Python normalization-flow Libraries
PyPSA: Python for Power System Analysis
1 Python for Power System Analysis Contents 1 Python for Power System Analysis 1.1 About 1.2 Documentation 1.3 Functionality 1.4 Example scripts as Ju
SinGlow: Generative Flow for SVS tasks in Tensorflow 2
SinGlow is a part of my Singing voice synthesis system. It can extract features of sound, particularly songs and musics. Then we can use these features (or perfect encoding) for feature migrating tasks. For example migrate features of real singers' song to those virtual singers' songs.
Angora is a mutation-based fuzzer. The main goal of Angora is to increase branch coverage by solving path constraints without symbolic execution.
Angora Angora is a mutation-based coverage guided fuzzer. The main goal of Angora is to increase branch coverage by solving path constraints without s
TensorFlow implementation of "Variational Inference with Normalizing Flows"
[TensorFlow 2] Variational Inference with Normalizing Flows TensorFlow implementation of "Variational Inference with Normalizing Flows" [1] Concept Co
Demo code for ICCV 2021 paper "Sensor-Guided Optical Flow"
Sensor-Guided Optical Flow Demo code for "Sensor-Guided Optical Flow", ICCV 2021 This code is provided to replicate results with flow hints obtained f
A fast model to compute optical flow between two input images.
DCVNet: Dilated Cost Volumes for Fast Optical Flow This repository contains our implementation of the paper: @InProceedings{jiang2021dcvnet, title={
a reimplementation of Optical Flow Estimation using a Spatial Pyramid Network in PyTorch
pytorch-spynet This is a personal reimplementation of SPyNet [1] using PyTorch. Should you be making use of this work, please cite the paper according
Know your customer pipeline in apache air flow
KYC_pipline Know your customer pipeline in apache air flow For a successful pipeline run take these steps: Run you Airflow server Admin - connection
A PyTorch implementation of the WaveGlow: A Flow-based Generative Network for Speech Synthesis
WaveGlow A PyTorch implementation of the WaveGlow: A Flow-based Generative Network for Speech Synthesis Quick Start: Install requirements: pip install
PyTorch implementations of normalizing flow and its variants.
PyTorch implementations of normalizing flow and its variants.
Pytorch implementation of FlowNet by Dosovitskiy et al.
FlowNetPytorch Pytorch implementation of FlowNet by Dosovitskiy et al. This repository is a torch implementation of FlowNet, by Alexey Dosovitskiy et
Pytorch-version BERT-flow: One can apply BERT-flow to any PLM within Pytorch framework.
Pytorch-version BERT-flow: One can apply BERT-flow to any PLM within Pytorch framework.
This python module is an easy-to-use port of the text normalization used in the paper "Not low-resource anymore: Aligner ensembling, batch filtering, and new datasets for Bengali-English machine translation". It is intended to be used for normalizing / cleaning Bengali and English text.
normalizer This python module is an easy-to-use port of the text normalization used in the paper "Not low-resource anymore: Aligner ensembling, batch
Classifying audio using Wavelet transform and deep learning
Audio Classification using Wavelet Transform and Deep Learning A step-by-step tutorial to classify audio signals using continuous wavelet transform (C
Normalization Matters in Weakly Supervised Object Localization (ICCV 2021)
Normalization Matters in Weakly Supervised Object Localization (ICCV 2021) 99% of the code in this repository originates from this link. ICCV 2021 pap
Deep Learning ❤️ OneFlow
Deep Learning with OneFlow made easy 🚀 ! Carefree? carefree-learn aims to provide CAREFREE usages for both users and developers. User Side Computer V
Official PyTorch code for Hierarchical Conditional Flow: A Unified Framework for Image Super-Resolution and Image Rescaling (HCFlow, ICCV2021)
Hierarchical Conditional Flow: A Unified Framework for Image Super-Resolution and Image Rescaling (HCFlow, ICCV2021) This repository is the official P
CrossNorm and SelfNorm for Generalization under Distribution Shifts (ICCV 2021)
CrossNorm (CN) and SelfNorm (SN) (Accepted at ICCV 2021) This is the official PyTorch implementation of our CNSN paper, in which we propose CrossNorm
Official PyTorch code for Hierarchical Conditional Flow: A Unified Framework for Image Super-Resolution and Image Rescaling (HCFlow, ICCV2021)
Hierarchical Conditional Flow: A Unified Framework for Image Super-Resolution and Image Rescaling (HCFlow, ICCV2021) This repository is the official P
CrossNorm and SelfNorm for Generalization under Distribution Shifts (ICCV 2021)
CrossNorm (CN) and SelfNorm (SN) (Accepted at ICCV 2021) This is the official PyTorch implementation of our CNSN paper, in which we propose CrossNorm
Code for "On the Effects of Batch and Weight Normalization in Generative Adversarial Networks"
Note: this repo has been discontinued, please check code for newer version of the paper here Weight Normalized GAN Code for the paper "On the Effects
Code in PyTorch for the convex combination linear IAF and the Householder Flow, J.M. Tomczak & M. Welling
VAE with Volume-Preserving Flows This is a PyTorch implementation of two volume-preserving flows as described in the following papers: Tomczak, J. M.,
Abusing Microsoft 365 OAuth Authorization Flow for Phishing Attack
Microsoft365_devicePhish Abusing Microsoft 365 OAuth Authorization Flow for Phishing Attack This is a simple proof-of-concept script that allows an at
[Preprint] "Bag of Tricks for Training Deeper Graph Neural Networks A Comprehensive Benchmark Study" by Tianlong Chen*, Kaixiong Zhou*, Keyu Duan, Wenqing Zheng, Peihao Wang, Xia Hu, Zhangyang Wang
Bag of Tricks for Training Deeper Graph Neural Networks: A Comprehensive Benchmark Study Codes for [Preprint] Bag of Tricks for Training Deeper Graph
Generative Flow Networks
Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation Implementation for our paper, submitted to NeurIPS 2021 (also chec
Phishing Abusing Microsoft 365 OAuth Authorization Flow
Microsoft365_devicePhish Abusing Microsoft 365 OAuth Authorization Flow for Phishing Attack This is a simple proof-of-concept script that allows an at
LOC-FLOW is an “hands-free” earthquake location workflow to process continuous seismic records
LOC-FLOW is an “hands-free” earthquake location workflow to process continuous seismic records: from raw waveforms to well located earthquakes with magnitude calculations. The package assembles several popular routines for sequential earthquake location refinements, suitable for catalog building ranging from local to regional scales.
PyTorch Lightning Optical Flow models, scripts, and pretrained weights.
PyTorch Lightning Optical Flow models, scripts, and pretrained weights.
Dewarping Document Image By Displacement Flow Estimation with Fully Convolutional Network
Dewarping Document Image By Displacement Flow Estimation with Fully Convolutional Network
This repository contains data used in the NAACL 2021 Paper - Proteno: Text Normalization with Limited Data for Fast Deployment in Text to Speech Systems
Proteno This is the data release associated with the corresponding NAACL 2021 Paper - Proteno: Text Normalization with Limited Data for Fast Deploymen
PyTorch implementation of the Transformer in Post-LN (Post-LayerNorm) and Pre-LN (Pre-LayerNorm).
Transformer-PyTorch A PyTorch implementation of the Transformer from the paper Attention is All You Need in both Post-LN (Post-LayerNorm) and Pre-LN (
Official PyTorch implementation of "VITON-HD: High-Resolution Virtual Try-On via Misalignment-Aware Normalization" (CVPR 2021)
VITON-HD — Official PyTorch Implementation VITON-HD: High-Resolution Virtual Try-On via Misalignment-Aware Normalization Seunghwan Choi*1, Sunghyun Pa
RIFE: Real-Time Intermediate Flow Estimation for Video Frame Interpolation
RIFE RIFE: Real-Time Intermediate Flow Estimation for Video Frame Interpolation Ported from https://github.com/hzwer/arXiv2020-RIFE Dependencies NumPy
Pytorch implementation of FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks
flownet2-pytorch Pytorch implementation of FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks. Multiple GPU training is supported, a
Official Pytorch implementation of ICLR 2018 paper Deep Learning for Physical Processes: Integrating Prior Scientific Knowledge.
Deep Learning for Physical Processes: Integrating Prior Scientific Knowledge: Official Pytorch implementation of ICLR 2018 paper Deep Learning for Phy
Stochastic Downsampling for Cost-Adjustable Inference and Improved Regularization in Convolutional Networks
Stochastic Downsampling for Cost-Adjustable Inference and Improved Regularization in Convolutional Networks (SDPoint) This repository contains the cod
A Flow-based Generative Network for Speech Synthesis
WaveGlow: a Flow-based Generative Network for Speech Synthesis Ryan Prenger, Rafael Valle, and Bryan Catanzaro In our recent paper, we propose WaveGlo
A PyTorch implementation of the WaveGlow: A Flow-based Generative Network for Speech Synthesis
WaveGlow A PyTorch implementation of the WaveGlow: A Flow-based Generative Network for Speech Synthesis Quick Start: Install requirements: pip install
Unsupervised Learning of Multi-Frame Optical Flow with Occlusions
This is a Pytorch implementation of Janai, J., Güney, F., Ranjan, A., Black, M. and Geiger, A., Unsupervised Learning of Multi-Frame Optical Flow with
Dewarping Document Image By Displacement Flow Estimation with Fully Convolutional Network.
Dewarping Document Image By Displacement Flow Estimation with Fully Convolutional Network
PyTorch implementation of Glow, Generative Flow with Invertible 1x1 Convolutions
glow-pytorch PyTorch implementation of Glow, Generative Flow with Invertible 1x1 Convolutions
box is a text-based visual programming language inspired by Unreal Engine Blueprint function graphs.
Box is a text-based visual programming language inspired by Unreal Engine blueprint function graphs. $ cat factorial.box ┌─ƒ(Factorial)───┐
Classify bird species based on their songs using SIamese Networks and 1D dilated convolutions.
The goal is to classify different birds species based on their songs/calls. Spectrograms have been extracted from the audio samples and used as features for classification.
LibTraffic is a unified, flexible and comprehensive traffic prediction library based on PyTorch
LibTraffic is a unified, flexible and comprehensive traffic prediction library, which provides researchers with a credibly experimental tool and a convenient development framework. Our library is implemented based on PyTorch, and includes all the necessary steps or components related to traffic prediction into a systematic pipeline.
MODeflattener deobfuscates control flow flattened functions obfuscated by OLLVM using Miasm.
MODeflattener deobfuscates control flow flattened functions obfuscated by OLLVM using Miasm.
[CVPR 2021] Region-aware Adaptive Instance Normalization for Image Harmonization
RainNet — Official Pytorch Implementation Region-aware Adaptive Instance Normalization for Image Harmonization Jun Ling, Han Xue, Li Song*, Rong Xie,
A lightweight deep network for fast and accurate optical flow estimation.
FastFlowNet: A Lightweight Network for Fast Optical Flow Estimation The official PyTorch implementation of FastFlowNet (ICRA 2021). Authors: Lingtong
Learning Optical Flow from a Few Matches (CVPR 2021)
Learning Optical Flow from a Few Matches This repository contains the source code for our paper: Learning Optical Flow from a Few Matches CVPR 2021 Sh
Pytorch implementation of MaskFlownet
MaskFlownet-Pytorch Unofficial PyTorch implementation of MaskFlownet (https://github.com/microsoft/MaskFlownet). Tested with: PyTorch 1.5.0 CUDA 10.1
The implemention of Video Depth Estimation by Fusing Flow-to-Depth Proposals
Flow-to-depth (FDNet) video-depth-estimation This is the implementation of paper Video Depth Estimation by Fusing Flow-to-Depth Proposals Jiaxin Xie,
Official implementation of "One-Shot Voice Conversion with Weight Adaptive Instance Normalization".
One-Shot Voice Conversion with Weight Adaptive Instance Normalization By Shengjie Huang, Yanyan Xu*, Dengfeng Ke*, Mingjie Chen, Thomas Hain. This rep
HINet: Half Instance Normalization Network for Image Restoration
HINet: Half Instance Normalization Network for Image Restoration Liangyu Chen, Xin Lu, Jie Zhang, Xiaojie Chu, Chengpeng Chen Paper: https://arxiv.org
Code for "PV-RAFT: Point-Voxel Correlation Fields for Scene Flow Estimation of Point Clouds", CVPR 2021
PV-RAFT This repository contains the PyTorch implementation for paper "PV-RAFT: Point-Voxel Correlation Fields for Scene Flow Estimation of Point Clou
Code for ACL 2021 main conference paper "Conversations are not Flat: Modeling the Intrinsic Information Flow between Dialogue Utterances".
Conversations are not Flat: Modeling the Intrinsic Information Flow between Dialogue Utterances This repository contains the code and pre-trained mode
Self-Supervised Multi-Frame Monocular Scene Flow (CVPR 2021)
Self-Supervised Multi-Frame Monocular Scene Flow 3D visualization of estimated depth and scene flow (overlayed with input image) from temporally conse
Just Go with the Flow: Self-Supervised Scene Flow Estimation
Just Go with the Flow: Self-Supervised Scene Flow Estimation Code release for the paper Just Go with the Flow: Self-Supervised Scene Flow Estimation,
[CVPRW 21] "BNN - BN = ? Training Binary Neural Networks without Batch Normalization", Tianlong Chen, Zhenyu Zhang, Xu Ouyang, Zechun Liu, Zhiqiang Shen, Zhangyang Wang
BNN - BN = ? Training Binary Neural Networks without Batch Normalization Codes for this paper BNN - BN = ? Training Binary Neural Networks without Bat
The official repo of the CVPR2021 oral paper: Representative Batch Normalization with Feature Calibration
Representative Batch Normalization (RBN) with Feature Calibration The official implementation of the CVPR2021 oral paper: Representative Batch Normali
Python bindings to libpostal for fast international address parsing/normalization
pypostal These are the official Python bindings to https://github.com/openvenues/libpostal, a fast statistical parser/normalizer for street addresses
Demo code for paper "Learning optical flow from still images", CVPR 2021.
Depthstillation Demo code for "Learning optical flow from still images", CVPR 2021. [Project page] - [Paper] - [Supplementary] This code is provided t
Towards Ultra-Resolution Neural Style Transfer via Thumbnail Instance Normalization
Towards Ultra-Resolution Neural Style Transfer via Thumbnail Instance Normalization Official PyTorch implementation for our URST (Ultra-Resolution Sty
[CVPR2021 Oral] FFB6D: A Full Flow Bidirectional Fusion Network for 6D Pose Estimation.
FFB6D This is the official source code for the CVPR2021 Oral work, FFB6D: A Full Flow Biderectional Fusion Network for 6D Pose Estimation. (Arxiv) Tab
[ICLR'21] FedBN: Federated Learning on Non-IID Features via Local Batch Normalization
FedBN: Federated Learning on Non-IID Features via Local Batch Normalization This is the PyTorch implemention of our paper FedBN: Federated Learning on
FLAVR is a fast, flow-free frame interpolation method capable of single shot multi-frame prediction
FLAVR is a fast, flow-free frame interpolation method capable of single shot multi-frame prediction. It uses a customized encoder decoder architecture with spatio-temporal convolutions and channel gating to capture and interpolate complex motion trajectories between frames to generate realistic high frame rate videos. This repository contains original source code for the paper accepted to CVPR 2021.
Official PyTorch Implementation of Unsupervised Learning of Scene Flow Estimation Fusing with Local Rigidity
UnRigidFlow This is the official PyTorch implementation of UnRigidFlow (IJCAI2019). Here are two sample results (~10MB gif for each) of our unsupervis
PyTorch implementation of paper "Neural Scene Flow Fields for Space-Time View Synthesis of Dynamic Scenes", CVPR 2021
Neural Scene Flow Fields PyTorch implementation of paper "Neural Scene Flow Fields for Space-Time View Synthesis of Dynamic Scenes", CVPR 20
Python script for Linear, Non-Linear Convection, Burger’s & Poisson Equation in 1D & 2D, 1D Diffusion Equation using Standard Wall Function, 2D Heat Conduction Convection equation with Dirichlet & Neumann BC, full Navier-Stokes Equation coupled with Poisson equation for Cavity and Channel flow in 2D using Finite Difference Method & Finite Volume Method.
Navier-Stokes-numerical-solution-using-Python- Python script for Linear, Non-Linear Convection, Burger’s & Poisson Equation in 1D & 2D, 1D D
Sandwich Batch Normalization
Sandwich Batch Normalization Code for Sandwich Batch Normalization. Introduction We present Sandwich Batch Normalization (SaBN), an extremely easy imp
Weakly Supervised Learning of Rigid 3D Scene Flow
Weakly Supervised Learning of Rigid 3D Scene Flow This repository provides code and data to train and evaluate a weakly supervised method for rigid 3D
Code for "Learning to Segment Rigid Motions from Two Frames".
rigidmask Code for "Learning to Segment Rigid Motions from Two Frames". ** This is a partial release with inference and evaluation code.
Fast and Easy Infinite Neural Networks in Python
Neural Tangents ICLR 2020 Video | Paper | Quickstart | Install guide | Reference docs | Release notes Overview Neural Tangents is a high-level neural
A Static Analysis Tool for Detecting Security Vulnerabilities in Python Web Applications
This project is no longer maintained March 2020 Update: Please go see the amazing Pysa tutorial that should get you up to speed finding security vulne
Performant type-checking for python.
Pyre is a performant type checker for Python compliant with PEP 484. Pyre can analyze codebases with millions of lines of code incrementally – providi
data/code repository of "C2F-FWN: Coarse-to-Fine Flow Warping Network for Spatial-Temporal Consistent Motion Transfer"
C2F-FWN data/code repository of "C2F-FWN: Coarse-to-Fine Flow Warping Network for Spatial-Temporal Consistent Motion Transfer" (https://arxiv.org/abs/
Performant type-checking for python.
Pyre is a performant type checker for Python compliant with PEP 484. Pyre can analyze codebases with millions of lines of code incrementally – providi