2928 Repositories
Python pix2pix-pytorch Libraries
Python scripts form performing stereo depth estimation using the high res stereo model in PyTorch .
PyTorch-High-Res-Stereo-Depth-Estimation Python scripts form performing stereo depth estimation using the high res stereo model in PyTorch. Stereo dep
official Pytorch implementation of ICCV 2021 paper FuseFormer: Fusing Fine-Grained Information in Transformers for Video Inpainting.
FuseFormer: Fusing Fine-Grained Information in Transformers for Video Inpainting By Rui Liu, Hanming Deng, Yangyi Huang, Xiaoyu Shi, Lewei Lu, Wenxiu
An easy way to build PyTorch datasets. Modularly build datasets and automatically cache processed results
EasyDatas An easy way to build PyTorch datasets. Modularly build datasets and automatically cache processed results Installation pip install git+https
Cookiecutter PyTorch Lightning
Cookiecutter PyTorch Lightning Instructions # install cookiecutter pip install cookiecutter
✨Rubrix is a production-ready Python framework for exploring, annotating, and managing data in NLP projects.
✨A Python framework to explore, label, and monitor data for NLP projects
Decentralized Reinforcment Learning: Global Decision-Making via Local Economic Transactions (ICML 2020)
Decentralized Reinforcement Learning This is the code complementing the paper Decentralized Reinforcment Learning: Global Decision-Making via Local Ec
Official PyTorch implementation of the Fishr regularization for out-of-distribution generalization
Fishr: Invariant Gradient Variances for Out-of-distribution Generalization Official PyTorch implementation of the Fishr regularization for out-of-dist
Unofficial pytorch implementation of paper "One-Shot Free-View Neural Talking-Head Synthesis for Video Conferencing"
One-Shot Free-View Neural Talking Head Synthesis Unofficial pytorch implementation of paper "One-Shot Free-View Neural Talking-Head Synthesis for Vide
CMT: Convolutional Neural Networks Meet Vision Transformers
CMT: Convolutional Neural Networks Meet Vision Transformers [arxiv] 1. Introduction This repo is the CMT model which impelement with pytorch, no refer
[ICCV 2021] Encoder-decoder with Multi-level Attention for 3D Human Shape and Pose Estimation
MAED: Encoder-decoder with Multi-level Attention for 3D Human Shape and Pose Estimation Getting Started Our codes are implemented and tested with pyth
PyTorch implementation of "Representing Shape Collections with Alignment-Aware Linear Models" paper.
deep-linear-shapes PyTorch implementation of "Representing Shape Collections with Alignment-Aware Linear Models" paper. If you find this code useful i
PocketNet: Extreme Lightweight Face Recognition Network using Neural Architecture Search and Multi-Step Knowledge Distillation
PocketNet This is the official repository of the paper: PocketNet: Extreme Lightweight Face Recognition Network using Neural Architecture Search and M
TorchIO is a Medical image preprocessing and augmentation toolkit for deep learning. Part of the PyTorch Ecosystem.
Medical image preprocessing and augmentation toolkit for deep learning. Part of the PyTorch Ecosystem.
Lightweight stereo matching network based on MobileNetV1 and MobileNetV2
MobileStereoNet: Towards Lightweight Deep Networks for Stereo Matching
A Simplied Framework of GAN Inversion
Framework of GAN Inversion Introcuction You can implement your own inversion idea using our repo. We offer a full range of tuning settings (in hparams
Implementation of "A Deep Learning Loss Function based on Auditory Power Compression for Speech Enhancement" by pytorch
This repository is used to suspend the results of our paper "A Deep Learning Loss Function based on Auditory Power Compression for Speech Enhancement"
PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations
PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations
MWPToolkit is a PyTorch-based toolkit for Math Word Problem (MWP) solving.
MWPToolkit is a PyTorch-based toolkit for Math Word Problem (MWP) solving. It is a comprehensive framework for research purpose that integrates popular MWP benchmark datasets and typical deep learning-based MWP algorithms.
The (Official) PyTorch Implementation of the paper "Deep Extraction of Manga Structural Lines"
MangaLineExtraction_PyTorch The (Official) PyTorch Implementation of the paper "Deep Extraction of Manga Structural Lines" Usage model_torch.py [sourc
[ACMMM 2021 Oral] Enhanced Invertible Encoding for Learned Image Compression
InvCompress Official Pytorch Implementation for "Enhanced Invertible Encoding for Learned Image Compression", ACMMM 2021 (Oral) Figure: Our framework
Deployment of PyTorch chatbot with Flask
Chatbot Deployment with Flask and JavaScript In this tutorial we deploy the chatbot I created in this tutorial with Flask and JavaScript. This gives 2
An efficient framework for reinforcement learning.
rl: An efficient framework for reinforcement learning Requirements Introduction PPO Test Requirements name version Python =3.7 numpy =1.19 torch =1
Bayesian Neural Networks in PyTorch
We present the new scheme to compute Monte Carlo estimator in Bayesian VI settings with almost no memory cost in GPU, regardles of the number of sampl
Ptorch NLU, a Chinese text classification and sequence annotation toolkit, supports multi class and multi label classification tasks of Chinese long text and short text, and supports sequence annotation tasks such as Chinese named entity recognition, part of speech tagging and word segmentation.
Pytorch-NLU,一个中文文本分类、序列标注工具包,支持中文长文本、短文本的多类、多标签分类任务,支持中文命名实体识别、词性标注、分词等序列标注任务。 Ptorch NLU, a Chinese text classification and sequence annotation toolkit, supports multi class and multi label classification tasks of Chinese long text and short text, and supports sequence annotation tasks such as Chinese named entity recognition, part of speech tagging and word segmentation.
超轻量级bert的pytorch版本,大量中文注释,容易修改结构,持续更新
bert4pytorch 2021年8月27更新: 感谢大家的star,最近有小伙伴反映了一些小的bug,我也注意到了,奈何这个月工作上实在太忙,更新不及时,大约会在9月中旬集中更新一个只需要pip一下就完全可用的版本,然后会新添加一些关键注释。 再增加对抗训练的内容,更新一个完整的finetune
Official PyTorch code for Mutual Affine Network for Spatially Variant Kernel Estimation in Blind Image Super-Resolution (MANet, ICCV2021)
Mutual Affine Network for Spatially Variant Kernel Estimation in Blind Image Super-Resolution (MANet, ICCV2021) This repository is the official PyTorc
SummerTime - Text Summarization Toolkit for Non-experts
A library to help users choose appropriate summarization tools based on their specific tasks or needs. Includes models, evaluation metrics, and datasets.
Unoffical implementation about Image Super-Resolution via Iterative Refinement by Pytorch
Image Super-Resolution via Iterative Refinement Paper | Project Brief This is a unoffical implementation about Image Super-Resolution via Iterative Re
[ICCV21] Self-Calibrating Neural Radiance Fields
Self-Calibrating Neural Radiance Fields, ICCV, 2021 Project Page | Paper | Video Author Information Yoonwoo Jeong [Google Scholar] Seokjun Ahn [Google
[CVPR 2021] Official PyTorch Implementation for "Iterative Filter Adaptive Network for Single Image Defocus Deblurring"
IFAN: Iterative Filter Adaptive Network for Single Image Defocus Deblurring Checkout for the demo (GUI/Google Colab)! The GUI version might occasional
Code for Blind Image Decomposition (BID) and Blind Image Decomposition network (BIDeN).
arXiv, porject page, paper Blind Image Decomposition (BID) Blind Image Decomposition is a novel task. The task requires separating a superimposed imag
[ICCV 2021] Official PyTorch implementation for Deep Relational Metric Learning.
Deep Relational Metric Learning This repository is the official PyTorch implementation of Deep Relational Metric Learning. Framework Datasets CUB-200-
Semantic Segmentation with Pytorch-Lightning
This is a simple demo for performing semantic segmentation on the Kitti dataset using Pytorch-Lightning and optimizing the neural network by monitoring and comparing runs with Weights & Biases.
🌈 PyTorch Implementation for EMNLP'21 Findings "Reasoning Visual Dialog with Sparse Graph Learning and Knowledge Transfer"
SGLKT-VisDial Pytorch Implementation for the paper: Reasoning Visual Dialog with Sparse Graph Learning and Knowledge Transfer Gi-Cheon Kang, Junseok P
Unofficial PyTorch implementation of Fastformer based on paper "Fastformer: Additive Attention Can Be All You Need"."
Fastformer-PyTorch Unofficial PyTorch implementation of Fastformer based on paper Fastformer: Additive Attention Can Be All You Need. Usage : import t
Unofficial implementation of Perceiver IO: A General Architecture for Structured Inputs & Outputs
Perceiver IO Unofficial implementation of Perceiver IO: A General Architecture for Structured Inputs & Outputs Usage import torch from src.perceiver.
Robust Video Matting in PyTorch, TensorFlow, TensorFlow.js, ONNX, CoreML!
Robust Video Matting (RVM) English | 中文 Official repository for the paper Robust High-Resolution Video Matting with Temporal Guidance. RVM is specific
The official repository for our paper "The Devil is in the Detail: Simple Tricks Improve Systematic Generalization of Transformers". We significantly improve the systematic generalization of transformer models on a variety of datasets using simple tricks and careful considerations.
Codebase for training transformers on systematic generalization datasets. The official repository for our EMNLP 2021 paper The Devil is in the Detail:
Unofficial PyTorch Implementation of UnivNet: A Neural Vocoder with Multi-Resolution Spectrogram Discriminators for High-Fidelity Waveform Generation
UnivNet UnivNet: A Neural Vocoder with Multi-Resolution Spectrogram Discriminators for High-Fidelity Waveform Generation This is an unofficial PyTorch
MIMO-UNet - Official Pytorch Implementation
MIMO-UNet - Official Pytorch Implementation This repository provides the official PyTorch implementation of the following paper: Rethinking Coarse-to-
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
Official implementation of the MM'21 paper Constrained Graphic Layout Generation via Latent Optimization
[MM'21] Constrained Graphic Layout Generation via Latent Optimization This repository provides the official code for the paper "Constrained Graphic La
Official implementation of deep Gaussian process (DGP)-based multi-speaker speech synthesis with PyTorch.
Multi-speaker DGP This repository provides official implementation of deep Gaussian process (DGP)-based multi-speaker speech synthesis with PyTorch. O
(ICCV'21) Official PyTorch implementation of Relational Embedding for Few-Shot Classification
Relational Embedding for Few-Shot Classification (ICCV 2021) Dahyun Kang, Heeseung Kwon, Juhong Min, Minsu Cho [paper], [project hompage] We propose t
The source code of CVPR 2019 paper "Deep Exemplar-based Video Colorization".
Deep Exemplar-based Video Colorization (Pytorch Implementation) Paper | Pretrained Model | Youtube video 🔥 | Colab demo Deep Exemplar-based Video Col
CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms
CARLA - Counterfactual And Recourse Library CARLA is a python library to benchmark counterfactual explanation and recourse models. It comes out-of-the
[ICCV 2021] Official Pytorch implementation for Discriminative Region-based Multi-Label Zero-Shot Learning SOTA results on NUS-WIDE and OpenImages
Discriminative Region-based Multi-Label Zero-Shot Learning (ICCV 2021) [arXiv][Project page coming soon] Sanath Narayan*, Akshita Gupta*, Salman Kh
Implementation of Fast Transformer in Pytorch
Fast Transformer - Pytorch Implementation of Fast Transformer in Pytorch. This only work as an encoder. Yannic video AI Epiphany Install $ pip install
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
[ICCV 2021] Official Pytorch implementation for Discriminative Region-based Multi-Label Zero-Shot Learning SOTA results on NUS-WIDE and OpenImages
Discriminative Region-based Multi-Label Zero-Shot Learning (ICCV 2021) [arXiv][Project page coming soon] Sanath Narayan*, Akshita Gupta*, Salman Kh
Robust Video Matting in PyTorch, TensorFlow, TensorFlow.js, ONNX, CoreML!
Robust Video Matting in PyTorch, TensorFlow, TensorFlow.js, ONNX, CoreML!
PyNIF3D is an open-source PyTorch-based library for research on neural implicit functions (NIF)-based 3D geometry representation.
PyNIF3D is an open-source PyTorch-based library for research on neural implicit functions (NIF)-based 3D geometry representation. It aims to accelerate research by providing a modular design that allows for easy extension and combination of NIF-related components, as well as readily available paper implementations and dataset loaders.
TorchDistiller - a collection of the open source pytorch code for knowledge distillation, especially for the perception tasks, including semantic segmentation, depth estimation, object detection and instance segmentation.
This project is a collection of the open source pytorch code for knowledge distillation, especially for the perception tasks, including semantic segmentation, depth estimation, object detection and instance segmentation.
Base pretrained models and datasets in pytorch (MNIST, SVHN, CIFAR10, CIFAR100, STL10, AlexNet, VGG16, VGG19, ResNet, Inception, SqueezeNet)
This is a playground for pytorch beginners, which contains predefined models on popular dataset. Currently we support mnist, svhn cifar10, cifar100 st
Neural Turing Machine (NTM) & Differentiable Neural Computer (DNC) with pytorch & visdom
Neural Turing Machine (NTM) & Differentiable Neural Computer (DNC) with pytorch & visdom Sample on-line plotting while training(avg loss)/testing(writ
Minimal But Practical Image Classifier Pipline Using Pytorch, Finetune on ResNet18, Got 99% Accuracy on Own Small Datasets.
PyTorch Image Classifier Updates As for many users request, I released a new version of standared pytorch immage classification example at here: http:
PyTorch Implementation of CycleGAN and SSGAN for Domain Transfer (Minimal)
MNIST-to-SVHN and SVHN-to-MNIST PyTorch Implementation of CycleGAN and Semi-Supervised GAN for Domain Transfer. Prerequites Python 3.5 PyTorch 0.1.12
Implement Decoupled Neural Interfaces using Synthetic Gradients in Pytorch
disclaimer: this code is modified from pytorch-tutorial Image classification with synthetic gradient in Pytorch I implement the Decoupled Neural Inter
A pytorch implementation of Paper "Improved Training of Wasserstein GANs"
WGAN-GP An pytorch implementation of Paper "Improved Training of Wasserstein GANs". Prerequisites Python, NumPy, SciPy, Matplotlib A recent NVIDIA GPU
Intent parsing and slot filling in PyTorch with seq2seq + attention
PyTorch Seq2Seq Intent Parsing Reframing intent parsing as a human - machine translation task. Work in progress successor to torch-seq2seq-intent-pars
Re-implementation of the Noise Contrastive Estimation algorithm for pyTorch, following "Noise-contrastive estimation: A new estimation principle for unnormalized statistical models." (Gutmann and Hyvarinen, AISTATS 2010)
Noise Contrastive Estimation for pyTorch Overview This repository contains a re-implementation of the Noise Contrastive Estimation algorithm, implemen
Molecular AutoEncoder in PyTorch
MolEncoder Molecular AutoEncoder in PyTorch Install $ git clone https://github.com/cxhernandez/molencoder.git && cd molencoder $ python setup.py insta
Implementations of polygamma, lgamma, and beta functions for PyTorch
lgamma Implementations of polygamma, lgamma, and beta functions for PyTorch. It's very hacky, but that's usually ok for research use. To build, run: .
A3C LSTM Atari with Pytorch plus A3G design
NEWLY ADDED A3G A NEW GPU/CPU ARCHITECTURE OF A3C FOR SUBSTANTIALLY ACCELERATED TRAINING!! RL A3C Pytorch NEWLY ADDED A3G!! New implementation of A3C
Transfer Learning Shootout for PyTorch's model zoo (torchvision)
pytorch-retraining Transfer Learning shootout for PyTorch's model zoo (torchvision). Load any pretrained model with custom final layer (num_classes) f
Many Class Activation Map methods implemented in Pytorch for CNNs and Vision Transformers. Including Grad-CAM, Grad-CAM++, Score-CAM, Ablation-CAM and XGrad-CAM
Class Activation Map methods implemented in Pytorch pip install grad-cam ⭐ Tested on many Common CNN Networks and Vision Transformers. ⭐ Includes smoo
PyTorch implementation of Interpretable Explanations of Black Boxes by Meaningful Perturbation
PyTorch implementation of Interpretable Explanations of Black Boxes by Meaningful Perturbation The paper: https://arxiv.org/abs/1704.03296 What makes
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.,
Pytorch implementation of "A simple neural network module for relational reasoning" (Relational Networks)
Pytorch implementation of Relational Networks - A simple neural network module for relational reasoning Implemented & tested on Sort-of-CLEVR task. So
Visual Question Answering in Pytorch
Visual Question Answering in pytorch /!\ New version of pytorch for VQA available here: https://github.com/Cadene/block.bootstrap.pytorch This repo wa
Principled Detection of Out-of-Distribution Examples in Neural Networks
ODIN: Out-of-Distribution Detector for Neural Networks This is a PyTorch implementation for detecting out-of-distribution examples in neural networks.
Accelerate Neural Net Training by Progressively Freezing Layers
FreezeOut A simple technique to accelerate neural net training by progressively freezing layers. This repository contains code for the extended abstra
Pytorch implementation of "Forward Thinking: Building and Training Neural Networks One Layer at a Time"
forward-thinking-pytorch Pytorch implementation of Forward Thinking: Building and Training Neural Networks One Layer at a Time Requirements Python 2.7
PyTorch Implement of Context Encoders: Feature Learning by Inpainting
Context Encoders: Feature Learning by Inpainting This is the Pytorch implement of CVPR 2016 paper on Context Encoders 1) Semantic Inpainting Demo Inst
A PyTorch implementation of the Transformer model in "Attention is All You Need".
Attention is all you need: A Pytorch Implementation This is a PyTorch implementation of the Transformer model in "Attention is All You Need" (Ashish V
PyTorch implementation of Neural Combinatorial Optimization with Reinforcement Learning.
neural-combinatorial-rl-pytorch PyTorch implementation of Neural Combinatorial Optimization with Reinforcement Learning. I have implemented the basic
Sequence-to-Sequence learning using PyTorch
Seq2Seq in PyTorch This is a complete suite for training sequence-to-sequence models in PyTorch. It consists of several models and code to both train
A pytorch implementation of Pytorch-Sketch-RNN
Pytorch-Sketch-RNN A pytorch implementation of https://arxiv.org/abs/1704.03477 In order to draw other things than cats, you will find more drawing da
PyTorch Implementation of [1611.06440] Pruning Convolutional Neural Networks for Resource Efficient Inference
PyTorch implementation of [1611.06440 Pruning Convolutional Neural Networks for Resource Efficient Inference] This demonstrates pruning a VGG16 based
A pytorch implementation of Reading Wikipedia to Answer Open-Domain Questions.
DrQA A pytorch implementation of the ACL 2017 paper Reading Wikipedia to Answer Open-Domain Questions (DrQA). Reading comprehension is a task to produ
PyTorch implementation of SampleRNN: An Unconditional End-to-End Neural Audio Generation Model
samplernn-pytorch A PyTorch implementation of SampleRNN: An Unconditional End-to-End Neural Audio Generation Model. It's based on the reference implem
pytorch implementation for Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network arXiv:1609.04802
PyTorch SRResNet Implementation of Paper: "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network"(https://arxiv.org/abs
PyTorch Code for the paper "VSE++: Improving Visual-Semantic Embeddings with Hard Negatives"
Improving Visual-Semantic Embeddings with Hard Negatives Code for the image-caption retrieval methods from VSE++: Improving Visual-Semantic Embeddings
Pytorch implementation of Distributed Proximal Policy Optimization
Pytorch-DPPO Pytorch implementation of Distributed Proximal Policy Optimization: https://arxiv.org/abs/1707.02286 Using PPO with clip loss (from https
Unsupervised Image-to-Image Translation
UNIT: UNsupervised Image-to-image Translation Networks Imaginaire Repository We have a reimplementation of the UNIT method that is more performant. It
A memory-efficient implementation of DenseNets
efficient_densenet_pytorch A PyTorch =1.0 implementation of DenseNets, optimized to save GPU memory. Recent updates Now works on PyTorch 1.0! It uses
Temporal Segment Networks (TSN) in PyTorch
TSN-Pytorch We have released MMAction, a full-fledged action understanding toolbox based on PyTorch. It includes implementation for TSN as well as oth
A PyTorch implementation of the paper "Semantic Image Synthesis via Adversarial Learning" in ICCV 2017
Semantic Image Synthesis via Adversarial Learning This is a PyTorch implementation of the paper Semantic Image Synthesis via Adversarial Learning. Req
A PyTorch implementation of a Factorization Machine module in cython.
fmpytorch A library for factorization machines in pytorch. A factorization machine is like a linear model, except multiplicative interaction terms bet
Oriented Response Networks, in CVPR 2017
Oriented Response Networks [Home] [Project] [Paper] [Supp] [Poster] Torch Implementation The torch branch contains: the official torch implementation
PyTorch implementation of the supervised learning experiments from the paper Model-Agnostic Meta-Learning (MAML)
pytorch-maml This is a PyTorch implementation of the supervised learning experiments from the paper Model-Agnostic Meta-Learning (MAML): https://arxiv
Collection of generative models in Pytorch version.
pytorch-generative-model-collections Original : [Tensorflow version] Pytorch implementation of various GANs. This repository was re-implemented with r
Pytorch implementation of winner from VQA Chllange Workshop in CVPR'17
2017 VQA Challenge Winner (CVPR'17 Workshop) pytorch implementation of Tips and Tricks for Visual Question Answering: Learnings from the 2017 Challeng
PyTorch implementation of Tacotron speech synthesis model.
tacotron_pytorch PyTorch implementation of Tacotron speech synthesis model. Inspired from keithito/tacotron. Currently not as much good speech quality
PyTorch implementation of PSPNet segmentation network
pspnet-pytorch PyTorch implementation of PSPNet segmentation network Original paper Pyramid Scene Parsing Network Details This is a slightly different
Implementation of Fast Transformer in Pytorch
Fast Transformer - Pytorch Implementation of Fast Transformer in Pytorch. This only work as an encoder. Yannic video AI Epiphany Install $ pip install
An AutoML Library made with Optuna and PyTorch Lightning
An AutoML Library made with Optuna and PyTorch Lightning Installation Recommended pip install -U gradsflow From source pip install git+https://github.
Unofficial Alias-Free GAN implementation. Based on rosinality's version with expanded training and inference options.
Alias-Free GAN An unofficial version of Alias-Free Generative Adversarial Networks (https://arxiv.org/abs/2106.12423). This repository was heavily bas
Official PyTorch code for WACV 2022 paper "CFLOW-AD: Real-Time Unsupervised Anomaly Detection with Localization via Conditional Normalizing Flows"
CFLOW-AD: Real-Time Unsupervised Anomaly Detection with Localization via Conditional Normalizing Flows WACV 2022 preprint:https://arxiv.org/abs/2107.1
Simple tool/toolkit for evaluating NLG (Natural Language Generation) offering various automated metrics.
Simple tool/toolkit for evaluating NLG (Natural Language Generation) offering various automated metrics. Jury offers a smooth and easy-to-use interface. It uses datasets for underlying metric computation, and hence adding custom metric is easy as adopting datasets.Metric.