Python Value-Iteration-Networks-PyTorch Resources

PP-LCNet-Pytorch Pre-Trained Models Google Drive p018 Accuracy Models Top1 Top5 PPLCNet_x0_25 0.5186 0.7565 PPLCNet_x0_35 0.5809 0.8083 PPLCNet_x0_5 0

N-ImageNet: Towards Robust, Fine-Grained Object Recognition with Event Cameras Official PyTorch implementation of N-ImageNet: Towards Robust, Fine-Gra

IceVision is the first agnostic computer vision framework to offer a curated collection with hundreds of high-quality pre-trained models from torchvision, MMLabs, and soon Pytorch Image Models. It orchestrates the end-to-end deep learning workflow allowing to train networks with easy-to-use robust high-performance libraries such as Pytorch-Lightning and Fastai

ANTsPyNet A collection of deep learning architectures and applications ported to the python language and tools for basic medical image processing. Bas

Mathematical modeling is a powerful method for the analysis of complex biological systems. Although there are many researches devoted on produ

MONAI Deploy App SDK offers a framework and associated tools to design, develop and verify AI-driven applications in the healthcare imaging domain.

Unsupervised Image Generation with Infinite Generative Adversarial Networks Here is the implementation of MICGANs using DCGAN architecture on MNIST da

Official PyTorch Implementation of Learning Self-Similarity in Space and Time as Generalized Motion for Video Action Recognition, ICCV 2021

MosaicML Composer contains a library of methods, and ways to compose them together for more efficient ML training.

A collection of papers about Transformer in the field of medical image analysis.

KUIELAB-MDX-Net got the 2nd place on the Leaderboard A and the 3rd place on the Leaderboard B in the MDX-Challenge ISMIR 2021

Unofficial Implementation of MLP-Mixer, gMLP, resMLP, Vision Permutator, S2MLPv2, RaftMLP, ConvMLP, ConvMixer in Jittor and PyTorch! Now, Rearrange and Reduce in einops.layers.jittor are support!!

GUI for a Vocal Remover that uses Deep Neural Networks.

Magnetic Graph Convolutional Networks About The official PyTorch implementation for the paper sMGC: A Complex-Valued Graph Convolutional Network via M

SoGCN: Second-Order Graph Convolutional Networks This is the authors' implementation of paper "SoGCN: Second-Order Graph Convolutional Networks" in Py

DeepMoCap: Deep Optical Motion Capture using multiple Depth Sensors and Retro-reflectors By Anargyros Chatzitofis, Dimitris Zarpalas, Stefanos Kollias

GCond A PyTorch implementation of paper "Graph Condensation for Graph Neural Networks" Code will be released soon. Stay tuned :) Abstract We propose a

CONDOR pytorch implementation for ordinal regression with deep neural networks. Documentation: https://GarrettJenkinson.github.io/condor_pytorch About

Feedback Network for Image Super-Resolution [arXiv] [CVF] [Poster] Update: Our proposed Gated Multiple Feedback Network (GMFN) will appear in BMVC2019

Progressive Image Deraining Networks: A Better and Simpler Baseline [arxiv] [pdf] [supp] Introduction This paper provides a better and simpler baselin

Gated Multiple Feedback Network for Image Super-Resolution This repository contains the PyTorch implementation for the proposed GMFN [arXiv]. The fram

About PyTorch 1.2.0 Now the master branch supports PyTorch 1.2.0 by default. Due to the serious version problem (especially torch.utils.data.dataloade

Deep Adversarial Decomposition PDF | Supp | 1min-DemoVideo Pytorch implementation of the paper: "Deep Adversarial Decomposition: A Unified Framework f

Spatial Attentive Single-Image Deraining with a High Quality Real Rain Dataset (CVPR'19) Tianyu Wang*, Xin Yang*, Ke Xu, Shaozhe Chen, Qiang Zhang, Ry

EDVR has been merged into BasicSR. This GitHub repo is a mirror of BasicSR. Recommend to use BasicSR, and open issues, pull requests, etc in BasicSR.

DFN：Distributed Feedback Network for Single-Image Deraining Abstract Recently, deep convolutional neural networks have achieved great success for sing

Overview The Open Graph Benchmark (OGB) is a collection of benchmark datasets, data loaders, and evaluators for graph machine learning. Datasets cover

Graph Convolutional Networks This is a TensorFlow implementation of Graph Convolutional Networks for the task of (semi-supervised) classification of n

Simplifying Graph Convolutional Networks Updates As pointed out by #23, there was a subtle bug in our preprocessing code for the reddit dataset. After

SPAGAN in PyTorch This is a PyTorch implementation of the paper "SPAGAN: Shortest Path Graph Attention Network" Prerequisites We prefer to create a ne

Intro This repository contains code to generate data and reproduce experiments from our NeurIPS 2019 paper: Boris Knyazev, Graham W. Taylor, Mohamed R

Graph Convolutional Networks for Temporal Action Localization This repo holds the codes and models for the PGCN framework presented on ICCV 2019 Graph

Simple and Deep Graph Convolutional Networks This repository contains a PyTorch implementation of "Simple and Deep Graph Convolutional Networks".(http

Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks This repository contains a TensorFlow implementation of "

When Does Self-Supervision Help Graph Convolutional Networks? PyTorch implementation for When Does Self-Supervision Help Graph Convolutional Networks?

DropEdge: Towards Deep Graph Convolutional Networks on Node Classification This is a Pytorch implementation of paper: DropEdge: Towards Deep Graph Con

Benchmarking Graph Neural Networks Updates Nov 2, 2020 Project based on DGL 0.4.2. See the relevant dependencies defined in the environment yml files

GAT Graph Attention Networks (Veličković et al., ICLR 2018): https://arxiv.org/abs/1710.10903 GAT layer t-SNE + Attention coefficients on Cora Overvie

Residual Gated Graph ConvNets April 24, 2018 Xavier Bresson http://www.ntu.edu.sg/home/xbresson https://github.com/xbresson https://twitter.com/xbress

DeepGCNs: Can GCNs Go as Deep as CNNs? In this work, we present new ways to successfully train very deep GCNs. We borrow concepts from CNNs, mainly re

A new codebase for popular Scene Graph Generation methods (2020). Visualization & Scene Graph Extraction on custom images/datasets are provided. It's also a PyTorch implementation of paper “Unbiased Scene Graph Generation from Biased Training CVPR 2020”

Densely Connected Convolutional Networks (DenseNets) This repository contains the code for DenseNet introduced in the following paper Densely Connecte

pycls pycls is an image classification codebase, written in PyTorch. It was originally developed for the On Network Design Spaces for Visual Recogniti

Feedback Networks http://feedbacknet.stanford.edu/ Paper: Feedback Networks, CVPR 2017. Amir R. Zamir*,Te-Lin Wu*, Lin Sun, William B. Shen, Bertram E

PointRend A PyTorch implementation of PointRend: Image Segmentation as Rendering [arxiv] [Official Implementation: Detectron2] This repo for Only Sema

Deep Residual Networks with 1K Layers By Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun. Microsoft Research Asia (MSRA). Table of Contents Introduc

MicLeveler Fixes your Microphone Level to one specific value. Intention A friend of mine has the problem that some programs are setting his microphone

Collection of Docker images for ML/DL and video processing projects. Overview of images Three types of images differ by tag postfix: base: Python with

This work has now been superseded by: https://github.com/sniklaus/revisiting-sepconv sepconv-slomo This is a reference implementation of Video Frame I

revisiting-sepconv This is a reference implementation of Revisiting Adaptive Convolutions for Video Frame Interpolation [1] using PyTorch. Given two f

At Bittensor, we are creating an open, decentralized, peer-to-peer network that functions as a market system for the development of artificial intelligence.

PyTorch implementation of "LayoutTransformer: Layout Generation and Completion with Self-attention" to appear in ICCV 2021

Unofficial PyTorch implementation of SimCLR by Google Brain

SynNet This repo contains the code and analysis scripts for our amortized approach to synthetic tree generation using neural networks. Our model can s

UniSpeech The family of UniSpeech: UniSpeech (ICML 2021): Unified Pre-training for Self-Supervised Learning and Supervised Learning for ASR UniSpeech-

Optimizing Dense Retrieval Model Training with Hard Negatives Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Jiafeng Guo, Min Zhang, Shaoping Ma 🔥 News 2021-10

Variational Graph Auto-encoder in Pytorch This repository implements variational graph auto-encoder by Thomas Kipf. For details of the model, refer to

This is a repository for the paper of "Well-classified Examples are Underestimated in Classification with Deep Neural Networks" The implementation and

Fast Fourier Convolution (FFC) for Image Classification This is the official code of Fast Fourier Convolution for image classification on ImageNet. Ma

Random JSON Key:Value Pair Generator This simple script take an engish dictionary of words and and makes random key value pairs. The dictionary has ap

PyTorch implementation of PP-LCNet Reproduction of PP-LCNet architecture as described in PP-LCNet: A Lightweight CPU Convolutional Neural Network by C

Chimera: Learning Shared Semantic Space for Speech-to-Text Translation This is a Pytorch implementation for the "Chimera" paper Learning Shared Semant

MosaicML Composer MosaicML Composer contains a library of methods, and ways to compose them together for more efficient ML training. We aim to ease th

Introduction GeneralOCR is open source Optical Character Recognition based on PyTorch. It makes a fidelity and useful tool to implement SOTA models on

PointWOLF: Point Cloud Augmentation with Weighted Local Transformations This repository is the implementation of PointWOLF(To appear). Sihyeon Kim1*,

DINN We introduce Disease Informed Neural Networks (DINNs) — neural networks capable of learning how diseases spread, forecasting their progression, a

EchoVPR Repo for EchoVPR: Echo State Networks for Visual Place Recognition Currently under development Dirs: data: pre-collected hidden representation

Select, Reduce, Connect This repository contains the code used for the experiments of: "Understanding Pooling in Graph Neural Networks" Setup Install

Instance-based Label Smoothing for Neural Networks Pytorch Implementation of the algorithm. This repository includes a new proposed method for instanc

Recurrent Model-Free RL is a Strong Baseline for Many POMDPs Welcome to the POMDP world! This repo provides some simple baselines for POMDPs, specific

Introduction This project is developed based on FastReID, which is an ongoing ReID project. Projects BUC In projects/BUC, we implement AAAI 2019 paper

MMSceneGraph Introduction MMSceneneGraph is an open source code hub for scene graph generation as well as supporting downstream tasks based on the sce

3D Infomax improves GNNs for Molecular Property Prediction Video | Paper We pre-train GNNs to understand the geometry of molecules given only their 2D

DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision Paper | Project page | Demo (Youtube) | Demo (Bilib

PASS - Official PyTorch Implementation [CVPR2021 Oral] Prototype Augmentation and Self-Supervision for Incremental Learning Fei Zhu, Xu-Yao Zhang, Chu

StarterCode for VALUE Benchmark This is the starter code for VALUE Benchmark [website], [paper]. This repository currently supports all baseline model

PyDreamer Reimplementation of DreamerV2 model-based RL algorithm in PyTorch. The official DreamerV2 implementation can be found here. Features ... Run

BasicRL: easy and fundamental codes for deep reinforcement learning BasicRL is an improvement on rainbow-is-all-you-need and OpenAI Spinning Up. It is

Self-Knowledge Distillation with Progressive Refinement of Targets (PS-KD) Accepted at ICCV 2021, oral presentation Official PyTorch implementation of

Select, Reduce, Connect This repository contains the code used for the experiments of: "Understanding Pooling in Graph Neural Networks" Setup Install

AASIST This repository provides the overall framework for training and evaluating audio anti-spoofing systems proposed in 'AASIST: Audio Anti-Spoofing

StARformer This repository contains the PyTorch implementation for our paper titled StARformer: Transformer with State-Action-Reward Representations.

PyTorch implementation of our ICCV 2021 paper, Interpretation of Emergent Communication in Heterogeneous Collaborative Embodied Agents.

Large Scale Multi-Illuminant (LSMI) Dataset for Developing White Balance Algorithm under Mixed Illumination (ICCV 2021) Dataset License This work is l

🌈 ERASOR (RA-L'21 with ICRA Option) Official page of "ERASOR: Egocentric Ratio of Pseudo Occupancy-based Dynamic Object Removal for Static 3D Point C

This repository contains the source code for the paper SnowflakeNet: Point Cloud Completion by Snowflake Point Deconvolution with Skip-Transformer (ICCV 2021 Oral). The project page is here.

TRAnsformer Routing Networks (TRAR) This is an official implementation for ICCV 2021 paper "TRAR: Routing the Attention Spans in Transformers for Visu

From Two to One: A New Scene Text Recognizer with Visual Language Modeling Network The official code of VisionLAN (ICCV2021). VisionLAN successfully a

Template repository to build PyTorch projects from source on any version of PyTorch/CUDA/cuDNN.

Alias-Free Generative Adversarial Networks (StyleGAN3) Official PyTorch implementation

Permute Me Softly: Learning Soft Permutations for Graph Representations

FLAME Original Pytorch Implementation of FLAME: Facial Landmark Heatmap Activated Multimodal Gaze Estimation, accepted at the 17th IEEE Internation Co

HyperNets Hypercomplex Neural Networks with PyTorch: this repository would be a container for hypercomplex neural network modules to facilitate resear

PyTorch implementation of DUL (Data Uncertainty Learning in Face Recognition, CVPR2020)

Predictive Modeling on Electronic Health Records(EHR) using Pytorch Overview Although there are plenty of repos on vision and NLP models, there are ve

DARDet PyTorch implementation of "DARDet: A Dense Anchor-free Rotated Object Detector in Aerial Images", [pdf]. Highlights: 1. We develop a new dense

EdiTTS: Score-based Editing for Controllable Text-to-Speech Official implementation of EdiTTS: Score-based Editing for Controllable Text-to-Speech. Au

Time-stretch audio clips quickly with PyTorch (CUDA supported)! Additional utilities for searching efficient transformations are included.

Official Pytorch implementation of Meta Internal Learning

PortaSpeech - PyTorch Implementation PyTorch Implementation of PortaSpeech: Portable and High-Quality Generative Text-to-Speech. Model Size Module Nor