967 Repositories
Python self-attention Libraries
Self-supervised learning optimally robust representations for domain generalization.
OptDom: Learning Optimal Representations for Domain Generalization This repository contains the official implementation for Optimal Representations fo
SAFL: A Self-Attention Scene Text Recognizer with Focal Loss
SAFL: A Self-Attention Scene Text Recognizer with Focal Loss This repository implements the SAFL in pytorch. Installation conda env create -f environm
Safe Local Motion Planning with Self-Supervised Freespace Forecasting, CVPR 2021
Safe Local Motion Planning with Self-Supervised Freespace Forecasting By Peiyun Hu, Aaron Huang, John Dolan, David Held, and Deva Ramanan Citing us Yo
Diverse Image Generation via Self-Conditioned GANs
Diverse Image Generation via Self-Conditioned GANs Project | Paper Diverse Image Generation via Self-Conditioned GANs Steven Liu, Tongzhou Wang, David
DAGAN - Dual Attention GANs for Semantic Image Synthesis
Contents Semantic Image Synthesis with DAGAN Installation Dataset Preparation Generating Images Using Pretrained Model Train and Test New Models Evalu
MatchGAN: A Self-supervised Semi-supervised Conditional Generative Adversarial Network
MatchGAN: A Self-supervised Semi-supervised Conditional Generative Adversarial Network This repository is the official implementation of MatchGAN: A S
Adversarial Self-Defense for Cycle-Consistent GANs
Adversarial Self-Defense for Cycle-Consistent GANs This is the official implementation of the CycleGAN robust to self-adversarial attacks used in pape
AttentionGAN for Unpaired Image-to-Image Translation & Multi-Domain Image-to-Image Translation
AttentionGAN-v2 for Unpaired Image-to-Image Translation AttentionGAN-v2 Framework The proposed generator learns both foreground and background attenti
A unified framework to jointly model images, text, and human attention traces.
connect-caption-and-trace This repository contains the reference code for our paper Connecting What to Say With Where to Look by Modeling Human Attent
Implementation of 'X-Linear Attention Networks for Image Captioning' [CVPR 2020]
Introduction This repository is for X-Linear Attention Networks for Image Captioning (CVPR 2020). The original paper can be found here. Please cite wi
Code for paper Adaptively Aligned Image Captioning via Adaptive Attention Time
Adaptively Aligned Image Captioning via Adaptive Attention Time This repository includes the implementation for Adaptively Aligned Image Captioning vi
HyperDict - Self linked dictionary in Python
Hyper Dictionary Advanced python dictionary(hash-table), which can link it-self
Tensorflow implementation of soft-attention mechanism for video caption generation.
SA-tensorflow Tensorflow implementation of soft-attention mechanism for video caption generation. An example of soft-attention mechanism. The attentio
Show-attend-and-tell - TensorFlow Implementation of "Show, Attend and Tell"
Show, Attend and Tell Update (December 2, 2016) TensorFlow implementation of Show, Attend and Tell: Neural Image Caption Generation with Visual Attent
Image captioning - Tensorflow implementation of Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
Introduction This neural system for image captioning is roughly based on the paper "Show, Attend and Tell: Neural Image Caption Generation with Visual
[3DV 2021] Channel-Wise Attention-Based Network for Self-Supervised Monocular Depth Estimation
Channel-Wise Attention-Based Network for Self-Supervised Monocular Depth Estimation This is the official implementation for the method described in Ch
AlexaUsingPython - Alexa will pay attention to your order, as: Hello Alexa, play music, Hello Alexa
AlexaUsingPython - Alexa will pay attention to your order, as: Hello Alexa, play music, Hello Alexa, what's the time? Alexa will pay attention to your order, get it, and afterward do some activity as indicated by your order.
Self-Learning - Books Papers, Courses & more I have to learn soon
Self-Learning This repository is intended to be used for personal use, all rights reserved to respective owners, please cite original authors and ask
Awesome Graph Classification - A collection of important graph embedding, classification and representation learning papers with implementations.
A collection of graph classification methods, covering embedding, deep learning, graph kernel and factorization papers
CarND-LaneLines-P1 - Lane Finding Project for Self-Driving Car ND
Finding Lane Lines on the Road Overview When we drive, we use our eyes to decide where to go. The lines on the road that show us where the lanes are a
Transformer - A TensorFlow Implementation of the Transformer: Attention Is All You Need
[UPDATED] A TensorFlow Implementation of Attention Is All You Need When I opened this repository in 2017, there was no official code yet. I tried to i
DankMemer-Farmer - Autofarm Self-Bot for Discord bot Named Dankmemer.
DankMemer-Farmer Autofarm Self-Bot for Discord bot Named Dankmemer. Warning We are not responsible if you got banned, since "self-bots" outside of the
Ethone-Selfbot - Open Source Discord Self-Bot, written in discord.py
Ethone SB Table of contents Newest open-source Discord SelfBot with useful commands and easy documentation on how to add your own and change the exist
Self Governing Neural Networks (SGNN): the Projection Layer
Self Governing Neural Networks (SGNN): the Projection Layer A SGNN's word projections preprocessing pipeline in scikit-learn In this notebook, we'll u
Offical implementation of Shunted Self-Attention via Multi-Scale Token Aggregation
Shunted Transformer This is the offical implementation of Shunted Self-Attention via Multi-Scale Token Aggregation by Sucheng Ren, Daquan Zhou, Shengf
Self-supervised Equivariant Attention Mechanism for Weakly Supervised Semantic Segmentation, CVPR 2020 (Oral)
SEAM The implementation of Self-supervised Equivariant Attention Mechanism for Weakly Supervised Semantic Segmentaion. You can also download the repos
Implementation of " SESS: Self-Ensembling Semi-Supervised 3D Object Detection" (CVPR2020 Oral)
SESS: Self-Ensembling Semi-Supervised 3D Object Detection Created by Na Zhao from National University of Singapore Introduction This repository contai
Learning to Self-Train for Semi-Supervised Few-Shot
Learning to Self-Train for Semi-Supervised Few-Shot Classification This repository contains the TensorFlow implementation for NeurIPS 2019 Paper "Lear
Implementation of ICLR 2020 paper "Revisiting Self-Training for Neural Sequence Generation"
Self-Training for Neural Sequence Generation This repo includes instructions for running noisy self-training algorithms from the following paper: Revi
Scaling and Benchmarking Self-Supervised Visual Representation Learning
FAIR Self-Supervision Benchmark is deprecated. Please see VISSL, a ground-up rewrite of benchmark in PyTorch. FAIR Self-Supervision Benchmark This cod
PyTorch implementation for Graph Contrastive Learning with Augmentations
Graph Contrastive Learning with Augmentations PyTorch implementation for Graph Contrastive Learning with Augmentations [poster] [appendix] Yuning You*
CCCL: Contrastive Cascade Graph Learning.
CCGL: Contrastive Cascade Graph Learning This repo provides a reference implementation of Contrastive Cascade Graph Learning (CCGL) framework as descr
Mixup for Supervision, Semi- and Self-Supervision Learning Toolbox and Benchmark
OpenSelfSup News Downstream tasks now support more methods(Mask RCNN-FPN, RetinaNet, Keypoints RCNN) and more datasets(Cityscapes). 'GaussianBlur' is
A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling"
SelfGNN A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling" paper, which will appear in Th
Code for ICDM2020 full paper: "Sub-graph Contrast for Scalable Self-Supervised Graph Representation Learning"
Subg-Con Sub-graph Contrast for Scalable Self-Supervised Graph Representation Learning (Jiao et al., ICDM 2020): https://arxiv.org/abs/2009.10273 Over
Graph InfoClust: Leveraging cluster-level node information for unsupervised graph representation learning
Graph-InfoClust-GIC [PAKDD 2021] PAKDD'21 version Graph InfoClust: Maximizing Coarse-Grain Mutual Information in Graphs Preprint version Graph InfoClu
Pytorch implementation of SELF-ATTENTIVE VAD, ICASSP 2021
SELF-ATTENTIVE VAD: CONTEXT-AWARE DETECTION OF VOICE FROM NOISE (ICASSP 2021) Pytorch implementation of SELF-ATTENTIVE VAD | Paper | Dataset Yong Rae
Unofficial implementation of Google "CutPaste: Self-Supervised Learning for Anomaly Detection and Localization" in PyTorch
CutPaste CutPaste: image from paper Unofficial implementation of Google's "CutPaste: Self-Supervised Learning for Anomaly Detection and Localization"
In this project, we develop a face recognize platform based on MTCNN object-detection netcwork and FaceNet self-supervised network.
模式识别大作业——人脸检测与识别平台 本项目是一个简易的人脸检测识别平台,提供了人脸信息录入和人脸识别的功能。前端采用 html+css+js,后端采用 pytorch,
Code for "SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanism"
SUGAR Code for "SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanism" Overview train.py: the cor
Implementation of paper "Self-supervised Learning on Graphs:Deep Insights and New Directions"
SelfTask-GNN A PyTorch implementation of "Self-supervised Learning on Graphs: Deep Insights and New Directions". [paper] In this paper, we first deepe
Source code of the "Graph-Bert: Only Attention is Needed for Learning Graph Representations" paper
Graph-Bert Source code of "Graph-Bert: Only Attention is Needed for Learning Graph Representations". Please check the script.py as the entry point. We
PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"
SLAPS-GNN This repo contains the implementation of the model proposed in SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks
Code for KDD'20 "Generative Pre-Training of Graph Neural Networks"
GPT-GNN: Generative Pre-Training of Graph Neural Networks GPT-GNN is a pre-training framework to initialize GNNs by generative pre-training. It can be
Official PyTorch Implementation of "Self-supervised Auxiliary Learning with Meta-paths for Heterogeneous Graphs". NeurIPS 2020.
Self-supervised Auxiliary Learning with Meta-paths for Heterogeneous Graphs This repository is the implementation of SELAR. Dasol Hwang* , Jinyoung Pa
Reference Code for AAAI-20 paper "Multi-Stage Self-Supervised Learning for Graph Convolutional Networks on Graphs with Few Labels"
Reference Code for AAAI-20 paper "Multi-Stage Self-Supervised Learning for Graph Convolutional Networks on Graphs with Few Labels" Please refer to htt
code for "Self-supervised edge features for improved Graph Neural Network training", arxivlink
Self-supervised edge features for improved Graph Neural Network training Data availability: Here is a link to the raw data for the organoids dataset.
A Self-Supervised Contrastive Learning Framework for Aspect Detection
AspDecSSCL A Self-Supervised Contrastive Learning Framework for Aspect Detection This repository is a pytorch implementation for the following AAAI'21
Self-Guided Contrastive Learning for BERT Sentence Representations
Self-Guided Contrastive Learning for BERT Sentence Representations This repository is dedicated for releasing the implementation of the models utilize
Autoregressive Predictive Coding: An unsupervised autoregressive model for speech representation learning
Autoregressive Predictive Coding This repository contains the official implementation (in PyTorch) of Autoregressive Predictive Coding (APC) proposed
Self-labelling via simultaneous clustering and representation learning. (ICLR 2020)
Self-labelling via simultaneous clustering and representation learning 🆗 🆗 🎉 NEW models (20th August 2020): Added standard SeLa pretrained torchvis
Self-supervised Label Augmentation via Input Transformations (ICML 2020)
Self-supervised Label Augmentation via Input Transformations Authors: Hankook Lee, Sung Ju Hwang, Jinwoo Shin (KAIST) Accepted to ICML 2020 Install de
Code to generate datasets used in "How Useful is Self-Supervised Pretraining for Visual Tasks?"
Synthetic dataset rendering Framework for producing the synthetic datasets used in: How Useful is Self-Supervised Pretraining for Visual Tasks? Alejan
Official code for the paper "Self-Supervised Prototypical Transfer Learning for Few-Shot Classification"
Self-Supervised Prototypical Transfer Learning for Few-Shot Classification This repository contains the reference source code and pre-trained models (
SCAN: Learning to Classify Images without Labels, incl. SimCLR. [ECCV 2020]
Learning to Classify Images without Labels This repo contains the Pytorch implementation of our paper: SCAN: Learning to Classify Images without Label
Official PyTorch implementation of the paper "Self-Supervised Relational Reasoning for Representation Learning", NeurIPS 2020 Spotlight.
Official PyTorch implementation of the paper: "Self-Supervised Relational Reasoning for Representation Learning" (2020), Patacchiola, M., and Storkey,
Joint-task Self-supervised Learning for Temporal Correspondence (NeurIPS 2019)
Joint-task Self-supervised Learning for Temporal Correspondence Project | Paper Overview Joint-task Self-supervised Learning for Temporal Corresponden
Official implementation of ACMMM'20 paper 'Self-supervised Video Representation Learning Using Inter-intra Contrastive Framework'
Self-supervised Video Representation Learning Using Inter-intra Contrastive Framework Official code for paper, Self-supervised Video Representation Le
Implementation of our paper "Video Playback Rate Perception for Self-supervised Spatio-Temporal Representation Learning".
PRP Introduction This is the implementation of our paper "Video Playback Rate Perception for Self-supervised Spatio-Temporal Representation Learning".
code for our ECCV-2020 paper: Self-supervised Video Representation Learning by Pace Prediction
Video_Pace This repository contains the code for the following paper: Jiangliu Wang, Jianbo Jiao and Yunhui Liu, "Self-Supervised Video Representation
Video Representation Learning by Recognizing Temporal Transformations. In ECCV, 2020.
Video Representation Learning by Recognizing Temporal Transformations [Project Page] Simon Jenni, Givi Meishvili, and Paolo Favaro. In ECCV, 2020. Thi
[NeurIPS'20] Self-supervised Co-Training for Video Representation Learning. Tengda Han, Weidi Xie, Andrew Zisserman.
CoCLR: Self-supervised Co-Training for Video Representation Learning This repository contains the implementation of: InfoNCE (MoCo on videos) UberNCE
Code for Paper: Self-supervised Learning of Motion Capture
Self-supervised Learning of Motion Capture This is code for the paper: Hsiao-Yu Fish Tung, Hsiao-Wei Tung, Ersin Yumer, Katerina Fragkiadaki, Self-sup
An unsupervised learning framework for depth and ego-motion estimation from monocular videos
SfMLearner This codebase implements the system described in the paper: Unsupervised Learning of Depth and Ego-Motion from Video Tinghui Zhou, Matthew
Code for the paper: Audio-Visual Scene Analysis with Self-Supervised Multisensory Features
[Paper] [Project page] This repository contains code for the paper: Andrew Owens, Alexei A. Efros. Audio-Visual Scene Analysis with Self-Supervised Mu
Codebase for ECCV18 "The Sound of Pixels"
Sound-of-Pixels Codebase for ECCV18 "The Sound of Pixels". *This repository is under construction, but the core parts are already there. Environment T
Code for the paper: Fighting Fake News: Image Splice Detection via Learned Self-Consistency
Fighting Fake News: Image Splice Detection via Learned Self-Consistency [paper] [website] Minyoung Huh *12, Andrew Liu *1, Andrew Owens1, Alexei A. Ef
Multi-task Self-supervised Object Detection via Recycling of Bounding Box Annotations (CVPR, 2019)
Multi-task Self-supervised Object Detection via Recycling of Bounding Box Annotations (CVPR 2019) To make better use of given limited labels, we propo
TensorFlow implementation of "Attention is all you need (Transformer)"
[TensorFlow 2] Attention is all you need (Transformer) TensorFlow implementation of "Attention is all you need (Transformer)" Dataset The MNIST datase
The code for SAG-DTA: Prediction of Drug–Target Affinity Using Self-Attention Graph Network.
SAG-DTA The code is the implementation for the paper 'SAG-DTA: Prediction of Drug–Target Affinity Using Self-Attention Graph Network'. Requirements py
The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.
News December 27: v1.1.0 New loss functions: CentroidTripletLoss and VICRegLoss Mean reciprocal rank + per-class accuracies See the release notes Than
XViT - Space-time Mixing Attention for Video Transformer
XViT - Space-time Mixing Attention for Video Transformer This is the official implementation of the XViT paper: @inproceedings{bulat2021space, title
Marketplace for self published books
Nile API API for the imaginary Nile marketplace for self published books. This is a project created to try out FastAPI as the post promising ASGI serv
Attention for PyTorch with Linear Memory Footprint
Attention for PyTorch with Linear Memory Footprint Unofficially implements https://arxiv.org/abs/2112.05682 to get Linear Memory Cost on Attention (+
PyTorch implementation of Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation.
ALiBi PyTorch implementation of Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation. Quickstart Clone this reposit
Modern, privacy-friendly, and detailed web analytics that works without cookies or JS.
Modern, privacy-friendly, and cookie-free web analytics. Getting started » Screenshots • Features • Office Hours Motivation There are a lot of web ana
Learning hierarchical attention for weakly-supervised chest X-ray abnormality localization and diagnosis
Hierarchical Attention Mining (HAM) for weakly-supervised abnormality localization This is the official PyTorch implementation for the HAM method. Pap
Multi-Probe Attention for Semantic Indexing
Multi-Probe Attention for Semantic Indexing About This project is developed for the topic of COVID-19 semantic indexing. Directories & files A. The di
A human-readable PyTorch implementation of "Self-attention Does Not Need O(n^2) Memory"
memory_efficient_attention.pytorch A human-readable PyTorch implementation of "Self-attention Does Not Need O(n^2) Memory" (Rabe&Staats'21). def effic
PyTorch Implementation of PIXOR: Real-time 3D Object Detection from Point Clouds
PIXOR: Real-time 3D Object Detection from Point Clouds This is a custom implementation of the paper from Uber ATG using PyTorch 1.0. It represents the
Weak-supervised Visual Geo-localization via Attention-based Knowledge Distillation
Weak-supervised Visual Geo-localization via Attention-based Knowledge Distillation Introduction WAKD is a PyTorch implementation for our ICPR-2022 pap
An self sufficient AI that crawls the web to learn how to generate art from keywords
Roxx-IO - The Smart Artist AI! TO DO / IDEAS Implement Web-Scraping Functionality Figure out a less annoying (and an off button for it) text to speech
Code release for SLIP Self-supervision meets Language-Image Pre-training
SLIP: Self-supervision meets Language-Image Pre-training What you can find in this repo: Pre-trained models (with ViT-Small, Base, Large) and code to
Self-describing JSON-RPC services made easy
ReflectRPC Self-describing JSON-RPC services made easy Contents What is ReflectRPC? Installation Features Datatypes Custom Datatypes Returning Errors
ttslearn: Library for Pythonで学ぶ音声合成 (Text-to-speech with Python)
ttslearn: Library for Pythonで学ぶ音声合成 (Text-to-speech with Python) 日本語は以下に続きます (Japanese follows) English: This book is written in Japanese and primaril
Source code of D-HAN: Dynamic News Recommendation with Hierarchical Attention Network
D-HAN The source code of D-HAN This is the source code of D-HAN: Dynamic News Recommendation with Hierarchical Attention Network. However, only the co
Self-Adaptable Point Processes with Nonparametric Time Decays
NPPDecay This is our implementation for the paper Self-Adaptable Point Processes with Nonparametric Time Decays, by Zhimeng Pan, Zheng Wang, Jeff M. P
[NeurIPS-2020] Self-paced Contrastive Learning with Hybrid Memory for Domain Adaptive Object Re-ID.
Self-paced Contrastive Learning (SpCL) The official repository for Self-paced Contrastive Learning with Hybrid Memory for Domain Adaptive Object Re-ID
Codes for “A Deeply Supervised Attention Metric-Based Network and an Open Aerial Image Dataset for Remote Sensing Change Detection”
DSAMNet The pytorch implementation for "A Deeply-supervised Attention Metric-based Network and an Open Aerial Image Dataset for Remote Sensing Change
CoANet: Connectivity Attention Network for Road Extraction From Satellite Imagery
CoANet: Connectivity Attention Network for Road Extraction From Satellite Imagery This paper (CoANet) has been published in IEEE TIP 2021. This code i
Official Pytorch implementation of the paper: "Locally Shifted Attention With Early Global Integration"
Locally-Shifted-Attention-With-Early-Global-Integration Pretrained models You can download all the models from here. Training Imagenet python -m torch
A-ESRGAN aims to provide better super-resolution images by using multi-scale attention U-net discriminators.
A-ESRGAN: Training Real-World Blind Super-Resolution with Attention-based U-net Discriminators The authors are hidden for the purpose of double blind
Tensorflow Implementation for "Pre-trained Deep Convolution Neural Network Model With Attention for Speech Emotion Recognition"
Tensorflow Implementation for "Pre-trained Deep Convolution Neural Network Model With Attention for Speech Emotion Recognition" Pre-trained Deep Convo
The code for paper "Contrastive Spatio-Temporal Pretext Learning for Self-supervised Video Representation" which is accepted by AAAI 2022
Contrastive Spatio Temporal Pretext Learning for Self-supervised Video Representation (AAAI 2022) The code for paper "Contrastive Spatio-Temporal Pret
Pytorch implementation of SenFormer: Efficient Self-Ensemble Framework for Semantic Segmentation
SenFormer: Efficient Self-Ensemble Framework for Semantic Segmentation Efficient Self-Ensemble Framework for Semantic Segmentation by Walid Bousselham
TensorFlow Implementation of "Show, Attend and Tell"
Show, Attend and Tell Update (December 2, 2016) TensorFlow implementation of Show, Attend and Tell: Neural Image Caption Generation with Visual Attent
A simple, personal chat program that runs on a single computer. No Internet, just you.
MultiChat A simple, personal chat program that runs on a single computer. No Internet, just you. Simple and Local MultiChat was created with ease of u
Graph Self-Supervised Learning for Optoelectronic Properties of Organic Semiconductors
SSL_OSC Graph Self-Supervised Learning for Optoelectronic Properties of Organic Semiconductors
[CVPR 2019 Oral] Multi-Channel Attention Selection GAN with Cascaded Semantic Guidance for Cross-View Image Translation
SelectionGAN for Guided Image-to-Image Translation CVPR Paper | Extended Paper | Guided-I2I-Translation-Papers Citation If you use this code for your
3D Human Pose Machines with Self-supervised Learning
3D Human Pose Machines with Self-supervised Learning Keze Wang, Liang Lin, Chenhan Jiang, Chen Qian, and Pengxu Wei, “3D Human Pose Machines with Self