457 Repositories
Python multihead-attention Libraries
Code for the paper "MASTER: Multi-Aspect Non-local Network for Scene Text Recognition" (Pattern Recognition 2021)
MASTER-PyTorch PyTorch reimplementation of "MASTER: Multi-Aspect Non-local Network for Scene Text Recognition" (Pattern Recognition 2021). This projec
Implementation of Cross Transformer for spatially-aware few-shot transfer, in Pytorch
Cross Transformers - Pytorch (wip) Implementation of Cross Transformer for spatially-aware few-shot transfer, in Pytorch Install $ pip install cross-t
Tool for visualizing attention in the Transformer model (BERT, GPT-2, Albert, XLNet, RoBERTa, CTRL, etc.)
Tool for visualizing attention in the Transformer model (BERT, GPT-2, Albert, XLNet, RoBERTa, CTRL, etc.)
Implementation of TransGanFormer, an all-attention GAN that combines the finding from the recent GanFormer and TransGan paper
TransGanFormer (wip) Implementation of TransGanFormer, an all-attention GAN that combines the finding from the recent GansFormer and TransGan paper. I
Official PyTorch implementation for Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers, a novel method to visualize any Transformer-based network. Including examples for DETR, VQA.
PyTorch Implementation of Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers 1 Using Colab Please notic
Code for the paper "Graph Attention Tracking". (CVPR2021)
SiamGAT 1. Environment setup This code has been tested on Ubuntu 16.04, Python 3.5, Pytorch 1.2.0, CUDA 9.0. Please install related libraries before r
Implementation of the Swin Transformer in PyTorch.
Swin Transformer - PyTorch Implementation of the Swin Transformer architecture. This paper presents a new vision Transformer, called Swin Transformer,
Implementation of STAM (Space Time Attention Model), a pure and simple attention model that reaches SOTA for video classification
STAM - Pytorch Implementation of STAM (Space Time Attention Model), yet another pure and simple SOTA attention model that bests all previous models in
Implementation of LambdaNetworks, a new approach to image recognition that reaches SOTA with less compute
Lambda Networks - Pytorch Implementation of λ Networks, a new approach to image recognition that reaches SOTA on ImageNet. The new method utilizes λ l
An implementation of Performer, a linear attention-based transformer, in Pytorch
Performer - Pytorch An implementation of Performer, a linear attention-based transformer variant with a Fast Attention Via positive Orthogonal Random
Reformer, the efficient Transformer, in Pytorch
Reformer, the Efficient Transformer, in Pytorch This is a Pytorch implementation of Reformer https://openreview.net/pdf?id=rkgNKkHtvB It includes LSH
git《Self-Attention Attribution: Interpreting Information Interactions Inside Transformer》(AAAI 2021) GitHub:
Self-Attention Attribution This repository contains the implementation for AAAI-2021 paper Self-Attention Attribution: Interpreting Information Intera
The open source code of SA-UNet: Spatial Attention U-Net for Retinal Vessel Segmentation.
SA-UNet: Spatial Attention U-Net for Retinal Vessel Segmentation(ICPR 2020) Overview This code is for the paper: Spatial Attention U-Net for Retinal V
Implementation of the 😇 Attention layer from the paper, Scaling Local Self-Attention For Parameter Efficient Visual Backbones
HaloNet - Pytorch Implementation of the Attention layer from the paper, Scaling Local Self-Attention For Parameter Efficient Visual Backbones. This re
Visual Attention based OCR
Attention-OCR Authours: Qi Guo and Yuntian Deng Visual Attention based OCR. The model first runs a sliding CNN on the image (images are resized to hei
A Tensorflow model for text recognition (CNN + seq2seq with visual attention) available as a Python package and compatible with Google Cloud ML Engine.
Attention-based OCR Visual attention-based OCR model for image recognition with additional tools for creating TFRecords datasets and exporting the tra
🖺 OCR using tensorflow with attention
tensorflow-ocr 🖺 OCR using tensorflow with attention, batteries included Installation git clone --recursive http://github.com/pannous/tensorflow-ocr
Single Shot Text Detector with Regional Attention
Single Shot Text Detector with Regional Attention Introduction SSTD is initially described in our ICCV 2017 spotlight paper. A third-party implementat
Implement 'Single Shot Text Detector with Regional Attention, ICCV 2017 Spotlight'
SSTDNet Implement 'Single Shot Text Detector with Regional Attention, ICCV 2017 Spotlight' using pytorch. This code is work for general object detecti
textspotter - An End-to-End TextSpotter with Explicit Alignment and Attention
An End-to-End TextSpotter with Explicit Alignment and Attention This is initially described in our CVPR 2018 paper. Getting Started Installation Clone
Pytorch implementation of PSEnet with Pyramid Attention Network as feature extractor
Scene Text-Spotting based on PSEnet+CRNN Pytorch implementation of an end to end Text-Spotter with a PSEnet text detector and CRNN text recognizer. We
MORAN: A Multi-Object Rectified Attention Network for Scene Text Recognition
MORAN: A Multi-Object Rectified Attention Network for Scene Text Recognition Python 2.7 Python 3.6 MORAN is a network with rectification mechanism for
Adaptive Attention Span for Reinforcement Learning
Adaptive Transformers in RL Official implementation of Adaptive Transformers in RL In this work we replicate several results from Stabilizing Transfor
CVPR 2021: "Generating Diverse Structure for Image Inpainting With Hierarchical VQ-VAE"
Diverse Structure Inpainting ArXiv | Papar | Supplementary Material | BibTex This repository is for the CVPR 2021 paper, "Generating Diverse Structure
[ICLR 2021] Is Attention Better Than Matrix Decomposition?
Enjoy-Hamburger 🍔 Official implementation of Hamburger, Is Attention Better Than Matrix Decomposition? (ICLR 2021) Under construction. Introduction T
Implementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch
Implementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch
Official implementation of Self-supervised Graph Attention Networks (SuperGAT), ICLR 2021.
SuperGAT Official implementation of Self-supervised Graph Attention Networks (SuperGAT). This model is presented at How to Find Your Friendly Neighbor
Object-Centric Learning with Slot Attention
Slot Attention This is a re-implementation of "Object-Centric Learning with Slot Attention" in PyTorch (https://arxiv.org/abs/2006.15055). Requirement
Code for our CVPR2021 paper coordinate attention
Coordinate Attention for Efficient Mobile Network Design (preprint) This repository is a PyTorch implementation of our coordinate attention (will appe
Implementation of Perceiver, General Perception with Iterative Attention, in Pytorch
Perceiver - Pytorch Implementation of Perceiver, General Perception with Iterative Attention, in Pytorch Install $ pip install perceiver-pytorch Usage
Implementation of OmniNet, Omnidirectional Representations from Transformers, in Pytorch
Omninet - Pytorch Implementation of OmniNet, Omnidirectional Representations from Transformers, in Pytorch. The authors propose that we should be atte
GANsformer: Generative Adversarial Transformers Drew A
GANsformer: Generative Adversarial Transformers Drew A. Hudson* & C. Lawrence Zitnick *I wish to thank Christopher D. Manning for the fruitf
Implementation of Transformer in Transformer, pixel level attention paired with patch level attention for image classification, in Pytorch
Transformer in Transformer Implementation of Transformer in Transformer, pixel level attention paired with patch level attention for image c
An attempt at the implementation of Glom, Geoffrey Hinton's new idea that integrates neural fields, predictive coding, top-down-bottom-up, and attention (consensus between columns)
GLOM - Pytorch (wip) An attempt at the implementation of Glom, Geoffrey Hinton's new idea that integrates neural fields, predictive coding,
Implementation of E(n)-Transformer, which extends the ideas of Welling's E(n)-Equivariant Graph Neural Network to attention
E(n)-Equivariant Transformer (wip) Implementation of E(n)-Equivariant Transformer, which extends the ideas from Welling's E(n)-Equivariant G
Pytorch Code for "Medical Transformer: Gated Axial-Attention for Medical Image Segmentation"
Medical-Transformer Pytorch Code for the paper "Medical Transformer: Gated Axial-Attention for Medical Image Segmentation" About this repo: This repo
Implementation of TimeSformer, a pure attention-based solution for video classification
TimeSformer - Pytorch Implementation of TimeSformer, a pure and simple attention-based solution for reaching SOTA on video classification.
Implementation of Nyström Self-attention, from the paper Nyströmformer
Nyström Attention Implementation of Nyström Self-attention, from the paper Nyströmformer. Yannic Kilcher video Install $ pip install nystrom-attention
Implementation of self-attention mechanisms for general purpose. Focused on computer vision modules. Ongoing repository.
Self-attention building blocks for computer vision applications in PyTorch Implementation of self attention mechanisms for computer vision in PyTorch
计算机视觉中用到的注意力模块和其他即插即用模块PyTorch Implementation Collection of Attention Module and Plug&Play Module
PyTorch实现多种计算机视觉中网络设计中用到的Attention机制,还收集了一些即插即用模块。由于能力有限精力有限,可能很多模块并没有包括进来,有任何的建议或者改进,可以提交issue或者进行PR。
Sequence-to-sequence framework with a focus on Neural Machine Translation based on Apache MXNet
Sockeye This package contains the Sockeye project, an open-source sequence-to-sequence framework for Neural Machine Translation based on Apache MXNet
text_recognition_toolbox: The reimplementation of a series of classical scene text recognition papers with Pytorch in a uniform way.
text recognition toolbox 1. 项目介绍 该项目是基于pytorch深度学习框架,以统一的改写方式实现了以下6篇经典的文字识别论文,论文的详情如下。该项目会持续进行更新,欢迎大家提出问题以及对代码进行贡献。 模型 论文标题 发表年份 模型方法划分 CRNN 《An End-t
Implementation of TabTransformer, attention network for tabular data, in Pytorch
Tab Transformer Implementation of Tab Transformer, attention network for tabular data, in Pytorch. This simple architecture came within a hair's bread
Code for our ICASSP 2021 paper: SA-Net: Shuffle Attention for Deep Convolutional Neural Networks
SA-Net: Shuffle Attention for Deep Convolutional Neural Networks (paper) By Qing-Long Zhang and Yu-Bin Yang [State Key Laboratory for Novel Software T
Authors implementation of LieTransformer: Equivariant Self-Attention for Lie Groups
LieTransformer This repository contains the implementation of the LieTransformer used for experiments in the paper LieTransformer: Equivariant self-at
Sequence-to-sequence framework with a focus on Neural Machine Translation based on Apache MXNet
Sockeye This package contains the Sockeye project, an open-source sequence-to-sequence framework for Neural Machine Translation based on Apache MXNet
Implementation of Feedback Transformer in Pytorch
Feedback Transformer - Pytorch Simple implementation of Feedback Transformer in Pytorch. They improve on Transformer-XL by having each token have acce
FcaNet: Frequency Channel Attention Networks
FcaNet: Frequency Channel Attention Networks PyTorch implementation of the paper "FcaNet: Frequency Channel Attention Networks". Simplest usage Models
Implementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch
DALL-E in Pytorch Implementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch. It will also contain CLIP for ranking the ge
Implementation of Bottleneck Transformer in Pytorch
Bottleneck Transformer - Pytorch Implementation of Bottleneck Transformer, SotA visual recognition model with convolution + attention that outperforms
Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting
Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting This is the origin Pytorch implementation of Informer in the followin
Implementation of the Point Transformer layer, in Pytorch
Point Transformer - Pytorch Implementation of the Point Transformer self-attention layer, in Pytorch. The simple circuit above seemed to have allowed
Graph Transformer Architecture. Source code for
Graph Transformer Architecture Source code for the paper "A Generalization of Transformer Networks to Graphs" by Vijay Prakash Dwivedi and Xavier Bres
Implementation of SE3-Transformers for Equivariant Self-Attention, in Pytorch.
SE3 Transformer - Pytorch Implementation of SE3-Transformers for Equivariant Self-Attention, in Pytorch. May be needed for replicating Alphafold2 resu
Implementation of Lie Transformer, Equivariant Self-Attention, in Pytorch
Lie Transformer - Pytorch (wip) Implementation of Lie Transformer, Equivariant Self-Attention, in Pytorch. Only the SE3 version will be present in thi
Graph neural network message passing reframed as a Transformer with local attention
Adjacent Attention Network An implementation of a simple transformer that is equivalent to graph neural network where the message passing is done with
Machine learning, in numpy
numpy-ml Ever wish you had an inefficient but somewhat legible collection of machine learning algorithms implemented exclusively in NumPy? No? Install