574 Repositories
Python meta-attention Libraries
Gathers machine learning and Tensorflow deep learning models for NLP problems, 1.13 Tensorflow 2.0
NLP-Models-Tensorflow, Gathers machine learning and tensorflow deep learning models for NLP problems, code simplify inside Jupyter Notebooks 100%. Tab
MVS2D: Efficient Multi-view Stereo via Attention-Driven 2D Convolutions
MVS2D: Efficient Multi-view Stereo via Attention-Driven 2D Convolutions Project Page | Paper If you find our work useful for your research, please con
Repository for the paper : Meta-FDMixup: Cross-Domain Few-Shot Learning Guided byLabeled Target Data
1 Meta-FDMIxup Repository for the paper : Meta-FDMixup: Cross-Domain Few-Shot Learning Guided byLabeled Target Data. (ACM MM 2021) paper News! the rep
Official PyTorch implementation of "The Center of Attention: Center-Keypoint Grouping via Attention for Multi-Person Pose Estimation" (ICCV 21).
CenterGroup This the official implementation of our ICCV 2021 paper The Center of Attention: Center-Keypoint Grouping via Attention for Multi-Person P
Code for "Multi-Time Attention Networks for Irregularly Sampled Time Series", ICLR 2021.
Multi-Time Attention Networks (mTANs) This repository contains the PyTorch implementation for the paper Multi-Time Attention Networks for Irregularly
Official Implementation for Fast Training of Neural Lumigraph Representations using Meta Learning.
Fast Training of Neural Lumigraph Representations using Meta Learning Project Page | Paper | Data Alexander W. Bergman, Petr Kellnhofer, Gordon Wetzst
Meta Learning Backpropagation And Improving It (VSML)
Meta Learning Backpropagation And Improving It (VSML) This is research code for the NeurIPS 2021 publication Kirsch & Schmidhuber 2021. Many concepts
This is a super simple visualization toolbox (script) for transformer attention visualization ✌
Trans_attention_vis This is a super simple visualization toolbox (script) for transformer attention visualization ✌ 1. How to prepare your attention m
RaftMLP: How Much Can Be Done Without Attention and with Less Spatial Locality?
RaftMLP RaftMLP: How Much Can Be Done Without Attention and with Less Spatial Locality? By Yuki Tatsunami and Masato Taki (Rikkyo University) [arxiv]
Python meta class and abstract method library with restrictions.
abcmeta Python meta class and abstract method library with restrictions. This library provides a restricted way to validate abstract methods. The Pyth
In this project we use both Resnet and Self-attention layer for cat, dog and flower classification.
cdf_att_classification classes = {0: 'cat', 1: 'dog', 2: 'flower'} In this project we use both Resnet and Self-attention layer for cdf-Classification.
Datasets, tools, and benchmarks for representation learning of code.
The CodeSearchNet challenge has been concluded We would like to thank all participants for their submissions and we hope that this challenge provided
GAT - Graph Attention Network (PyTorch) 💻 + graphs + 📣 = ❤️
GAT - Graph Attention Network (PyTorch) 💻 + graphs + 📣 = ❤️ This repo contains a PyTorch implementation of the original GAT paper ( 🔗 Veličković et
Fast convergence of detr with spatially modulated co-attention
Fast convergence of detr with spatially modulated co-attention Usage There are no extra compiled components in SMCA DETR and package dependencies are
SCOUTER: Slot Attention-based Classifier for Explainable Image Recognition
SCOUTER: Slot Attention-based Classifier for Explainable Image Recognition PDF Abstract Explainable artificial intelligence has been gaining attention
Custom studies about block sparse attention.
Block Sparse Attention 研究总结 本人近半年来对Block Sparse Attention(块稀疏注意力)的研究总结(持续更新中)。按时间顺序,主要分为如下三部分: PyTorch 自定义 CUDA 算子——以矩阵乘法为例 基于 Triton 的 Block Sparse A
Attention-based Transformation from Latent Features to Point Clouds (AAAI 2022)
Attention-based Transformation from Latent Features to Point Clouds This repository contains a PyTorch implementation of the paper: Attention-based Tr
Bottom-up attention model for image captioning and VQA, based on Faster R-CNN and Visual Genome
bottom-up-attention This code implements a bottom-up attention model, based on multi-gpu training of Faster R-CNN with ResNet-101, using object and at
DeepSpamReview: Detection of Fake Reviews on Online Review Platforms using Deep Learning Architectures. Summer Internship project at CoreView Systems.
Detection of Fake Reviews on Online Review Platforms using Deep Learning Architectures Dataset: https://s3.amazonaws.com/fast-ai-nlp/yelp_review_polar
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
MT-GAN-PyTorch - PyTorch Implementation of Learning to Transfer: Unsupervised Domain Translation via Meta-Learning
MT-GAN-PyTorch PyTorch Implementation of AAAI-2020 Paper "Learning to Transfer: Unsupervised Domain Translation via Meta-Learning" Dependency: Python
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
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
Web Scraping COVID 19 Meta Portal with Python
Web-Scraping-COVID-19-Meta-Portal-with-Python - Requests API and Beautiful Soup to scrape real-time COVID statistics from worldometer website and perform data cleaning and visual analysis in Jupyter notebook.
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.
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
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
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
Meta Learning for Semi-Supervised Few-Shot Classification
few-shot-ssl-public Code for paper Meta-Learning for Semi-Supervised Few-Shot Classification. [arxiv] Dependencies cv2 numpy pandas python 2.7 / 3.5+
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
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
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
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
Basic infrastructure for writing scripts in Python
Base Script Python is an excellent language that makes writing scripts very straightforward. Over the course of writing many scripts, we realized that
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
MetaMove is written in Python3 and aims at easing batch renaming operations based on file meta data.
MetaMove MetaMove is written in Python3 and aims at easing batch renaming operations based on file meta data. MetaMove abuses eval combined with f-str
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
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
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
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
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
Code for "Offline Meta-Reinforcement Learning with Advantage Weighting" [ICML 2021]
Offline Meta-Reinforcement Learning with Advantage Weighting (MACAW) MACAW code used for the experiments in the ICML 2021 paper. Installing the enviro
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
[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
Memory Efficient Attention (O(sqrt(n)) for Jax and PyTorch
Memory Efficient Attention This is unofficial implementation of Self-attention Does Not Need O(n^2) Memory for Jax and PyTorch. Implementation is almo
Code for the paper Progressive Pose Attention for Person Image Generation in CVPR19 (Oral).
Pose-Transfer Code for the paper Progressive Pose Attention for Person Image Generation in CVPR19(Oral). The paper is available here. Video generation
The official implementation of the Hybrid Self-Attention NEAT algorithm
PUREPLES - Pure Python Library for ES-HyperNEAT About This is a library of evolutionary algorithms with a focus on neuroevolution, implemented in pure
GANformer: Generative Adversarial Transformers
GANformer: Generative Adversarial Transformers Drew A. Hudson* & C. Lawrence Zitnick Update: We released the new GANformer2 paper! *I wish to thank Ch
Edge-Augmented Graph Transformer
Edge-augmented Graph Transformer Introduction This is the official implementation of the Edge-augmented Graph Transformer (EGT) as described in https:
Nystromformer: A Nystrom-based Algorithm for Approximating Self-Attention
Nystromformer: A Nystrom-based Algorithm for Approximating Self-Attention April 6, 2021 We extended segment-means to compute landmarks without requiri
Sinkhorn Transformer - Practical implementation of Sparse Sinkhorn Attention
Sinkhorn Transformer This is a reproduction of the work outlined in Sparse Sinkhorn Attention, with additional enhancements. It includes a parameteriz
An implementation of the Pay Attention when Required transformer
Pay Attention when Required (PAR) Transformer-XL An implementation of the Pay Attention when Required transformer from the paper: https://arxiv.org/pd
Fully featured implementation of Routing Transformer
Routing Transformer A fully featured implementation of Routing Transformer. The paper proposes using k-means to route similar queries / keys into the
Reproducing the Linear Multihead Attention introduced in Linformer paper (Linformer: Self-Attention with Linear Complexity)
Linear Multihead Attention (Linformer) PyTorch Implementation of reproducing the Linear Multihead Attention introduced in Linformer paper (Linformer:
DeBERTa: Decoding-enhanced BERT with Disentangled Attention
DeBERTa: Decoding-enhanced BERT with Disentangled Attention This repository is the official implementation of DeBERTa: Decoding-enhanced BERT with Dis
Examples of using sparse attention, as in "Generating Long Sequences with Sparse Transformers"
Status: Archive (code is provided as-is, no updates expected) Update August 2020: For an example repository that achieves state-of-the-art modeling pe
Reimplementation of NeurIPS'19: "Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting" by Shu et al.
[Re] Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting Reimplementation of NeurIPS'19: "Meta-Weight-Net: Learning an Explicit Mapping
PyContinual (An Easy and Extendible Framework for Continual Learning)
PyContinual (An Easy and Extendible Framework for Continual Learning) Easy to Use You can sumply change the baseline, backbone and task, and then read
[ACM MM 2021] Yes, "Attention is All You Need", for Exemplar based Colorization
Transformer for Image Colorization This is an implemention for Yes, "Attention Is All You Need", for Exemplar based Colorization, and the current soft
Mask2Former: Masked-attention Mask Transformer for Universal Image Segmentation in TensorFlow 2
Mask2Former: Masked-attention Mask Transformer for Universal Image Segmentation in TensorFlow 2 Bowen Cheng, Ishan Misra, Alexander G. Schwing, Alexan
This repository is the official implementation of the Hybrid Self-Attention NEAT algorithm.
This repository is the official implementation of the Hybrid Self-Attention NEAT algorithm. It contains the code to reproduce the results presented in the original paper: https://arxiv.org/abs/2112.03670
TRACER: Extreme Attention Guided Salient Object Tracing Network implementation in PyTorch
TRACER: Extreme Attention Guided Salient Object Tracing Network This paper was accepted at AAAI 2022 SA poster session. Datasets All datasets are avai
Artifacts for paper "MMO: Meta Multi-Objectivization for Software Configuration Tuning"
MMO: Meta Multi-Objectivization for Software Configuration Tuning This repository contains the data and code for the following paper that is currently
FinRL-Meta: A Universe for Data-Driven Financial Reinforcement Learning. 🔥
FinRL-Meta: A Universe of Market Environments. FinRL-Meta is a universe of market environments for data-driven financial reinforcement learning. Users
A repository with exploration into using transformers to predict DNA ↔ transcription factor binding
Transcription Factor binding predictions with Attention and Transformers A repository with exploration into using transformers to predict DNA ↔ transc
(Preprint) Official PyTorch implementation of "How Do Vision Transformers Work?"
(Preprint) Official PyTorch implementation of "How Do Vision Transformers Work?"
Implementation of Heterogeneous Graph Attention Network
HetGAN Implementation of Heterogeneous Graph Attention Network This is the code repository of paper "Prediction of Metro Ridership During the COVID-19
Official implementation of the paper Do pedestrians pay attention? Eye contact detection for autonomous driving
Do pedestrians pay attention? Eye contact detection for autonomous driving Official implementation of the paper Do pedestrians pay attention? Eye cont
A Dynamic Residual Self-Attention Network for Lightweight Single Image Super-Resolution
DRSAN A Dynamic Residual Self-Attention Network for Lightweight Single Image Super-Resolution Karam Park, Jae Woong Soh, and Nam Ik Cho Environments U
Codes for TIM2021 paper "Anchor-Based Spatio-Temporal Attention 3-D Convolutional Networks for Dynamic 3-D Point Cloud Sequences"
Codes for TIM2021 paper "Anchor-Based Spatio-Temporal Attention 3-D Convolutional Networks for Dynamic 3-D Point Cloud Sequences"
[KDD 2021, Research Track] DiffMG: Differentiable Meta Graph Search for Heterogeneous Graph Neural Networks
DiffMG This repository contains the code for our KDD 2021 Research Track paper: DiffMG: Differentiable Meta Graph Search for Heterogeneous Graph Neura
NeurIPS'19: Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting (Pytorch implementation for noisy labels).
Meta-Weight-Net NeurIPS'19: Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting (Official Pytorch implementation for noisy labels). The
[NeurIPS 2020] Code for the paper "Balanced Meta-Softmax for Long-Tailed Visual Recognition"
Balanced Meta-Softmax Code for the paper Balanced Meta-Softmax for Long-Tailed Visual Recognition Jiawei Ren, Cunjun Yu, Shunan Sheng, Xiao Ma, Haiyu
[CVPR 2021] MetaSAug: Meta Semantic Augmentation for Long-Tailed Visual Recognition
MetaSAug: Meta Semantic Augmentation for Long-Tailed Visual Recognition (CVPR 2021) arXiv Prerequisite PyTorch = 1.2.0 Python3 torchvision PIL argpar
Pytorch Implementations of large number classical backbone CNNs, data enhancement, torch loss, attention, visualization and some common algorithms.
Torch-template-for-deep-learning Pytorch implementations of some **classical backbone CNNs, data enhancement, torch loss, attention, visualization and
An end to end ASR Transformer model training repo
END TO END ASR TRANSFORMER 本项目基于transformer 6*encoder+6*decoder的基本结构构造的端到端的语音识别系统 Model Instructions 1.数据准备: 自行下载数据,遵循文件结构如下: ├── data │ ├── train │
Markov Attention Models
Introduction This repo contains code for reproducing the results in the paper Graphical Models with Attention for Context-Specific Independence and an
Python implementation of ADD: Frequency Attention and Multi-View based Knowledge Distillation to Detect Low-Quality Compressed Deepfake Images, AAAI2022.
ADD: Frequency Attention and Multi-View based Knowledge Distillation to Detect Low-Quality Compressed Deepfake Images Binh M. Le & Simon S. Woo, "ADD:
Bayesian Deep Learning and Deep Reinforcement Learning for Object Shape Error Response and Correction of Manufacturing Systems
Bayesian Deep Learning for Manufacturing 2.0 (dlmfg) Object Shape Error Response (OSER) Digital Lifecycle Management - In Process Quality Improvement
Unofficial implementation of "Coordinate Attention for Efficient Mobile Network Design"
Unofficial implementation of "Coordinate Attention for Efficient Mobile Network Design". CoordAttention tensorflow slim
Robust Lane Detection via Expanded Self Attention (WACV 2022)
Robust Lane Detection via Expanded Self Attention (WACV 2022) Minhyeok Lee, Junhyeop Lee, Dogyoon Lee, Woojin Kim, Sangwon Hwang, Sangyoun Lee Overvie
An Implementation of Transformer in Transformer in TensorFlow for image classification, attention inside local patches
Transformer-in-Transformer An Implementation of the Transformer in Transformer paper by Han et al. for image classification, attention inside local pa
Neural Caption Generator with Attention
Neural Caption Generator with Attention Tensorflow implementation of "Show