Summary of related papers on visual attention

Overview

This repo is built for paper: Attention Mechanisms in Computer Vision: A Survey paper

image

🔥 (citations > 200)

  • TODO : Code about different attention mechanisms will come soon.
  • TODO : Code link will come soon.
  • TODO : collect more related papers. Contributions are welcome.

Channel attention

  • Squeeze-and-Excitation Networks(CVPR2018) pdf, (PAMI2019 version) pdf 🔥
  • Image superresolution using very deep residual channel attention networks(ECCV2018) pdf 🔥
  • Context encoding for semantic segmentation(CVPR2018) pdf 🔥
  • Spatio-temporal channel correlation networks for action classification(ECCV2018) pdf
  • Global second-order pooling convolutional networks(CVPR2019) pdf
  • Srm : A style-based recalibration module for convolutional neural networks(ICCV2019) pdf
  • You look twice: Gaternet for dynamic filter selection in cnns(CVPR2019) pdf
  • Second-order attention network for single image super-resolution(CVPR2019) pdf 🔥
  • Spsequencenet: Semantic segmentation network on 4d point clouds(CVPR2020) pdf
  • Ecanet: Efficient channel attention for deep convolutional neural networks (CVPR2020) pdf 🔥
  • Gated channel transformation for visual recognition(CVPR2020) pdf
  • Fcanet: Frequency channel attention networks(ICCV2021) pdf

Spatial attention

  • Recurrent models of visual attention(NeurIPS2014), pdf 🔥
  • Show, attend and tell: Neural image caption generation with visual attention(PMLR2015) pdf 🔥
  • Draw: A recurrent neural network for image generation(ICML2015) pdf 🔥
  • Spatial transformer networks(NeurIPS2015) pdf 🔥
  • Multiple object recognition with visual attention(ICLR2015) pdf 🔥
  • Action recognition using visual attention(arXiv2015) pdf 🔥
  • Videolstm convolves, attends and flows for action recognition(arXiv2016) pdf 🔥
  • Look closer to see better: Recurrent attention convolutional neural network for fine-grained image recognition(CVPR2017) pdf 🔥
  • Learning multi-attention convolutional neural network for fine-grained image recognition(ICCV2017) pdf 🔥
  • Diversified visual attention networks for fine-grained object classification(TMM2017) pdf 🔥
  • Attentional pooling for action recognition(NeurIPS2017) pdf 🔥
  • Non-local neural networks(CVPR2018) pdf 🔥
  • Attentional shapecontextnet for point cloud recognition(CVPR2018) pdf
  • Relation networks for object detection(CVPR2018) pdf 🔥
  • a2-nets: Double attention networks(NeurIPS2018) pdf 🔥
  • Attention-aware compositional network for person re-identification(CVPR2018) pdf 🔥
  • Tell me where to look: Guided attention inference network(CVPR2018) pdf 🔥
  • Pedestrian alignment network for large-scale person re-identification(TCSVT2018) pdf 🔥
  • Learn to pay attention(ICLR2018) pdf 🔥
  • Attention U-Net: Learning Where to Look for the Pancreas(MIDL2018) pdf 🔥
  • Psanet: Point-wise spatial attention network for scene parsing(ECCV2018) pdf 🔥
  • Self attention generative adversarial networks(ICML2019) pdf 🔥
  • Attentional pointnet for 3d-object detection in point clouds(CVPRW2019) pdf
  • Co-occurrent features in semantic segmentation(CVPR2019) pdf
  • Attention augmented convolutional networks(ICCV2019) pdf 🔥
  • Local relation networks for image recognition(ICCV2019) pdf
  • Latentgnn: Learning efficient nonlocal relations for visual recognition(ICML2019) pdf
  • Graph-based global reasoning networks(CVPR2019) pdf 🔥
  • Gcnet: Non-local networks meet squeeze-excitation networks and beyond(ICCVW2019) pdf 🔥
  • Asymmetric non-local neural networks for semantic segmentation(ICCV2019) pdf 🔥
  • Looking for the devil in the details: Learning trilinear attention sampling network for fine-grained image recognition(CVPR2019) pdf
  • Second-order non-local attention networks for person re-identification(ICCV2019) pdf 🔥
  • End-to-end comparative attention networks for person re-identification(ICCV2019) pdf 🔥
  • Modeling point clouds with self-attention and gumbel subset sampling(CVPR2019) pdf
  • Diagnose like a radiologist: Attention guided convolutional neural network for thorax disease classification(arXiv 2019) pdf
  • L2g autoencoder: Understanding point clouds by local-to-global reconstruction with hierarchical self-attention(arXiv 2019) pdf
  • Generative pretraining from pixels(PMLR2020) pdf
  • Exploring self-attention for image recognition(CVPR2020) pdf
  • Cf-sis: Semantic-instance segmentation of 3d point clouds by context fusion with self attention(MM20) pdf
  • Disentangled non-local neural networks(ECCV2020) pdf
  • Relation-aware global attention for person re-identification(CVPR2020) pdf
  • Segmentation transformer: Object-contextual representations for semantic segmentation(ECCV2020) pdf 🔥
  • Spatial pyramid based graph reasoning for semantic segmentation(CVPR2020) pdf
  • Self-supervised Equivariant Attention Mechanism for Weakly Supervised Semantic Segmentation(CVPR2020) pdf
  • End-to-end object detection with transformers(ECCV2020) pdf 🔥
  • Pointasnl: Robust point clouds processing using nonlocal neural networks with adaptive sampling(CVPR2020) pdf
  • Rethinking semantic segmentation from a sequence-to-sequence perspective with transformers(CVPR2021) pdf
  • An image is worth 16x16 words: Transformers for image recognition at scale(ICLR2021) pdf 🔥
  • An empirical study of training selfsupervised vision transformers(CVPR2021) pdf
  • Ocnet: Object context network for scene parsing(IJCV 2021) pdf 🔥
  • Point transformer(ICCV 2021) pdf
  • PCT: Point Cloud Transformer (CVMJ 2021) pdf
  • Pre-trained image processing transformer(CVPR 2021) pdf
  • An empirical study of training self-supervised vision transformers(ICCV 2021) pdf
  • Segformer: Simple and efficient design for semantic segmentation with transformers(arxiv 2021) pdf
  • Beit: Bert pre-training of image transformers(arxiv 2021) pdf
  • Beyond selfattention: External attention using two linear layers for visual tasks(arxiv 2021) pdf
  • Query2label: A simple transformer way to multi-label classification(arxiv 2021) pdf
  • Transformer in transformer(arxiv 2021) pdf

Temporal attention

  • Jointly attentive spatial-temporal pooling networks for video-based person re-identification (ICCV 2017) pdf 🔥
  • Video person reidentification with competitive snippet-similarity aggregation and co-attentive snippet embedding(CVPR 2018) pdf
  • Scan: Self-and-collaborative attention network for video person re-identification (TIP 2019) pdf

Branch attention

  • Training very deep networks, (NeurIPS 2015) pdf 🔥
  • Selective kernel networks,(CVPR 2019) pdf 🔥
  • CondConv: Conditionally Parameterized Convolutions for Efficient Inference (NeurIPS 2019) pdf
  • Dynamic convolution: Attention over convolution kernels (CVPR 2020) pdf
  • ResNest: Split-attention networks (arXiv 2020) pdf 🔥

ChannelSpatial attention

  • Residual attention network for image classification (CVPR 2017) pdf 🔥
  • SCA-CNN: spatial and channel-wise attention in convolutional networks for image captioning,(CVPR 2017) pdf 🔥
  • CBAM: convolutional block attention module, (ECCV 2018) pdf 🔥
  • Harmonious attention network for person re-identification (CVPR 2018) pdf 🔥
  • Recalibrating fully convolutional networks with spatial and channel “squeeze and excitation” blocks (TMI 2018) pdf
  • Mancs: A multi-task attentional network with curriculum sampling for person re-identification (ECCV 2018) pdf 🔥
  • Bam: Bottleneck attention module(BMVC 2018) pdf 🔥
  • Pvnet: A joint convolutional network of point cloud and multi-view for 3d shape recognition (ACM MM 2018) pdf
  • Learning what and where to attend,(ICLR 2019) pdf
  • Dual attention network for scene segmentation (CVPR 2019) pdf 🔥
  • Abd-net: Attentive but diverse person re-identification (ICCV 2019) pdf
  • Mixed high-order attention network for person re-identification (ICCV 2019) pdf
  • Mlcvnet: Multi-level context votenet for 3d object detection (CVPR 2020) pdf
  • Improving convolutional networks with self-calibrated convolutions (CVPR 2020) pdf
  • Relation-aware global attention for person re-identification (CVPR 2020) pdf
  • Strip Pooling: Rethinking spatial pooling for scene parsing (CVPR 2020) pdf
  • Rotate to attend: Convolutional triplet attention module, (WACV 2021) pdf
  • Coordinate attention for efficient mobile network design (CVPR 2021) pdf
  • Simam: A simple, parameter-free attention module for convolutional neural networks (ICML 2021) pdf

SpatialTemporal attention

  • An end-to-end spatio-temporal attention model for human action recognition from skeleton data(AAAI 2017) pdf 🔥
  • Diversity regularized spatiotemporal attention for video-based person re-identification (ArXiv 2018) 🔥
  • Interpretable spatio-temporal attention for video action recognition (ICCVW 2019) pdf
  • Hierarchical lstms with adaptive attention for visual captioning, (TPAMI 2020) pdf
  • Stat: Spatial-temporal attention mechanism for video captioning, (TMM 2020) pdf_link
  • Gta: Global temporal attention for video action understanding (ArXiv 2020) pdf
  • Multi-granularity reference-aided attentive feature aggregation for video-based person re-identification (CVPR 2020) pdf
  • Read: Reciprocal attention discriminator for image-to-video re-identification, (ECCV 2020) pdf
  • Decoupled spatial-temporal transformer for video inpainting (ArXiv 2021) pdf
Owner
MenghaoGuo
Second-year Ph.D candidate at G2 group, Tsinghua University.
MenghaoGuo
BERTMap: A BERT-Based Ontology Alignment System

BERTMap: A BERT-based Ontology Alignment System Important Notices The relevant paper was accepted in AAAI-2022. Arxiv version is available at: https:/

KRR 36 Dec 24, 2022
Code used to generate the results appearing in "Train longer, generalize better: closing the generalization gap in large batch training of neural networks"

Train longer, generalize better - Big batch training This is a code repository used to generate the results appearing in "Train longer, generalize bet

Elad Hoffer 145 Sep 16, 2022
A python package for generating, analyzing and visualizing building shadows

pybdshadow Introduction pybdshadow is a python package for generating, analyzing and visualizing building shadows from large scale building geographic

Qing Yu 13 Nov 30, 2022
Amazing-Python-Scripts - 🚀 Curated collection of Amazing Python scripts from Basics to Advance with automation task scripts.

📑 Introduction A curated collection of Amazing Python scripts from Basics to Advance with automation task scripts. This is your Personal space to fin

Avinash Ranjan 1.1k Dec 29, 2022
Transformer - Transformer in PyTorch

Transformer 完成进度 Embeddings and PositionalEncoding with example. MultiHeadAttent

Tianyang Li 1 Jan 06, 2022
Implementation for our ICCV 2021 paper: Dual-Camera Super-Resolution with Aligned Attention Modules

DCSR: Dual Camera Super-Resolution Implementation for our ICCV 2021 oral paper: Dual-Camera Super-Resolution with Aligned Attention Modules paper | pr

Tengfei Wang 110 Dec 20, 2022
The description of FMFCC-A (audio track of FMFCC) dataset and Challenge resluts.

FMFCC-A This project is the description of FMFCC-A (audio track of FMFCC) dataset and Challenge resluts. The FMFCC-A dataset is shared through BaiduCl

18 Dec 24, 2022
AI创造营 :Metaverse启动机之重构现世,结合PaddlePaddle 和 Wechaty 创造自己的聊天机器人

paddle-wechaty-Zodiac AI创造营 :Metaverse启动机之重构现世,结合PaddlePaddle 和 Wechaty 创造自己的聊天机器人 12星座若穿越科幻剧,会拥有什么超能力呢?快来迎接你的专属超能力吧! 现在很多年轻人都喜欢看科幻剧,像是复仇者系列,里面有很多英雄、超

105 Dec 22, 2022
Exploring whether attention is necessary for vision transformers

Do You Even Need Attention? A Stack of Feed-Forward Layers Does Surprisingly Well on ImageNet Paper/Report TL;DR We replace the attention layer in a v

Luke Melas-Kyriazi 461 Jan 07, 2023
An 16kHz implementation of HiFi-GAN for soft-vc.

HiFi-GAN An 16kHz implementation of HiFi-GAN for soft-vc. Relevant links: Official HiFi-GAN repo HiFi-GAN paper Soft-VC repo Soft-VC paper Example Usa

Benjamin van Niekerk 42 Dec 27, 2022
This code provides a PyTorch implementation for OTTER (Optimal Transport distillation for Efficient zero-shot Recognition), as described in the paper.

Data Efficient Language-Supervised Zero-Shot Recognition with Optimal Transport Distillation This repository contains PyTorch evaluation code, trainin

Meta Research 45 Dec 20, 2022
PyTorch implementation of residual gated graph ConvNets, ICLR’18

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

Xavier Bresson 112 Aug 10, 2022
[CVPR 2021] Monocular depth estimation using wavelets for efficiency

Single Image Depth Prediction with Wavelet Decomposition Michaël Ramamonjisoa, Michael Firman, Jamie Watson, Vincent Lepetit and Daniyar Turmukhambeto

Niantic Labs 205 Jan 02, 2023
Simple reference implementation of GraphSAGE.

Reference PyTorch GraphSAGE Implementation Author: William L. Hamilton Basic reference PyTorch implementation of GraphSAGE. This reference implementat

William L Hamilton 861 Jan 06, 2023
Official code repository for the EMNLP 2021 paper

Integrating Visuospatial, Linguistic and Commonsense Structure into Story Visualization PyTorch code for the EMNLP 2021 paper "Integrating Visuospatia

Adyasha Maharana 23 Dec 19, 2022
Fast, differentiable sorting and ranking in PyTorch

Torchsort Fast, differentiable sorting and ranking in PyTorch. Pure PyTorch implementation of Fast Differentiable Sorting and Ranking (Blondel et al.)

Teddy Koker 655 Jan 04, 2023
Convert BART models to ONNX with quantization. 3X reduction in size, and upto 3X boost in inference speed

fast-Bart Reduction of BART model size by 3X, and boost in inference speed up to 3X BART implementation of the fastT5 library (https://github.com/Ki6a

Siddharth Sharma 19 Dec 09, 2022
This is an official PyTorch implementation of Task-Adaptive Neural Network Search with Meta-Contrastive Learning (NeurIPS 2021, Spotlight).

NeurIPS 2021 (Spotlight): Task-Adaptive Neural Network Search with Meta-Contrastive Learning This is an official PyTorch implementation of Task-Adapti

Wonyong Jeong 15 Nov 21, 2022
Tiny Kinetics-400 for test

Kinetics-400迷你数据集 English | 简体中文 该数据集旨在解决的问题:参照Kinetics-400数据格式,训练基于自己数据的视频理解模型。 数据集介绍 Kinetics-400是视频领域benchmark常用数据集,详细介绍可以参考其官方网站Kinetics。整个数据集包含40

38 Jan 06, 2023
Template repository for managing machine learning research projects built with PyTorch-Lightning

Tutorial Repository with a minimal example for showing how to deploy training across various compute infrastructure.

Sidd Karamcheti 3 Feb 11, 2022