Summary of related papers on visual attention

Overview

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

image

πŸ”₯ (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 πŸ”₯
  • Image superresolution using very deep residual channel attention networks(ECCV2018) pdf πŸ”₯
  • Context encoding for semantic segmentation(CVPR2018) pdf πŸ”₯
  • 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 πŸ”₯
  • Spsequencenet: Semantic segmentation network on 4d point clouds(CVPR2020) pdf
  • Ecanet: Efficient channel attention for deep convolutional neural networks (CVPR2020) pdf πŸ”₯
  • Gated channel transformation for visual recognition(CVPR2020) pdf
  • Fcanet: Frequency channel attention networks(ICCV2021) pdf

Spatial attention

  • Recurrent models of visual attention(NeurIPS2014), pdf πŸ”₯
  • Show, attend and tell: Neural image caption generation with visual attention(PMLR2015) pdf πŸ”₯
  • Draw: A recurrent neural network for image generation(ICML2015) pdf πŸ”₯
  • Spatial transformer networks(NeurIPS2015) pdf πŸ”₯
  • Multiple object recognition with visual attention(ICLR2015) pdf πŸ”₯
  • Action recognition using visual attention(arXiv2015) pdf πŸ”₯
  • Videolstm convolves, attends and flows for action recognition(arXiv2016) pdf πŸ”₯
  • Look closer to see better: Recurrent attention convolutional neural network for fine-grained image recognition(CVPR2017) pdf πŸ”₯
  • Learning multi-attention convolutional neural network for fine-grained image recognition(ICCV2017) pdf πŸ”₯
  • Diversified visual attention networks for fine-grained object classification(TMM2017) pdf πŸ”₯
  • Attentional pooling for action recognition(NeurIPS2017) pdf πŸ”₯
  • Non-local neural networks(CVPR2018) pdf πŸ”₯
  • Attentional shapecontextnet for point cloud recognition(CVPR2018) pdf
  • Relation networks for object detection(CVPR2018) pdf πŸ”₯
  • a2-nets: Double attention networks(NeurIPS2018) pdf πŸ”₯
  • Attention-aware compositional network for person re-identification(CVPR2018) pdf πŸ”₯
  • Tell me where to look: Guided attention inference network(CVPR2018) pdf πŸ”₯
  • Pedestrian alignment network for large-scale person re-identification(TCSVT2018) pdf πŸ”₯
  • Learn to pay attention(ICLR2018) pdf πŸ”₯
  • Attention U-Net: Learning Where to Look for the Pancreas(MIDL2018) pdf πŸ”₯
  • Psanet: Point-wise spatial attention network for scene parsing(ECCV2018) pdf πŸ”₯
  • Self attention generative adversarial networks(ICML2019) pdf πŸ”₯
  • 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 πŸ”₯
  • 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 πŸ”₯
  • Gcnet: Non-local networks meet squeeze-excitation networks and beyond(ICCVW2019) pdf πŸ”₯
  • Asymmetric non-local neural networks for semantic segmentation(ICCV2019) pdf πŸ”₯
  • 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 πŸ”₯
  • End-to-end comparative attention networks for person re-identification(ICCV2019) pdf πŸ”₯
  • 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 πŸ”₯
  • 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 πŸ”₯
  • 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 πŸ”₯
  • An empirical study of training selfsupervised vision transformers(CVPR2021) pdf
  • Ocnet: Object context network for scene parsing(IJCV 2021) pdf πŸ”₯
  • 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 πŸ”₯
  • 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 πŸ”₯
  • Selective kernel networks,(CVPR 2019) pdf πŸ”₯
  • 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 πŸ”₯

ChannelSpatial attention

  • Residual attention network for image classification (CVPR 2017) pdf πŸ”₯
  • SCA-CNN: spatial and channel-wise attention in convolutional networks for image captioning,(CVPR 2017) pdf πŸ”₯
  • CBAM: convolutional block attention module, (ECCV 2018) pdf πŸ”₯
  • Harmonious attention network for person re-identification (CVPR 2018) pdf πŸ”₯
  • Recalibrating fully convolutional networks with spatial and channel β€œsqueeze and excitation” blocks (TMI 2018) pdf
  • Mancs: A multi-task attentional network with curriculum sampling for person re-identification (ECCV 2018) pdf πŸ”₯
  • Bam: Bottleneck attention module(BMVC 2018) pdf πŸ”₯
  • 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 πŸ”₯
  • 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 πŸ”₯
  • Diversity regularized spatiotemporal attention for video-based person re-identification (ArXiv 2018) πŸ”₯
  • 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
Optimus: the first large-scale pre-trained VAE language model

Optimus: the first pre-trained Big VAE language model This repository contains source code necessary to reproduce the results presented in the EMNLP 2

314 Dec 19, 2022
Tracking Pipeline helps you to solve the tracking problem more easily

Tracking_Pipeline Tracking_Pipeline helps you to solve the tracking problem more easily I integrate detection algorithms like: Yolov5, Yolov4, YoloX,

VNOpenAI 32 Dec 21, 2022
Multiple Object Extraction from Aerial Imagery with Convolutional Neural Networks

This is an implementation of Volodymyr Mnih's dissertation methods on his Massachusetts road & building dataset and my original methods that are publi

Shunta Saito 255 Sep 07, 2022
The PyTorch re-implement of a 3D CNN Tracker to extract coronary artery centerlines with state-of-the-art (SOTA) performance. (paper: 'Coronary artery centerline extraction in cardiac CT angiography using a CNN-based orientation classifier')

The PyTorch re-implement of a 3D CNN Tracker to extract coronary artery centerlines with state-of-the-art (SOTA) performance. (paper: 'Coronary artery centerline extraction in cardiac CT angiography

James 135 Dec 23, 2022
10th place solution for Google Smartphone Decimeter Challenge at kaggle.

Under refactoring 10th place solution for Google Smartphone Decimeter Challenge at kaggle. Google Smartphone Decimeter Challenge Global Navigation Sat

12 Oct 25, 2022
Resources related to EMNLP 2021 paper "FAME: Feature-Based Adversarial Meta-Embeddings for Robust Input Representations"

FAME: Feature-based Adversarial Meta-Embeddings This is the companion code for the experiments reported in the paper "FAME: Feature-Based Adversarial

Bosch Research 11 Nov 27, 2022
FCN (Fully Convolutional Network) is deep fully convolutional neural network architecture for semantic pixel-wise segmentation

FCN_via_Keras FCN FCN (Fully Convolutional Network) is deep fully convolutional neural network architecture for semantic pixel-wise segmentation. This

Kento Watanabe 48 Aug 30, 2022
Deep Learning Datasets Maker is a QGIS plugin to make datasets creation easier for raster and vector data.

Deep Learning Dataset Maker Deep Learning Datasets Maker is a QGIS plugin to make datasets creation easier for raster and vector data. How to use Down

deepbands 25 Dec 15, 2022
Instant-Teaching: An End-to-End Semi-Supervised Object Detection Framework

This repo is the official implementation of "Instant-Teaching: An End-to-End Semi-Supervised Object Detection Framework". @inproceedings{zhou2021insta

34 Dec 31, 2022
Fast image augmentation library and easy to use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about library: https://www.mdpi.com/2078-2489/11/2/125

Albumentations Albumentations is a Python library for image augmentation. Image augmentation is used in deep learning and computer vision tasks to inc

11.4k Jan 09, 2023
Laplace Redux -- Effortless Bayesian Deep Learning

Laplace Redux - Effortless Bayesian Deep Learning This repository contains the code to run the experiments for the paper Laplace Redux - Effortless Ba

Runa Eschenhagen 28 Dec 07, 2022
Segmentation models with pretrained backbones. Keras and TensorFlow Keras.

Python library with Neural Networks for Image Segmentation based on Keras and TensorFlow. The main features of this library are: High level API (just

Pavel Yakubovskiy 4.2k Jan 09, 2023
Python package to add text to images, textures and different backgrounds

nider Python package for text images generation and watermarking Free software: MIT license Documentation: https://nider.readthedocs.io. nider is an a

Vladyslav Ovchynnykov 131 Dec 30, 2022
TigerLily: Finding drug interactions in silico with the Graph.

Drug Interaction Prediction with Tigerlily Documentation | Example Notebook | Youtube Video | Project Report Tigerlily is a TigerGraph based system de

Benedek Rozemberczki 91 Dec 30, 2022
Code for paper [ACE: Ally Complementary Experts for Solving Long-Tailed Recognition in One-Shot] (ICCV 2021, oral))

ACE: Ally Complementary Experts for Solving Long-Tailed Recognition in One-Shot This repository is the official PyTorch implementation of ICCV-21 pape

Jiarui 21 May 09, 2022
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network

Super Resolution Examples We run this script under TensorFlow 2.0 and the TensorLayer2.0+. For TensorLayer 1.4 version, please check release. πŸš€ πŸš€ πŸš€

TensorLayer Community 2.9k Jan 08, 2023
MPRNet-Cloud-removal: Progressive cloud removal

MPRNet-Cloud-removal Progressive cloud removal Requirements 1.Pytorch = 1.0 2.Python 3 3.NVIDIA GPU + CUDA 9.0 4.Tensorboard Installation 1.Clone the

Semi 95 Dec 18, 2022
BirdCLEF 2021 - Birdcall Identification 4th place solution

BirdCLEF 2021 - Birdcall Identification 4th place solution My solution detail kaggle discussion Inference Notebook (best submission) Environment Use K

tattaka 42 Jan 02, 2023
This repository provides the official code for GeNER (an automated dataset Generation framework for NER).

GeNER This repository provides the official code for GeNER (an automated dataset Generation framework for NER). Overview of GeNER GeNER allows you to

DMIS Laboratory - Korea University 50 Nov 30, 2022
EASY - Ensemble Augmented-Shot Y-shaped Learning: State-Of-The-Art Few-Shot Classification with Simple Ingredients.

EASY - Ensemble Augmented-Shot Y-shaped Learning: State-Of-The-Art Few-Shot Classification with Simple Ingredients. This repository is the official im

Yassir BENDOU 57 Dec 26, 2022