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Table of Contents

Introduction

PyTorchAttentionissuePR

Attention Mechanism

Paper Publish Link Main Idea Blog
Global Second-order Pooling Convolutional Networks CVPR19 GSoPNet
Neural Architecture Search for Lightweight Non-Local Networks CVPR20 AutoNL NAS+LightNL
Squeeze and Excitation Network CVPR18 SENet zhihu
Selective Kernel Network CVPR19 SKNet SE+ zhihu
Convolutional Block Attention Module ECCV18 CBAM + zhihu
BottleNeck Attention Module BMVC18 BAM + zhihu
Concurrent Spatial and Channel Squeeze & Excitation in Fully Convolutional Networks MICCAI18 scSE + zhihu
Non-local Neural Networks CVPR19 Non-Local(NL) self-attention zhihu
GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond ICCVW19 GCNet NL zhihu
CCNet: Criss-Cross Attention for Semantic Segmentation ICCV19 CCNet NL
SA-Net:shuffle attention for deep convolutional neural networks ICASSP 21 SANet SGE+channel shuffle zhihu
ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks CVPR20 ECANet SE
Spatial Group-wise Enhance: Improving Semantic Feature Learning in Convolutional Networks CoRR19 SGENet Group+spatial+channel
FcaNet: Frequency Channel Attention Networks CoRR20 FcaNet SE
$A^2\text{-}Nets$: Double Attention Networks NeurIPS18 DANet NL
Asymmetric Non-local Neural Networks for Semantic Segmentation ICCV19 APNB spp+NL
Efficient Attention: Attention with Linear Complexities CoRR18 EfficientAttention NL
Image Restoration via Residual Non-local Attention Networks ICLR19 RNAN
Exploring Self-attention for Image Recognition CVPR20 SAN
An Empirical Study of Spatial Attention Mechanisms in Deep Networks ICCV19 None MSRAself-attention
Object-Contextual Representations for Semantic Segmentation ECCV20 OCRNet
IAUnet: Global Context-Aware Feature Learning for Person Re-Identification TTNNLS20 IAUNet
ResNeSt: Split-Attention Networks CoRR20 ResNeSt SK+ResNeXt
Gather-Excite: Exploiting Feature Context in Convolutional Neural Networks NeurIPS18 GENet SE
Improving Convolutional Networks with Self-calibrated Convolutions CVPR20 SCNet
Rotate to Attend: Convolutional Triplet Attention Module WACV21 TripletAttention CHW
Dual Attention Network for Scene Segmentation CVPR19 DANet self-attention
Relation-Aware Global Attention for Person Re-identification CVPR20 RGANet reid
Attentional Feature Fusion WACV21 AFF attention
An Attentive Survey of Attention Models CoRR19 None NLP/CV/
Stand-Alone Self-Attention in Vision Models NeurIPS19 FullAttention self-attention
BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation ECCV18 BiSeNet FPN zhihu
DCANet: Learning Connected Attentions for Convolutional Neural Networks CoRR20 DCANet attention
An Empirical Study of Spatial Attention Mechanisms in Deep Networks ICCV19 None
Look closer to see better: Recurrent attention convolutional neural network for fine-grained image recognition CVPR17 Oral RA-CNN
Guided Attention Network for Object Detection and Counting on Drones ACM MM20 GANet
Attention Augmented Convolutional Networks ICCV19 AANet +
GLOBAL SELF-ATTENTION NETWORKS FOR IMAGE RECOGNITION ICLR21 GSA
Attention-Guided Hierarchical Structure Aggregation for Image Matting CVPR20 HAttMatting
Weight Excitation: Built-in Attention Mechanisms in Convolutional Neural Networks ECCV20 None SE
Expectation-Maximization Attention Networks for Semantic Segmentation ICCV19 Oral EMANet EM+Attention
Dense-and-implicit attention network AAAI 20 DIANet LSTM+SE
Coordinate Attention for Efficient Mobile Network Design CVPR21 CoordAttention
Cross-channel Communication Networks NIPS19 C3Net GNN+SE
Gated Convolutional Networks with Hybrid Connectivity for Image Classification AAAI20 HCGNet LSTM
Weighted Channel Dropout for Regularization of Deep Convolutional Neural Network AAAI19 None Dropout+SE
BA^2M: A Batch Aware Attention Module for Image Classification CVPR21 None Batchattention
EPSANetAn Efficient Pyramid Split Attention Block on Convolutional Neural Network CoRR21 EPSANet
Stand-Alone Self-Attention in Vision Models NIPS19 SASA Non-Local
ResT: An Efficient Transformer for Visual Recognition CoRR21 ResT self-attention
Spanet: Spatial Pyramid Attention Network for Enhanced Image Recognition ICME20 SPANet AAP
Space-time Mixing Attention for Video Transformer CoRR21 X-VIT Not release VIT+attention
DMSANet: Dual Multi Scale Attention Network CoRR21 Not release yet +
CompConv: A Compact Convolution Module for Efficient Feature Learning CoRR21 Not release yet res2net+ghostnet
VOLO: Vision Outlooker for Visual Recognition CoRR21 VOLO ViTAttention
Interflow: Aggregating Multi-layer Featrue Mappings with Attention Mechanism CoRR21 Not release yet attention
MUSE: Parallel Multi-Scale Attention for Sequence to Sequence Learning CoRR21 MUSE Attention NLPSA
Polarized Self-Attention: Towards High-quality Pixel-wise Regression CoRR21 PSA Pixel-wise regression
CA-Net: Comprehensive Attention Convolutional Neural Networks for Explainable Medical Image Segmentation TMI21 CA-Net Spatial Attention
BAM: A Lightweight and Efficient Balanced Attention Mechanism for Single Image Super Resolution CoRR21 BAM Super resolution
Attention as Activation CoRR21 ATAC activation + attention
Region-based Non-local Operation for Video Classification CoRR21 RNL video classification
MSAF: Multimodal Split Attention Fusion CoRR21 MSAF MultiModal
All-Attention Layer CoRR19 None Tranformer Layer
Compact Global Descriptor CoRR20 CGD add every two channel attention
SimAM: A Simple, Parameter-Free Attention Module for Convolutional Neural Networks ICML21 SimAM
Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks With Octave Convolution ICCV19 OctConv
Contextual Transformer Networks for Visual Recognition ICCV2021 CoTNet Transformernon-local
Residual Attention: A Simple but Effective Method for Multi-Label Recognition ICCV2021 CSRA
Self-supervised Equivariant Attention Mechanism for Weakly Supervised Semantic Segmentation CVPR2020 SEAM
An Attention Module for Convolutional Neural Networks ICCV2021 AW-Conv SE
Attentive Normalization Arxiv2020 None BN+Attention
Person Re-identification via Attention Pyramid TIP2021 APNet +ReID
Unifying Nonlocal Blocks for Neural Networks ICCV2021 SNL Non-Local +

Plug and Play Module

  • ACBlock
  • Swishwish Activation
  • ASPP Block
  • DepthWise Convolution
  • Fused Conv & BN
  • MixedDepthwise Convolution
  • PSP Module
  • RFBModule
  • SematicEmbbedBlock
  • SSH Context Module
  • Some other usefull tools such as concate feature mapflatten feature map
  • WeightedFeatureFusion:EfficientDetFPNfuse
  • StripPoolingCVPR2020StripPooling
  • GhostModule: CVPR2020GhostNet
  • SlimConv: SlimConv3x3
  • Context Gating video classification
  • EffNetBlock: EffNet
  • ECCV2020 BorderDet: Border aligment module
  • CVPR2019 DANet: Dual Attention
  • Object Contextual Representation for sematic segmentation: OCRModule
  • FPT: Self TransformGrounding TransformRendering Transform
  • DOConv: Depthwise Over-parameterized Convolution
  • PyConv:
  • ULSAMCNN
  • DGC: ECCV 2020
  • DCANet: ECCV 2020
  • PSConv: ECCV 2020
  • Dynamic Convolution: CVPR2020
  • CondConv: Conditionally Parameterized Convolutions for Efficient Inference

Evaluation

CIFAR10+ResNet+https://github.com/kuangliu/pytorch-cifar/

top1 acc time params(MB)
SENet18 95.28% 1:27:50 11,260,354
ResNet18 95.16% 1:13:03 11,173,962
ResNet50 95.50% 4:24:38 23,520,842
ShuffleNetV2 91.90% 1:02:50 1,263,854
GoogLeNet 91.90% 1:02:50 6,166,250
MobileNetV2 92.66% 2:04:57 2,296,922
SA-ResNet50 89.83% 2:10:07 23,528,758
SA-ResNet18 95.07% 1:39:38 11,171,394

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