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Rethinking Attention Mechanism: Channel Re-Attention and Spatial Multi-Region Attention for Fine-Grained Visual Classification

https://doi.org/10.2139/ssrn.4757424
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inferredcites →https://doi.org/10.1007/978-3-030-01234-2_1openalex-extracted
CBAM: Convolutional Block Attention Module
inferredcites →https://doi.org/10.1007/978-3-030-01258-8_5openalex-extracted
Pairwise Confusion for Fine-Grained Visual Classification
inferredcites →https://doi.org/10.1007/978-3-030-01264-9_26openalex-extracted
Learning to Navigate for Fine-Grained Classification
inferredcites →https://doi.org/10.1007/978-3-030-01270-0_49openalex-extracted
Multi-Attention Multi-Class Constraint for Fine-grained Image Recognition
inferredcites →https://doi.org/10.1007/978-3-031-19803-8_11openalex-extracted
Uncertainty-DTW for Time Series and Sequences
inferredcites →https://doi.org/10.1007/978-3-031-26316-3_19openalex-extracted
Temporal-Viewpoint Transportation Plan for Skeletal Few-Shot Action Recognition
inferredcites →https://doi.org/10.1007/978-3-319-10590-1_54openalex-extracted
Part-Based R-CNNs for Fine-Grained Category Detection
inferredcites →https://doi.org/10.1109/cvpr.2015.7298775openalex-extracted
Deep LAC: Deep localization, alignment and classification for fine-grained recognition
inferredcites →https://doi.org/10.1109/cvpr.2016.90openalex-extracted
Deep Residual Learning for Image Recognition
inferredcites →https://doi.org/10.1109/cvpr.2017.243openalex-extracted
Densely Connected Convolutional Networks
inferredcites →https://doi.org/10.1109/cvpr.2017.476openalex-extracted
Look Closer to See Better: Recurrent Attention Convolutional Neural Network for Fine-Grained Image Recognition
inferredcites →https://doi.org/10.1109/cvpr.2018.00745openalex-extracted
Squeeze-and-Excitation Networks
inferredcites →https://doi.org/10.1109/cvpr.2018.00813openalex-extracted
Non-local Neural Networks
inferredcites →https://doi.org/10.1109/cvpr.2019.00530openalex-extracted
Destruction and Construction Learning for Fine-Grained Image Recognition
inferredcites →https://doi.org/10.1109/cvpr42600.2020.01048openalex-extracted
Attention Convolutional Binary Neural Tree for Fine-Grained Visual Categorization
inferredcites →https://doi.org/10.1109/cvpr52688.2022.00934openalex-extracted
A Simple Episodic Linear Probe Improves Visual Recognition in the Wild
inferredcites →https://doi.org/10.1109/cvpr52729.2023.00544openalex-extracted
3Mformer: Multi-order Multi-mode Transformer for Skeletal Action Recognition
inferredcites →https://doi.org/10.1109/cvprw.2009.5206848openalex-extracted
ImageNet: A large-scale hierarchical image database
inferredcites →https://doi.org/10.1109/iccv.2015.170openalex-extracted
Bilinear CNN Models for Fine-Grained Visual Recognition
inferredcites →https://doi.org/10.1109/iccv.2017.557openalex-extracted
Learning Multi-attention Convolutional Neural Network for Fine-Grained Image Recognition
inferredcites →https://doi.org/10.1109/iccv.2017.74openalex-extracted
Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization
inferredcites →https://doi.org/10.1109/iccv.2019.00670openalex-extracted
Selective Sparse Sampling for Fine-Grained Image Recognition
inferredcites →https://doi.org/10.1109/iccv.2019.00842openalex-extracted
Learning a Mixture of Granularity-Specific Experts for Fine-Grained Categorization
inferredcites →https://doi.org/10.1109/iccv.2019.00879openalex-extracted
Hallucinating IDT Descriptors and I3D Optical Flow Features for Action Recognition With CNNs
inferredcites →https://doi.org/10.1109/iccvw.2013.77openalex-extracted
3D Object Representations for Fine-Grained Categorization
inferredcites →https://doi.org/10.1109/tcsvt.2018.2834480openalex-extracted
Fast Fine-Grained Image Classification via Weakly Supervised Discriminative Localization
inferredcites →https://doi.org/10.1109/tcsvt.2020.3020079openalex-extracted
Food and Ingredient Joint Learning for Fine-Grained Recognition
inferredcites →https://doi.org/10.1109/tcsvt.2021.3069835openalex-extracted
Dynamic Perception Framework for Fine-Grained Recognition
inferredcites →https://doi.org/10.1109/tip.2020.2973812openalex-extracted
The Devil is in the Channels: Mutual-Channel Loss for Fine-Grained Image Classification
inferredcites →https://doi.org/10.1109/tip.2020.2996736openalex-extracted
Bi-Modal Progressive Mask Attention for Fine-Grained Recognition
inferredcites →https://doi.org/10.1109/tnnls.2022.3213563openalex-extracted
Penalizing the Hard Example But Not Too Much: A Strong Baseline for Fine-Grained Visual Classification
inferredcites →https://doi.org/10.1109/tpami.2021.3107160openalex-extracted
Tensor Representations for Action Recognition
inferredcites →https://doi.org/10.1109/tpami.2021.3107164openalex-extracted
Power Normalizations in Fine-Grained Image, Few-Shot Image and Graph Classification
inferredcites →https://doi.org/10.1109/vcip53242.2021.9675376openalex-extracted
Progressive Co-Attention Network for Fine-Grained Visual Classification
inferredcites →https://doi.org/10.1109/wacv45572.2020.9093601openalex-extracted
ELoPE: Fine-Grained Visual Classification with Efficient Localization, Pooling and Embedding
inferredcites →https://doi.org/10.1145/3446208openalex-extracted
Alignment Enhancement Network for Fine-grained Visual Categorization
inferredcites →https://doi.org/10.1145/3474085.3475572openalex-extracted
Self-supervising Action Recognition by Statistical Moment and Subspace Descriptors
inferredcites →https://doi.org/10.1609/aaai.v34i07.6712openalex-extracted
Channel Interaction Networks for Fine-Grained Image Categorization
inferredcites →https://doi.org/10.1609/aaai.v34i07.6822openalex-extracted
Filtration and Distillation: Enhancing Region Attention for Fine-Grained Visual Categorization
inferredcites →https://doi.org/10.1609/aaai.v34i07.6973openalex-extracted
Web-Supervised Network with Softly Update-Drop Training for Fine-Grained Visual Classification
inferredcites →https://doi.org/10.1609/aaai.v34i07.7016openalex-extracted
Learning Attentive Pairwise Interaction for Fine-Grained Classification
inferredcites →https://doi.org/10.24963/ijcai.2018/87openalex-extracted
Knowledge-Embedded Representation Learning for Fine-Grained Image Recognition
inferredcites →https://doi.org/10.48550/arxiv.1409.1556openalex-extracted
Very Deep Convolutional Networks for Large-Scale Image Recognition
inferredcites →https://doi.org/10.48550/arxiv.1611.05109openalex-extracted
Low-rank Bilinear Pooling for Fine-Grained Classification
inferredcites →https://doi.org/10.48550/arxiv.1901.09891openalex-extracted
See Better Before Looking Closer: Weakly Supervised Data Augmentation Network for Fine-Grained Visual Classification
inferredcites →https://doi.org/10.48550/arxiv.2102.09875openalex-extracted
Re-rank Coarse Classification with Local Region Enhanced Features for Fine-Grained Image Recognition
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