[논문 정리] Delving into Multimodal Prompting for Fine-grained Visual Classification

논문정보Delving into Multimodal Prompting for Fine-grained Visual Classification Delving into Multimodal Prompting for Fine-grained Visual ClassificationFine-grained visual classification (FGVC) involves categorizing fine subdivisions within a broader category, which poses challenges due to subtle inter-class discrepancies and large intra-class variations. However, prevailing approaches primarily fo..

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• · 2024. 8. 22.
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Distract your attention: Multi-head cross attention network for facial expression recognition

논문정보 Distract your attention: Multi-head cross attention network for facial expression recognition Distract Your Attention: Multi-head Cross Attention Network for Facial Expression Recognition We present a novel facial expression recognition network, called Distract your Attention Network (DAN). Our method is based on two key observations. Firstly, multiple classes share inherently similar under..

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• · 2023. 10. 17.
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[논문 정리] Learning enhanced features and inferring twice for fine-grained image classification

논문정보 Learning enhanced features and inferring twice for fine-grained image classification X-MOL www.x-mol.net GitHub - boxyao/Forcing-Network Contribute to boxyao/Forcing-Network development by creating an account on GitHub. github.com 논문정리 Abstract FGVC는 비슷한 같은 카테고리에 속하는 데이터들의 하위 카테고리를 구별하는 것을 목표로 한다. 현재 연구는 FGVC에서 차별성있는 특징이 중요하다는 것을 입증했지만, 그 외 특징들 또한 올바른 분류에 기여할 수 있다는 것을 간과하였으며, 추출된 특징들은 미묘한 영..

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• · 2023. 8. 31.
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[논문 정리] Fine-grained Visual Classification with High-temperature Refinement and Background Suppression

논문정보 Fine-grained Visual Classification with High-temperature Refinement and Background Suppression Fine-grained Visual Classification with High-temperature Refinement and Background Suppression Fine-grained visual classification is a challenging task due to the high similarity between categories and distinct differences among data within one single category. To address the challenges, previous ..

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• · 2023. 5. 26.
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[논문 정리] Object-Part Attention Model for Fine-grained Image Classification

논문정보 Object-Part Attention Model for Fine-grained Image Classification Object-Part Attention Model for Fine-grained Image Classification Fine-grained image classification is to recognize hundreds of subcategories belonging to the same basic-level category, such as 200 subcategories belonging to the bird, which is highly challenging due to large variance in the same subcategory and small var arxi..

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• · 2023. 4. 18.
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[논문 정리] Dual Cross-Attention Learning for Fine-Grained Visual Categorization andObject Re-Identification

보호되어 있는 글입니다.

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• · 2023. 2. 28.