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Learning Feature Embedding with Strong Neural Activations ...
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由 C Shen 著作2017被引用 14 次 — We present that the novel feature embedding can dramatically enlarge the gap between inter-class variance and intra-class variance, which is the key factor to ...
(PDF) Learning Feature Embedding with Strong Neural ...
ResearchGate
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2017年10月23日 — We present that the novel feature embedding can dramatically enlarge the gap between inter-class variance and intra-class variance, which is the ...
Learning Feature Embedding with Strong Neural Activations for ...
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An effective feature embedding is proposed by simultaneously encoding original global features and discriminative local features, in which the local ...
Revision History for Learning Feature Embedding with...
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To attack this issue, we propose an effective feature embedding by simultaneously encoding original global features and discriminative local features, in which ...
Open-Set Fine-Grained Retrieval via Prompting Vision ...
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由 S Wang 著作2023被引用 18 次 — Open-set fine-grained retrieval is an emerging challenge that requires an extra capability to retrieve unknown sub- categories during evaluation.
11 頁
Illustration of feature embedding and multi-task framework.
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Recent studies in image retrieval task have shown that ensembling different models and combining multiple global descriptors lead to performance improvement.
Dual Attention Networks for Few-Shot Fine-Grained ...
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由 SL Xu 著作2022被引用 30 次 — By performing meta-learning in an end-to-end manner, we can learn a good image embedding in such a metric space to gen- eralize to novel fine-grained classes.
Embedding Label Structures for Fine-Grained Feature ...
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The proposed multitask learning framework significantly outperforms previous fine-grained feature representations for image retrieval at different levels of ...
Content-Aware Rectified Activation for Zero-Shot Fine-Grained ...
ACM Digital Library
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Fine-grained image retrieval mainly focuses on learning salient features ... embedding with strong neural activations for fine-grained retrieval,” in Proc.
Learning to Parameterize Visual Attributes for Open-set ...
NIPS papers
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由 S Wang 著作2024被引用 3 次 — Fine-grained image retrieval attempts to build a well-generalized embedding space where the vi- sual discrepancies among categories are clearly reflected.
14 頁