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Published in ACM MM, 2023
TL;DR: We propose a cross-domain retrieval benchmark and a corresponding large-scale e-commerce dataset Real20M, which possesses features: (1) cross-domain and multimodal, (2) query-driven, and (3) massive and diverse. We also present a query-driven framework for aligning the product and micro-video domains.
Recommended citation: Yanzhe Chen, Huasong Zhong, Xiangteng He, Yuxin Peng and Lele Cheng, "Real20M: A Large-scale E-commerce Dataset for Cross-domain Retrieval", ACM MM 2023.
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Published in TOMM, 2024
TL;DR: This paper proposes a modeling method for interaction between local patches of fashion images, which can be well applied to fine-grained composed fashion image retrieval.
Recommended citation: Yanzhe Chen, Jiahuan Zhou and Yuxin Peng, "SPIRIT: Style-guided Patch Interaction for Fashion Image Retrieval with Text Feedback", TOMM 2024.
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Published in AAAI, 2024
TL;DR: This paper defines and analyzes the common phenomenon of “visual dominance” in the composed image retrieval task, where retrieval results are dominated by reference images and overlook the modification text. To mitigate this “visual dominance”, we propose a Fashion Enhance-and-Refine Network (FashionERN) that enhances text semantics and filters visual semantics.
Recommended citation: Yanzhe Chen, Huasong Zhong, Xiangteng He, Yuxin Peng, Jiahuan Zhou and Lele Cheng, "FashionERN: Enhance-and-Refine Network for Composed Fashion Image Retrieval", AAAI 2024.
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Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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