Yuqi Bu


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Segment-Level and Category-Oriented Network for Knowledge-Based Referring Expression Comprehension
Yuqi Bu | Xin Wu | Liuwu Li | Yi Cai | Qiong Liu | Qingbao Huang
Findings of the Association for Computational Linguistics: ACL 2023

Knowledge-based referring expression comprehension (KB-REC) aims to identify visual objects referred to by expressions that incorporate knowledge. Existing methods employ sentence-level retrieval and fusion methods, which may lead to issues of similarity bias and interference from irrelevant information in unstructured knowledge sentences. To address these limitations, we propose a segment-level and category-oriented network (SLCO). Our approach includes a segment-level and prompt-based knowledge retrieval method to mitigate the similarity bias problem and a category-based grounding method to alleviate interference from irrelevant information in knowledge sentences. Experimental results show that our SLCO can eliminate interference and improve the overall performance of the KB-REC task.