Search Results for author: Xuejing Liu

Found 4 papers, 4 papers with code

Entity-enhanced Adaptive Reconstruction Network for Weakly Supervised Referring Expression Grounding

1 code implementation18 Jul 2022 Xuejing Liu, Liang Li, Shuhui Wang, Zheng-Jun Zha, Zechao Li, Qi Tian, Qingming Huang

Second, most previous weakly supervised REG methods ignore the discriminative location and context of the referent, causing difficulties in distinguishing the target from other same-category objects.

Referring Expression Semantic Similarity +1

Knowledge-guided Pairwise Reconstruction Network for Weakly Supervised Referring Expression Grounding

1 code implementation5 Sep 2019 Xuejing Liu, Liang Li, Shuhui Wang, Zheng-Jun Zha, Li Su, Qingming Huang

Weakly supervised referring expression grounding (REG) aims at localizing the referential entity in an image according to linguistic query, where the mapping between the image region (proposal) and the query is unknown in the training stage.

Referring Expression Region Proposal

Adaptive Reconstruction Network for Weakly Supervised Referring Expression Grounding

1 code implementation ICCV 2019 Xuejing Liu, Liang Li, Shuhui Wang, Zheng-Jun Zha, Dechao Meng, Qingming Huang

It builds the correspondence between image region proposal and query in an adaptive manner: adaptive grounding and collaborative reconstruction.

Referring Expression Region Proposal

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