12 citations · 16 across the 4 of their papers we have counts for
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cs.CV2023★ 1 cited
Decomposed Prototype Learning for Few-Shot Scene Graph Generation
Xingchen Li, Jun Xiao, Guikun Chen +4
Today's scene graph generation (SGG) models typically require abundant manual annotations to learn new predicate types. Therefore, it is difficult to apply them to real-world appli…
cs.CV2022
Integrating Object-aware and Interaction-aware Knowledge for Weakly Supervised Scene Graph Generation
Xingchen Li, Long Chen, Wenbo Ma +2
Recently, increasing efforts have been focused on Weakly Supervised Scene Graph Generation (WSSGG). The mainstream solution for WSSGG typically follows the same pipeline: they firs…
cs.CV2022★ 3 cited
Rethinking the Evaluation of Unbiased Scene Graph Generation
Xingchen Li, Long Chen, Jian Shao +3
Current Scene Graph Generation (SGG) methods tend to predict frequent predicate categories and fail to recognize rare ones due to the severe imbalanced distribution of predicates.…