5 citations · 19 across the 13 of their papers we have counts for
4 papers · 1 filter
Dual-branch Hybrid Learning Network for Unbiased Scene Graph Generation
Chaofan Zheng, Lianli Gao, Xinyu Lyu +3
The current studies of Scene Graph Generation (SGG) focus on solving the long-tailed problem for generating unbiased scene graphs. However, most de-biasing methods overemphasize th…
Adaptive Fine-Grained Predicates Learning for Scene Graph Generation
Xinyu Lyu, Lianli Gao, Pengpeng Zeng +2
The performance of current Scene Graph Generation (SGG) models is severely hampered by hard-to-distinguish predicates, e.g., woman-on/standing on/walking on-beach. As general SGG m…
Learning To Generate Scene Graph from Head to Tail
Chaofan Zheng, Xinyu Lyu, Yuyu Guo +3
Scene Graph Generation (SGG) represents objects and their interactions with a graph structure. Recently, many works are devoted to solving the imbalanced problem in SGG. However, u…
Fine-Grained Predicates Learning for Scene Graph Generation
Xinyu Lyu, Lianli Gao, Yuyu Guo +4
The performance of current Scene Graph Generation models is severely hampered by some hard-to-distinguish predicates, e.g., "woman-on/standing on/walking on-beach" or "woman-near/l…