16 citations · 34 across the 6 of their papers we have counts for
6 papers
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…
One-shot Scene Graph Generation
Yuyu Guo, Jingkuan Song, Lianli Gao +1
As a structured representation of the image content, the visual scene graph (visual relationship) acts as a bridge between computer vision and natural language processing. Existing…
Exploiting long-term temporal dynamics for video captioning
Yuyu Guo, Jingqiu Zhang, Lianli Gao
Automatically describing videos with natural language is a fundamental challenge for computer vision and natural language processing. Recently, progress in this problem has been ac…
Relation Regularized Scene Graph Generation
Yuyu Guo, Lianli Gao, Jingkuan Song +4
Scene graph generation (SGG) is built on top of detected objects to predict object pairwise visual relations for describing the image content abstraction. Existing works have revea…
From General to Specific: Informative Scene Graph Generation via Balance Adjustment
Yuyu Guo, Lianli Gao, Xuanhan Wang +5
The scene graph generation (SGG) task aims to detect visual relationship triplets, i.e., subject, predicate, object, in an image, providing a structural vision layout for scene und…
From Deterministic to Generative: Multi-Modal Stochastic RNNs for Video Captioning
Jingkuan Song, Yuyu Guo, Lianli Gao +3
Video captioning in essential is a complex natural process, which is affected by various uncertainties stemming from video content, subjective judgment, etc. In this paper we build…