8 citations · 18 across the 6 of their papers we have counts for
6 papers
HERO: HiErarchical spatio-tempoRal reasOning with Contrastive Action Correspondence for End-to-End Video Object Grounding
Mengze Li, Tianbao Wang, Haoyu Zhang +6
Video Object Grounding (VOG) is the problem of associating spatial object regions in the video to a descriptive natural language query. This is a challenging vision-language task t…
Unimodal-Concentrated Loss: Fully Adaptive Label Distribution Learning for Ordinal Regression
Qiang Li, Jingjing Wang, Zhaoliang Yao +5
Learning from a label distribution has achieved promising results on ordinal regression tasks such as facial age and head pose estimation wherein, the concept of adaptive label dis…
Alignment-Uniformity aware Representation Learning for Zero-shot Video Classification
Shi Pu, Kaili Zhao, Mao Zheng
Most methods tackle zero-shot video classification by aligning visual-semantic representations within seen classes, which limits generalization to unseen classes. To enhance model…
End-to-End Modeling via Information Tree for One-Shot Natural Language Spatial Video Grounding
Mengze Li, Tianbao Wang, Haoyu Zhang +9
Natural language spatial video grounding aims to detect the relevant objects in video frames with descriptive sentences as the query. In spite of the great advances, most existing…
Multimodal Topic Learning for Video Recommendation
Shi Pu, Yijiang He, Zheng Li +1
Facilitated by deep neural networks, video recommendation systems have made significant advances. Existing video recommendation systems directly exploit features from different mod…
Deep Attentive Tracking via Reciprocative Learning
Shi Pu, Yibing Song, Chao Ma +2
Visual attention, derived from cognitive neuroscience, facilitates human perception on the most pertinent subset of the sensory data. Recently, significant efforts have been made t…