activity
20182022
most citedAlignment-Uniformity aware Representation Learning for Zero-shot Video Classification

2 citations · 6 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV20221 cited

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…

cs.CV20222 cited

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…

cs.CV20222 cited

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…

cs.IR20201 cited

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…

cs.CV2018

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…