234 citations · 456 across the 13 of their papers we have counts for
5 papers · 1 filter
AdapNet: Adaptability Decomposing Encoder-Decoder Network for Weakly Supervised Action Recognition and Localization
Xiao-Yu Zhang, Changsheng Li, Haichao Shi +3
The point process is a solid framework to model sequential data, such as videos, by exploring the underlying relevance. As a challenging problem for high-level video understanding,…
Fi-GNN: Modeling Feature Interactions via Graph Neural Networks for CTR Prediction
Zekun Li, Zeyu Cui, Shu Wu +2
Click-through rate (CTR) prediction is an essential task in web applications such as online advertising and recommender systems, whose features are usually in multi-field form. The…
Semi-supervised Compatibility Learning Across Categories for Clothing Matching
Zekun Li, Zeyu Cui, Shu Wu +2
Learning the compatibility between fashion items across categories is a key task in fashion analysis, which can decode the secret of clothing matching. The main idea of this task i…
Dressing as a Whole: Outfit Compatibility Learning Based on Node-wise Graph Neural Networks
Zeyu Cui, Zekun Li, Shu Wu +2
With the rapid development of fashion market, the customers' demands of customers for fashion recommendation are rising. In this paper, we aim to investigate a practical problem of…
Learning Transferable Self-attentive Representations for Action Recognition in Untrimmed Videos with Weak Supervision
Xiao-Yu Zhang, Haichao Shi, Changsheng Li +3
Action recognition in videos has attracted a lot of attention in the past decade. In order to learn robust models, previous methods usually assume videos are trimmed as short seque…