99 citations · 102 across the 3 of their papers we have counts for
5 papers
Learning Domain-invariant Graph for Adaptive Semi-supervised Domain Adaptation with Few Labeled Source Samples
Jinfeng Li, Weifeng Liu, Yicong Zhou +2
Domain adaptation aims to generalize a model from a source domain to tackle tasks in a related but different target domain. Traditional domain adaptation algorithms assume that eno…
Weakly-Supervised Multi-Level Attentional Reconstruction Network for Grounding Textual Queries in Videos
Yijun Song, Jingwen Wang, Lin Ma +2
The task of temporally grounding textual queries in videos is to localize one video segment that semantically corresponds to the given query. Most of the existing approaches rely o…
Multimodal Unified Attention Networks for Vision-and-Language Interactions
Zhou Yu, Yuhao Cui, Jun Yu +2
Learning an effective attention mechanism for multimodal data is important in many vision-and-language tasks that require a synergic understanding of both the visual and textual co…
Deep Modular Co-Attention Networks for Visual Question Answering
Zhou Yu, Jun Yu, Yuhao Cui +2
Visual Question Answering (VQA) requires a fine-grained and simultaneous understanding of both the visual content of images and the textual content of questions. Therefore, designi…
Recovery analysis for weighted mixed minimization with
Zhiyong Zhou, Jun Yu
We study the recovery conditions of weighted mixed minimization for block sparse signal reconstruction from compressed measurements when partial block…