328 citations
- Zhejiang UniversityCN3 papers
- Johns Hopkins UniversityUS2 papers
- Shanghai Jiao Tong UniversityCN2 papers
- Shanghai UniversityCN2 papers
- Xi'an Jiaotong UniversityCN2 papers
- Beijing Institute of TechnologyCN1 paper
- Fudan UniversityCN1 paper
- InferVision (China)CN1 paper
- Nanyang Technological UniversitySG1 paper
- Rutgers, The State University of New JerseyUS1 paper
- University of California, Los AngelesUS1 paper
- University of California, MercedUS1 paper
13 papers
Counterfactual Samples Synthesizing for Robust Visual Question Answering
Long Chen, Xin Yan, Jun Xiao +3
Despite Visual Question Answering (VQA) has realized impressive progress over the last few years, today's VQA models tend to capture superficial linguistic correlations in the trai…
DIDFuse: Deep Image Decomposition for Infrared and Visible Image Fusion
Zixiang Zhao, Shuang Xu, Chunxia Zhang +3
Infrared and visible image fusion, a hot topic in the field of image processing, aims at obtaining fused images keeping the advantages of source images. This paper proposes a novel…
Adversarial Seeded Sequence Growing for Weakly-Supervised Temporal Action Localization
Chengwei Zhang, Yunlu Xu, Zhanzhan Cheng +4
Temporal action localization is an important yet challenging research topic due to its various applications. Since the frame-level or segment-level annotations of untrimmed videos…
REAPS: Towards Better Recognition of Fine-grained Images by Region Attending and Part Sequencing
Peng Zhang, Xinyu Zhu, Zhanzhan Cheng +2
Fine-grained image recognition has been a hot research topic in computer vision due to its various applications. The-state-of-the-art is the part/region-based approaches that first…
Semantic-Guided Multi-Attention Localization for Zero-Shot Learning
Yizhe Zhu, Jianwen Xie, Zhiqiang Tang +2
Zero-shot learning extends the conventional object classification to the unseen class recognition by introducing semantic representations of classes. Existing approaches predominan…
Segregated Temporal Assembly Recurrent Networks for Weakly Supervised Multiple Action Detection
Yunlu Xu, Chengwei Zhang, Zhanzhan Cheng +4
This paper proposes a segregated temporal assembly recurrent (STAR) network for weakly-supervised multiple action detection. The model learns from untrimmed videos with only superv…