no code implementations • 2 Mar 2024 • Luyao Wang, Pengnian Qi, Xigang Bao, Chunlai Zhou, Biao Qin
Unfortunately, prior arts have attempted to improve the interaction and fusion of multi-modal information, which have overlooked the influence of modal-specific noise and the usage of labeled and unlabeled data in semi-supervised settings.
1 code implementation • 1 Nov 2020 • Yujie Lu, Shengyu Zhang, Yingxuan Huang, Luyao Wang, Xinyao Yu, Zhou Zhao, Fei Wu
By diverse trends, supposing the future preferences can be diversified, we propose the diverse trends extractor and the time-aware mechanism to represent the possible trends of preferences for a given user with multiple vectors.
no code implementations • 20 Feb 2018 • Pingping Zhang, Luyao Wang, Dong Wang, Huchuan Lu, Chunhua Shen
This paper proposes an Agile Aggregating Multi-Level feaTure framework (Agile Amulet) for salient object detection.