no code implementations • 11 Mar 2024 • Sikai Bai, Jie Zhang, Shuaicheng Li, Song Guo, Jingcai Guo, Jun Hou, Tao Han, Xiaocheng Lu
Federated learning (FL) has emerged as a powerful paradigm for learning from decentralized data, and federated domain generalization further considers the test dataset (target domain) is absent from the decentralized training data (source domains).
no code implementations • 11 Jul 2023 • Sikai Bai, Shuaicheng Li, Weiming Zhuang, Jie Zhang, Song Guo, Kunlin Yang, Jun Hou, Shuai Zhang, Junyu Gao, Shuai Yi
Theoretically, we show the convergence guarantee of the dual regulators.
no code implementations • 21 Jun 2022 • Shuaicheng Li, Feng Zhang, Kunlin Yang, Lingbo Liu, Shinan Liu, Jun Hou, Shuai Yi
Our proposed method mainly leverages the intra-modality encoding and cross-modality co-occurrence encoding for fully representation modeling.
1 code implementation • 21 Jun 2022 • Shuaicheng Li, Feng Zhang, Rui-Wei Zhao, Rui Feng, Kunlin Yang, Lingbo Liu, Jun Hou
Based on PRSlot modules, we present a novel Pyramid Region-based Slot Attention Network termed PRSA-Net to learn a unified visual representation with rich temporal and semantic context for better proposal generation.
1 code implementation • ICCV 2021 • Shuaicheng Li, Qianggang Cao, Lingbo Liu, Kunlin Yang, Shinan Liu, Jun Hou, Shuai Yi
It captures spatial-temporal contextual information jointly to augment the individual and group representations effectively with a clustered spatial-temporal transformer.