no code implementations • 1 May 2024 • Weijian Sun, Yanbo Jia, Qi Zeng, Zihao Liu, Jiang Liao, Yue Li, Xianfeng Li
Deep-learning-based techniques have been widely adopted for autonomous driving software stacks for mass production in recent years, focusing primarily on perception modules, with some work extending this method to prediction modules.
1 code implementation • 9 Oct 2022 • Rang Meng, Xianfeng Li, WeiJie Chen, Shicai Yang, Jie Song, Xinchao Wang, Lei Zhang, Mingli Song, Di Xie, ShiLiang Pu
Under this guidance, a novel Attention Diversification framework is proposed, in which Intra-Model and Inter-Model Attention Diversification Regularization are collaborated to reassign appropriate attention to diverse task-related features.
no code implementations • 10 Dec 2020 • Xianfeng Li, WeiJie Chen, Di Xie, Shicai Yang, Peng Yuan, ShiLiang Pu, Yueting Zhuang
However, it is difficult to evaluate the quality of pseudo labels since no labels are available in target domain.