1 code implementation • 29 Feb 2024 • Hongxin Li, Zeyu Wang, Xu Yang, Yuran Yang, Shuqi Mei, Zhaoxiang Zhang
Subsequently, a graph attention module encodes the retained STM and the LTM to generate working memory (WM) which contains the scene features essential for efficient navigation.
no code implementations • ICCV 2023 • Yuxi Wang, Jian Liang, Jun Xiao, Shuqi Mei, Yuran Yang, Zhaoxiang Zhang
One-shot domain adaptation methods attempt to overcome these challenges by transferring the pre-trained source model to the target domain using only one target data.
no code implementations • ICCV 2023 • Jingtao Wang, Zengjie Song, Yuxi Wang, Jun Xiao, Yuran Yang, Shuqi Mei, Zhaoxiang Zhang
Surrogate gradient (SG) is one of the most effective approaches for training spiking neural networks (SNNs).
no code implementations • 20 Aug 2022 • Hongxin Li, Xu Yang, Yuran Yang, Shuqi Mei, Zhaoxiang Zhang
To address this limitation, we present the MemoNav, a novel memory mechanism for image-goal navigation, which retains the agent's informative short-term memory and long-term memory to improve the navigation performance on a multi-goal task.