Frequency-Enhanced Data Augmentation for Vision-and-Language Navigation | |
Keji He1,2,3![]() ![]() ![]() ![]() | |
2023-12 | |
会议名称 | Neural Information Processing Systems |
会议日期 | 2023-12-9 至 2023-12-15 |
会议地点 | 新奥尔良 |
摘要 | Vision-and-Language Navigation (VLN) is a challenging task that requires an agent to navigate through complex environments based on natural language instructions. In contrast to conventional approaches, which primarily focus on the spatial domain exploration, we propose a paradigm shift toward the Fourier domain. This alternative perspective aims to enhance visual-textual matching, ultimately improving the agent’s ability to understand and execute navigation tasks based on the given instructions. In this study, we first explore the significance of high-frequency information in VLN and provide evidence that it is instrumental in bolstering visual-textual matching processes. Building upon this insight, we further propose a sophisticated and versatile Frequency-enhanced Data Augmentation (FDA) technique to improve the VLN model’s capability of capturing critical high-frequency information. Specifically, this approach requires the agent to navigate in environments where only a subset of high-frequency visual information corresponds with the provided textual instructions, ultimately fostering the agent’s ability to selectively discern and capture pertinent high-frequency features according to the given instructions. Promising results on R2R, RxR, CVDN and REVERIE demonstrate that our FDA can be readily integrated with existing VLN approaches, improving performance without adding extra parameters, and keeping models simple and efficient. The code is available at https://github.com/hekj/FDA. |
收录类别 | EI |
七大方向——子方向分类 | 机器人感知与决策 |
国重实验室规划方向分类 | 多模态协同认知 |
是否有论文关联数据集需要存交 | 否 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/57627 |
专题 | 模式识别实验室 |
通讯作者 | Chenyang Si; Liang Wang; Xinchao Wang |
作者单位 | 1.Center for Research on Intelligent Perception and Computing, National Key Laboratory for Multi-modal Artificial Intelligence Systems Institute of Automation, Chinese Academy of Sciences 2.School of Artificial Intelligence, University of Chinese Academy of Sciences 3.National University of Singapore 4.Nanyang Technological University |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Keji He,Chenyang Si,Zhihe Lu,et al. Frequency-Enhanced Data Augmentation for Vision-and-Language Navigation[C],2023. |
条目包含的文件 | 下载所有文件 | |||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
NeurIPS-2023-frequen(2505KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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