ObjectRelator: Enabling Cross-View Object Relation Understanding in Ego-Centric and Exo-Centric Videos

• URL: http://arxiv.org/abs/2411.19083v1
• Date: Thu, 28 Nov 2024 12:01:03 GMT
• Title: ObjectRelator: Enabling Cross-View Object Relation Understanding in Ego-Centric and Exo-Centric Videos
• Authors: Yuqian Fu, Runze Wang, Yanwei Fu, Danda Pani Paudel, Xuanjing Huang, Luc Van Gool,
• Abstract summary: Ego-Exo Object Correspondence task aims to map objects across ego-centric and exo-centric views. We introduce ObjectRelator, a novel method designed to tackle this task.
• Score: 105.40690994956667
• License:
• Abstract: In this paper, we focus on the Ego-Exo Object Correspondence task, an emerging challenge in the field of computer vision that aims to map objects across ego-centric and exo-centric views. We introduce ObjectRelator, a novel method designed to tackle this task, featuring two new modules: Multimodal Condition Fusion (MCFuse) and SSL-based Cross-View Object Alignment (XObjAlign). MCFuse effectively fuses language and visual conditions to enhance target object localization, while XObjAlign enforces consistency in object representations across views through a self-supervised alignment strategy. Extensive experiments demonstrate the effectiveness of ObjectRelator, achieving state-of-the-art performance on Ego2Exo and Exo2Ego tasks with minimal additional parameters. This work provides a foundation for future research in comprehensive cross-view object relation understanding highlighting the potential of leveraging multimodal guidance and cross-view alignment. Codes and models will be released to advance further research in this direction.

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