PANORAMA: The Rise of Omnidirectional Vision in the Embodied AI Era
Authors: name: Xu Zheng, name: Chenfei Liao, name: Ziqiao Weng, name: Kaiyu Lei, name: Zihao Dongfang, name: Haocong He, name: Yuanhuiyi Lyu, name: Lutao Jiang, name: Lu Qi, name: Li Chen, name: Danda Pani Paudel, name: Kailun Yang, name: Linfeng Zhang, name: Luc Van Gool, name: Xuming Hu

Omnidirectional vision, using 360-degree vision to understand the
environment, has become increasingly critical across domains like robotics,
industrial inspection, and environmental monitoring. Compared to traditional
pinhole vision, omnidirectional vision provides holistic environmental
awareness, significantly enhancing the completeness of scene perception and the
reliability of decision-making. However, foundational research in this area has
historically lagged behind traditional pinhole vision. This talk presents an
emerging trend in the embodied AI era: the rapid development of omnidirectional
vision, driven by growing industrial demand and academic interest. We highlight
recent breakthroughs in omnidirectional generation, omnidirectional perception,
omnidirectional understanding, and related datasets. Drawing on insights from
both academia and industry, we propose an ideal panoramic system architecture
in the embodied AI era, PANORAMA, which consists of four key subsystems.
Moreover, we offer in-depth opinions related to emerging trends and
cross-community impacts at the intersection of panoramic vision and embodied
AI, along with the future roadmap and open challenges. This overview
synthesizes state-of-the-art advancements and outlines challenges and
opportunities for future research in building robust, general-purpose
omnidirectional AI systems in the embodied AI era.