详细信息
- 来源站点
- ArXiv CS.CV
- 作者
- Feng Qiao, Zhexiao Xiong, Xinge Zhu, Yuexin Ma, Qiumeng He, Nathan Jacobs
- 文章类型
- NEWS
- 语言
- en
- 发布日期
- 2026-06-02
摘要
arXiv:2408.01653v4 Announce Type: replace Abstract: Omnidirectional depth estimation presents a significant challenge due to the inherent distortions in panoramic images. Despite notable advancements, the impact of projection methods remains underexplored. We introduce Multi-Cylindrical Panoramic Depth Estimation (MCPDepth), a novel two-stage framework designed to enhance omnidirectional depth estimation through stereo matching across multiple cylindrical panoramas. MCPDepth initially performs stereo matching using cylindrical panoramas, followed by a robust fusion of the resulting depth maps from different views. Unlike existing methods that rely on customized kernels to address distortions, MCPDepth utilizes standard network components, facilitating seamless deployment on embedded devices while delivering exceptional performance.