Liu_PriOr-Flow_Enhancing_Primitive_Panoramic_Optical_Flow_with_Orthogonal_View@ICCV2025@CVF

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#1 PriOr-Flow: Enhancing Primitive Panoramic Optical Flow with Orthogonal View [PDF] [Copy] [Kimi1] [REL]

Authors: Longliang Liu, Miaojie Feng, Junda Cheng, Jijun Xiang, Xuan Zhu, Xin Yang

Panoramic optical flow enables a comprehensive understanding of temporal dynamics across wide fields of view. However, severe distortions caused by sphere-to-plane projections, such as the equirectangular projection (ERP), significantly degrade the performance of conventional perspective-based optical flow methods, especially in polar regions. To address this challenge, we propose PriOr-Flow, a novel dual-branch framework that leverages the low-distortion nature of the orthogonal view to enhance optical flow estimation in these regions. Specifically, we introduce the Dual-Cost Collaborative Lookup (DCCL) operator, which jointly retrieves correlation information from both the primitive and orthogonal cost volumes, effectively mitigating distortion noise during cost volume construction. Furthermore, our Ortho-Driven Distortion Compensation (ODDC) module iteratively refines motion features of the primitive branch, further suppressing polar distortions. Extensive experiments demonstrate that PriOr-Flow is compatible with various perspective-based iterative optical flow methods and consistently achieves state-of-the-art performance on publicly available panoramic optical flow datasets, setting a new benchmark for wide-field motion estimation.

Subject: ICCV.2025 - Highlight