PriOr-Flow: Enhancing Primitive Panoramic Optical Flow with Orthogonal View

• URL: http://arxiv.org/abs/2506.23897v3
• Date: Thu, 03 Jul 2025 12:44:27 GMT
• Title: PriOr-Flow: Enhancing Primitive Panoramic Optical Flow with Orthogonal View
• Authors: Longliang Liu, Miaojie Feng, Junda Cheng, Jijun Xiang, Xuan Zhu, Xin Yang,
• Abstract summary: PriOr-Flow is a novel dual-branch framework for optical flow estimation.<n>It mitigates distortion noise during cost volume construction.<n>It consistently achieves state-of-the-art performance on publicly available panoramic optical flow datasets.
• Score: 4.861898720749389
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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 from both branches, 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. The code is publicly available at: https://github.com/longliangLiu/PriOr-Flow.

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