Pixel-Pair Occlusion Relationship Map(P2ORM): Formulation, Inference & Application

• URL: http://arxiv.org/abs/2007.12088v1
• Date: Thu, 23 Jul 2020 15:52:09 GMT
• Title: Pixel-Pair Occlusion Relationship Map(P2ORM): Formulation, Inference & Application
• Authors: Xuchong Qiu and Yang Xiao and Chaohui Wang and Renaud Marlet
• Abstract summary: We formalize concepts around geometric occlusion in 2D images (i.e., ignoring semantics) We propose a novel unified formulation of both occlusion boundaries and occlusion orientations via a pixel-pair occlusion relation. Experiments on a variety of datasets demonstrate that our method outperforms existing ones on this task. We also propose a new depth map refinement method that consistently improve the performance of state-of-the-art monocular depth estimation methods.
• Score: 20.63938300312815
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We formalize concepts around geometric occlusion in 2D images (i.e., ignoring semantics), and propose a novel unified formulation of both occlusion boundaries and occlusion orientations via a pixel-pair occlusion relation. The former provides a way to generate large-scale accurate occlusion datasets while, based on the latter, we propose a novel method for task-independent pixel-level occlusion relationship estimation from single images. Experiments on a variety of datasets demonstrate that our method outperforms existing ones on this task. To further illustrate the value of our formulation, we also propose a new depth map refinement method that consistently improve the performance of state-of-the-art monocular depth estimation methods. Our code and data are available at http://imagine.enpc.fr/~qiux/P2ORM/.

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