UCP-Net: Unstructured Contour Points for Instance Segmentation

• URL: http://arxiv.org/abs/2109.07592v1
• Date: Wed, 15 Sep 2021 22:03:37 GMT
• Title: UCP-Net: Unstructured Contour Points for Instance Segmentation
• Authors: Camille Dupont, Yanis Ouakrim and Quoc Cuong Pham
• Abstract summary: We propose a novel approach to interactive segmentation based on unconstrained contour clicks for initial segmentation and segmentation refinement. Our method is class-agnostic and produces accurate segmentation masks (IoU > 85%) for a lower number of user interactions than state-of-the-art methods on popular segmentation datasets.
• Score: 2.105564340986074
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The goal of interactive segmentation is to assist users in producing segmentation masks as fast and as accurately as possible. Interactions have to be simple and intuitive and the number of interactions required to produce a satisfactory segmentation mask should be as low as possible. In this paper, we propose a novel approach to interactive segmentation based on unconstrained contour clicks for initial segmentation and segmentation refinement. Our method is class-agnostic and produces accurate segmentation masks (IoU > 85%) for a lower number of user interactions than state-of-the-art methods on popular segmentation datasets (COCO MVal, SBD and Berkeley).

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