Publications [#358817] of Sina Farsiu

Papers Published

1. Yang, Z; Soltanian-Zadeh, S; Farsiu, S, BiconNet: An Edge-preserved Connectivity-based Approach for Salient Object Detection., Pattern recognition, vol. 121 (January, 2022), pp. 108231 [doi]
   (last updated on 2024/12/31)

   Abstract:
   Salient object detection (SOD) is viewed as a pixel-wise saliency modeling task by traditional deep learning-based methods. A limitation of current SOD models is insufficient utilization of inter-pixel information, which usually results in imperfect segmentation near edge regions and low spatial coherence. As we demonstrate, using a saliency mask as the only label is suboptimal. To address this limitation, we propose a connectivity-based approach called bilateral connectivity network (BiconNet), which uses connectivity masks together with saliency masks as labels for effective modeling of inter-pixel relationships and object saliency. Moreover, we propose a bilateral voting module to enhance the output connectivity map, and a novel edge feature enhancement method that efficiently utilizes edge-specific features. Through comprehensive experiments on five benchmark datasets, we demonstrate that our proposed method can be plugged into any existing state-of-the-art saliency-based SOD framework to improve its performance with negligible parameter increase.