A Simple Yet Effective Network Based on Vision Transformer for Camouflaged Object and Salient Object Detection

Camouflaged object detection (COD) and salient object detection (SOD) are two distinct yet closely-related computer vision tasks widely studied during the past decades. Though sharing the same purpose of segmenting an image into binary foreground and background regions, their distinction lies in the fact that COD focuses on concealed objects hidden in the image, while SOD concentrates on the most prominent objects in the image. Building universal segmentation models is currently a hot topic in the community. Previous works achieved good performance on certain task by stacking various hand-designed modules and multi-scale features. However, these careful task-specific designs also make them lose their potential…

• NR
  National Research Foundation

  Award: 2023A1515140037
• NN
  National Natural Science Foundation of China

  Awards: 62171309, 62231018, 62306061, 62472308