CVPR 2023 - Discriminative Co-Saliency and Background Mining Transformer for Co-Salient Object Detection

In this episode we discuss Discriminative Co-Saliency and Background Mining Transformer for Co-Salient Object Detection by Long Li, Junwei Han, Ni Zhang, Nian Liu, Salman Khan, Hisham Cholakkal, Rao Muhammad Anwer, Fahad Shahbaz Khan. The paper proposes a Discriminative co-saliency and background Mining Transformer (DMT) framework for co-salient object detection. The framework includes several economical multi-grained correlation modules that explicitly mine both co-saliency and background information to effectively model their discrimination. These modules include a region-to-region correlation module, contrast-induced pixel-to-token correlation, and co-saliency token-to-token correlation modules. The proposed framework is experimentally validated on three benchmark datasets and the source code is available on GitHub.