CVPR 2023 - Sketch2Saliency: Learning to Detect Salient Objects from Human Drawings

In this episode we discuss Sketch2Saliency: Learning to Detect Salient Objects from Human Drawings by Authors: - Ayan Kumar Bhunia - Subhadeep Koley - Amandeep Kumar - Aneeshan Sain - Pinaki Nath Chowdhury - Tao Xiang - Yi-Zhe Song Affiliations: - SketchX, CVSSP, University of Surrey, United Kingdom - iFlyTek-Surrey Joint Research Centre on Artificial Intelligence. The paper discusses the saliency of human sketches and proposes a method for using sketches as weak labels to detect salient objects in images. The method uses a photo-to-sketch generation model with a 2D attention mechanism to generate sequential sketch coordinates corresponding to a given visual photo. Attention maps accumulated across the time steps give rise to salient regions, and experiments show that the sketch-based saliency detection model performs competitively compared to the state-of-the-art.