Salient object detection with image-level binary supervision

•We propose a learning framework for salient object detection, which is trained only on image-level binary labels but yields comparable performance to state-of-the-art weakly-supervised methods.•We propose a target label hallucination method, which can synthesize quality pseudo ground truth saliency maps from just binary labels.•We have conducted extensive experimental evaluation to demonstrate the effectiveness of the proposed weakly-supervised method.