UCNet

UCNet: Utilizing Uncertainty in RGB-D Saliency Detection UCNet is a powerful framework for RGB-D Saliency Detection that leverages the power of uncertainty in the data labelling process to generate highly accurate saliency maps. Developed using conditional variational autoencoders, UCNet employs an innovative approach to modelling human annotation uncertainty to produce highly detailed and accurate saliency maps for every input image. What is RGB-D Saliency Detection? RGB-D Saliency Detectio