UCNet
UCNet
**UCNet** is a probabilistic framework for RGB-D Saliency Detection that employs uncertainty by learning from the data labelling process. It utilizes conditional variational autoencoders to model human annotation uncertainty and generate multiple saliency maps for each input image by sampling in the latent space.
UC-Net: Uncertainty Inspired RGB-D Saliency Detection via Conditional Variational Autoencoders
https://paperswithcode.com/paper/uc-net-uncertainty-inspired-rgb-d-saliency
UC-Net: Uncertainty Inspired RGB-D Saliency Detection via Conditional Variational Autoencoders