Semantic Segmentation

We propose a self-supervised learning approach where the system learns transformations independently by reconstructing images that have undergone previously unseen transformations.

We propose to improve MDE while using auxiliary datasets from related vision tasks with an alternating training scheme with a shared decoder built on top of a pre-trained vision foundation model.