In this work we address various segmentation tasks each traditionally tackled by distinct or
partially unified models. We propose OMG-Seg One Model that is Good enough to efficiently …

Masked Autoencoders (MAE) have been popular paradigms for large-scale vision
representation pre-training. However, MAE solely reconstructs the low-level RGB signals …

Masked Image Modeling (MIM) is a powerful self-supervised strategy for visual pre-training
without the use of labels. MIM applies random crops to input images, processes them with …

Self-supervised landmark estimation is a challenging task that demands the formation of
locally distinct feature representations to identify sparse facial landmarks in the absence of …

Inspired by the fact that human brains can emphasize discriminative parts of the input and
suppress irrelevant ones, substantial local mechanisms have been designed to boost the …

Sound Event Detection and Localization (SELD) constitutes a complex task that depends on
extensive multichannel audio recordings with annotated sound events and their respective …