Abstract: The existing deep learning based reversible data hiding (RDH) predictors typically adopt standard convolutions for extracting features, which inherently fails to capture contextual ...

Abstract: Open-vocabulary semantic segmentation aims to partition an image into distinct semantic regions based on an open set of categories. Existing approaches primarily rely on image-level ...

In this post, we share the motivations, design choices, experiments, and learnings that informed its development, as well as an evaluation of the model’s performance and guidance on how to use it. Our ...

Abstract. An old-school recipe for training a classifier is to (i) learn a good feature extractor and (ii) optimize a linear layer atop. When only a handful of samples are available per category, as ...