Humans can naturally and effectively find salient regions in complex scenes. Motivated by
this observation, attention mechanisms were introduced into computer vision with the aim of …

Building extraction from remote sensing (RS) images is a fundamental task for geospatial
applications, aiming to obtain morphology, location, and other information about buildings …

Although perception systems have made remarkable advancements in recent years they still
rely on explicit human instruction or pre-defined categories to identify the target objects …

Semantic segmentation of remotely sensed urban scene images is required in a wide range
of practical applications, such as land cover mapping, urban change detection …

Recently, segmentation-based scene text detection methods have drawn extensive attention
in the scene text detection field, because of their superiority in detecting the text instances of …

Image segmentation is often ambiguous at the level of individual image patches and
requires contextual information to reach label consensus. In this paper we introduce …

Transformer architecture has emerged to be successful in a number of natural language
processing tasks. However, its applications to medical vision remain largely unexplored. In …

The emergence of large models, also known as foundation models, has brought significant
advancements to AI research. One such model is Segment Anything (SAM), which is …

Humans are able to recognize structured relations in observation, allowing us to decompose
complex scenes into simpler parts and abstract the visual world in multiple levels. However …

Attention mechanisms, which enable a neural network to accurately focus on all the relevant
elements of the input, have become an essential component to improve the performance of …