Since the popularisation of the Internet in the 1990s, the cyberspace has kept evolving. We
have created various computer-mediated virtual environments, including social networks …

The goal of semantic segmentation is to segment the input image according to semantic
information and predict the semantic category of each pixel from a given label set. With the …

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 …

Abstract The recent Segment Anything Model (SAM) represents a big leap in scaling up
segmentation models, allowing for powerful zero-shot capabilities and flexible prompting …

We present SegNeXt, a simple convolutional network architecture for semantic
segmentation. Recent transformer-based models have dominated the field of se-mantic …

Two-branch network architecture has shown its efficiency and effectiveness in real-time
semantic segmentation tasks. However, direct fusion of high-resolution details and low …

Visual segmentation seeks to partition images, video frames, or point clouds into multiple
segments or groups. This technique has numerous real-world applications, such as …

Using light-weight architectures or reasoning on low-resolution images, recent methods
realize very fast scene parsing, even running at more than 100 FPS on a single GPU …

Although vision transformers (ViTs) have achieved great success in computer vision, the
heavy computational cost hampers their applications to dense prediction tasks such as …

Recent studies show that Vision Transformers (ViTs) exhibit strong robustness against
various corruptions. Although this property is partly attributed to the self-attention …