Abstract Referring Expression Segmentation (RES) aims to generate a segmentation mask
for the object described by a given language expression. Existing classic RES datasets and …

Training data for video segmentation are expensive to annotate. This impedes extensions of
end-to-end algorithms to new video segmentation tasks, especially in large-vocabulary …

Video object segmentation (VOS) aims at segmenting a particular object throughout the
entire video clip sequence. The state-of-the-art VOS methods have achieved excellent …

This paper strives for motion expressions guided video segmentation, which focuses on
segmenting objects in video content based on a sentence describing the motion of the …

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 …

Parameter efficient tuning (PET) has received considerable attention owing to its
applicability to reduce the number of parameters that need to be updated while maintaining …

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 …

In the field of visual scene understanding, deep neural networks have made impressive
advancements in various core tasks like segmentation, tracking, and detection. However …

Open-vocabulary image segmentation aims to partition an image into semantic regions
according to arbitrary text descriptions. However, complex visual scenes can be naturally …

Current referring video object segmentation (R-VOS) techniques extract conditional kernels
from encoded (low-resolution) vision-language features to segment the decoded high …