Vision systems that see and reason about the compositional nature of visual scenes are
fundamental to understanding our world. The complex relations between objects and their …

Object segmentation and object tracking are fundamental research areas in the computer
vision community. These two topics are difficult to handle some common challenges, such …

All instance perception tasks aim at finding certain objects specified by some queries such
as category names, language expressions, and target annotations, but this complete field …

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 restoration aims to restore high-quality frames from low-quality frames. Different from
single image restoration, video restoration generally requires to utilize temporal information …

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 …

Current universal segmentation methods demonstrate strong capabilities in pixel-level
image and video understanding. However, they lack reasoning abilities and cannot be …

Video restoration aims at restoring multiple high-quality frames from multiple low-quality
frames. Existing video restoration methods generally fall into two extreme cases, ie, they …

Existing referring understanding tasks tend to involve the detection of a single text-referred
object. In this paper, we propose a new and general referring understanding task, termed …

In this paper we propose the Matting Anything Model (MAM) an efficient and versatile
framework for estimating the alpha matte of any instance in an image with flexible and …