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 …

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 …

We present a unified method, termed Unicorn, that can simultaneously solve four tracking
problems (SOT, MOT, VOS, MOTS) with a single network using the same model parameters …

Video instance segmentation (VIS) is the task that requires simultaneously classifying,
segmenting and tracking object instances of interest in video. Recent methods typically …

We present QueryInst, a new perspective for instance segmentation. QueryInst is a multi-
stage end-to-end system that treats instances of interest as learnable queries, enabling …

Panoptic segmentation assigns semantic and instance ID labels to every pixel of an image.
As permutations of instance IDs are also valid solutions, the task requires learning of high …

In recent years, video instance segmentation (VIS) has been largely advanced by offline
models, while online models gradually attracted less attention possibly due to their inferior …

We introduce a novel method using a new generative model that automatically learns
effective representations of the target and background appearance to detect, segment and …

Referring video object segmentation (R-VOS) is an emerging cross-modal task that aims to
segment the target object referred by a language expression in all video frames. In this work …

Video instance segmentation (VIS) is a new and critical task in computer vision. To date, top-
performing VIS methods extend the two-stage Mask R-CNN by adding a tracking branch …