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 …

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 …

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 …

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 paradigm for offline Video Instance Segmentation (VIS), based on the
hypothesis that explicit object-oriented information can be a strong clue for understanding …

This paper presents Video K-Net, a simple, strong, and unified framework for fully end-to-
end video panoptic segmentation. The method is built upon K-Net, a method that unifies …

Video segmentation—partitioning video frames into multiple segments or objects—plays a
critical role in a broad range of practical applications, from enhancing visual effects in movie …

In this work, we present SeqFormer for video instance segmentation. SeqFormer follows the
principle of vision transformer that models instance relationships among video frames …

We propose a novel end-to-end solution for video instance segmentation (VIS) based on
transformers. Recently, the per-clip pipeline shows superior performance over per-frame …

Recently vision transformer has achieved tremendous success on image-level visual
recognition tasks. To effectively and efficiently model the crucial temporal information within …