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 …

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 …

Video segmentation aims to segment and track every pixel in diverse scenarios accurately.
In this paper, we present Tube-Link, a versatile framework that addresses multiple core tasks …

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

Video instance segmentation (VIS) is a critical task with diverse applications, including
autonomous driving and video editing. Existing methods often underperform on complex …

Recent attention in instance segmentation has focused on query-based models. Despite
being non-maximum suppression (NMS)-free and end-to-end, the superiority of these …

The handling of long videos with complex and occluded sequences has recently emerged
as a new challenge in the video instance segmentation (VIS) community. However, existing …

The recent advancement in Video Instance Segmentation (VIS) has largely been driven by
the use of deeper and increasingly data-hungry transformer-based models. However, video …

In recent years, significant progress has been made in video instance segmentation (VIS),
with many offline and online methods achieving state-of-the-art performance. While offline …