The research advances concerning the typical architectures of convolutional neural
networks (CNNs) as well as their optimizations are analyzed and elaborated in detail in this …

As one of the fundamental problems in the field of video understanding, video object
segmentation aims at segmenting objects of interest throughout the given video sequence …

Recently integrating video foundation models and large language models to build a video
understanding system can overcome the limitations of specific pre-defined vision tasks. Yet …

We present XMem, a video object segmentation architecture for long videos with unified
feature memory stores inspired by the Atkinson-Shiffrin memory model. Prior work on video …

This paper investigates how to realize better and more efficient embedding learning to tackle
the semi-supervised video object segmentation under challenging multi-object scenarios …

We present Cutie a video object segmentation (VOS) network with object-level memory
reading which puts the object representation from memory back into the video object …

This paper presents a simple yet effective approach to modeling space-time
correspondences in the context of video object segmentation. Unlike most existing …

This paper focuses on developing a more effective method of hierarchical propagation for
semi-supervised Video Object Segmentation (VOS). Based on vision transformers, the …

Appearance and motion are two important sources of information in video object
segmentation (VOS). Previous methods mainly focus on using simplex solutions, lowering …

We present Modular interactive VOS (MiVOS) framework which decouples interaction-to-
mask and mask propagation, allowing for higher generalizability and better performance …