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 …

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 …

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 …

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 …

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

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 …

Abstract We present Hierarchical Memory Matching Network (HMMN) for semi-supervised
video object segmentation. Based on a recent memory-based method [33], we propose two …

Abstract Recently, several Space-Time Memory based networks have shown that the object
cues (eg video frames as well as the segmented object masks) from the past frames are …