Object segmentation and object tracking are fundamental research areas in the computer
vision community. These two topics are difficult to handle some common challenges, such …

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 …

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

Most online multi-object trackers perform object detection stand-alone in a neural net without
any input from tracking. In this paper, we present a new online joint detection and tracking …

Convolutional neural networks have made significant progresses in edge detection by
progressively exploring the context and semantic features. However, local details are …

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

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