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 …

We propose a novel solution for semi-supervised video object segmentation. By the nature
of the problem, available cues (eg video frame (s) with object masks) become richer with the …

In this paper we illustrate how to perform both visual object tracking and semi-supervised
video object segmentation, in real-time, with a single simple approach. Our method, dubbed …

Meta-learning has been proposed as a framework to address the challenging few-shot
learning setting. The key idea is to leverage a large number of similar few-shot tasks in order …

We introduce a novel network, called as CO-attention Siamese Network (COSNet), to
address the unsupervised video object segmentation task from a holistic view. We …

Many of the recent successful methods for video object segmentation (VOS) are overly
complicated, heavily rely on fine-tuning on the first frame, and/or are slow, and are hence of …

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

In this article, we introduce SiamMask, a framework to perform both visual object tracking
and video object segmentation, in real-time, with the same simple method. We improve the …

We present the 2017 DAVIS Challenge on Video Object Segmentation, a public dataset,
benchmark, and competition specifically designed for the task of video object segmentation …

We present an efficient method for the semi-supervised video object segmentation. Our
method achieves accuracy competitive with state-of-the-art methods while running in a …