Deep learning, a branch of machine learning, is a frontier for artificial intelligence, aiming to
be closer to its primary goal—artificial intelligence. This paper mainly adopts the summary …

Conventional neural networks have been demonstrated to be a powerful framework for
background subtraction in video acquired by static cameras. Indeed, the well-known Self …

We present Segment Anything Model 2 (SAM 2), a foundation model towards solving
promptable visual segmentation in images and videos. We build a data engine, which …

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 …

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 …

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 …

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 …

How to make a segmentation model efficiently adapt to a specific video as well as online
target appearance variations is a fundamental issue in the field of video object …

One-shot image semantic segmentation poses a challenging task of recognizing the object
regions from unseen categories with only one annotated example as supervision. In this …

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 …