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

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 paper, we aim to predict human eye fixation with view-free scenes based on an end-to-
end deep learning architecture. Although convolutional neural networks (CNNs) have made …

This paper proposes a deep learning model to efficiently detect salient regions in videos. It
addresses two important issues: 1) deep video saliency model training with the absence of …

This paper proposes a fast video salient object detection model, based on a novel recurrent
network architecture, named Pyramid Dilated Bidirectional ConvLSTM (PDB-ConvLSTM). A …

This paper addresses the problem of video object segmentation, where the initial object
mask is given in the first frame of an input video. We propose a novel spatio-temporal …

Most state-of-the-art semi-supervised video object segmentation methods rely on a pixel-
accurate mask of a target object provided for the first frame of a video. However, obtaining a …

The objective of this paper is self-supervised learning of video object segmentation. We
develop a unified framework which simultaneously models cross-frame dense …

Identity switches caused by inter-object interactions remain a critical problem for multi-player
tracking in real-world sports video analysis. Existing approaches utilizing the appearance …