Visual target tracking is one of the most sought-after yet challenging research topics in
computer vision. Given the ill-posed nature of the problem and its popularity in a broad …

Recently, deep learning has achieved great success in visual tracking. The goal of this
paper is to review the state-of-the-art tracking methods based on deep learning. First, we …

Neural compression is the application of neural networks and other machine learning
methods to data compression. Recent advances in statistical machine learning have opened …

摘要随着摄像头安装数量的日益增多, 以及智慧城市和公共安全需求的日益增长,
采用人工的视频监控方式已经远远不能满足需要, 因此智能视频监控技术应运而生并迅速成为 …

A typical pipeline for multi-object tracking (MOT) is to use a detector for object localization,
and following re-identification (re-ID) for object association. This pipeline is partially …

Camouflaged object segmentation (COS) aims to identify objects that are" perfectly"
assimilate into their surroundings, which has a wide range of valuable applications. The key …

Generic motion understanding from video involves not only tracking objects, but also
perceiving how their surfaces deform and move. This information is useful to make …

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 …

In this paper, we present LaSOT, a high-quality benchmark for Large-scale Single Object
Tracking. LaSOT consists of 1,400 sequences with more than 3.5 M frames in total. Each …

Object tracking is still a critical and challenging problem with many applications in computer
vision. For this challenge, more and more researchers pay attention to applying deep …