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 …

Abstract The Visual Object Tracking challenge VOT2019 is the seventh annual tracker
benchmarking activity organized by the VOT initiative. Results of 81 trackers are presented; …

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 …

Short-term tracking is an open and challenging problem for which discriminative correlation
filters (DCF) have shown excellent performance. We introduce the channel and spatial …

Abstract The Visual Object Tracking challenge 2015, VOT2015, aims at comparing short-
term single-object visual trackers that do not apply pre-learned models of object …

Convolutional networks reach top quality in pixel-level video object segmentation but
require a large amount of training data (1k–100k) to deliver such results. We propose a new …

Deep learning requires large amounts of annotated data. Manual annotation of objects in
video is, regardless of annotation type, a tedious and time-consuming process. In particular …

Convolutional networks reach top quality in pixellevel object tracking but require a large
amount of training data (1k∼ 10k) to deliver such results. We propose a new training …

This paper tackles the task of online video object segmentation with weak supervision, ie,
labeling the target object and background with pixel-level accuracy in unconstrained videos …

The accuracy of object detectors and trackers is most commonly evaluated by the
Intersection over Union (IoU) criterion. To date, most approaches are restricted to axis …