Estimating the target extent poses a fundamental challenge in visual object tracking.
Typically, trackers are box-centric and fully rely on a bounding box to define the target in the …

Tracking any given object (s) spatially and temporally is a common purpose in Visual Object
Tracking (VOT) and Video Object Segmentation (VOS). Joint tracking and segmentation …

Abstract The Visual Object Tracking challenge VOT2021 is the ninth annual tracker
benchmarking activity organized by the VOT initiative. Results of 71 trackers are presented; …

In recent years, deep neural networks have demonstrated increasingly strong abilities to
recognize objects and activities in videos. However, as video understanding becomes …

Current state-of-the-art Video Object Segmentation (VOS) methods rely on dense per-object
mask annotations both during training and testing. This requires time-consuming and costly …

Real-time portrait segmentation is an important task for a wide range of human-centered
applications. With the increase of mobile devices, such as mobile phones and personal …

Depth information opens up new opportunities for video object segmentation (VOS) to be
more accurate and robust in complex scenes. However, the RGBD VOS task is largely …

Most of the existing bounding box-based trackers rely on a classification subnetwork and a
regression subnetwork to predict the location and scale of the bounding box. They learn the …

Visual tracking plays a pivotal role in intelligent transportation systems and has a wide range
of practical applications such as autonomous driving and traffic counting. Recently, the …

Current state-of-the-art Video Object Segmentation (VOS) methods rely on dense per-object
mask annotations both during training and testing. This requires time-consuming and costly …