Thermal infrared (TIR) target tracking task is not affected by illumination changes and can be
tracked at night, on rainy days, foggy days, and other extreme weather; so it is widely used in …

Visual object tracking has been drawing increasing attention in recent years, as a
fundamental task in computer vision. To extend the range of tracking applications …

RGB-D object tracking has attracted considerable attention recently, achieving promising
performance thanks to the symbiosis between visual and depth channels. However, given a …

Depth cameras have recently become popular and many vision problems can be better
solved with depth information. But, how to integrate depth information into a visual tracker to …

Standard RGB-D trackers treat the target as a 2D structure, which makes modelling
appearance changes related even to out-of-plane rotation challenging. This limitation is …

The emergence of large-scale high-quality datasets has stimulated the rapid development of
deep learning in recent years. However, most computer vision tasks focus on the visual …

We propose a new color-and-depth general visual object tracking benchmark (CDTB).
CDTB is recorded by several passive and active RGB-D setups and contains indoor as well …

We present a real-time RGB-D object tracker which manages occlusions and scale changes
in a wide variety of scenarios. Its accuracy matches, and in many cases outperforms, state-of …

We propose a generic framework for converting an arbitrary short-term RGB tracker into an
RGBD tracker. The proposed framework has two mild requirements–the short-term tracker …

We propose an RGB-D single-object tracker, built upon the extremely fast RGB-only KCF
tracker that is able to exploit depth information to handle scale changes, occlusions, and …