In recent years, the ensembled trackers composed of multi-level features from the pre-
trained Convolutional Neural Network (CNN) have achieved top performance in visual …

Deformable parts models show a great potential in tracking by principally addressing
nonrigid object deformations and self occlusions, but according to recent benchmarks, they …

Sparse representations have been applied to visual tracking by finding the best candidate
region with minimal reconstruction error based on a set of target templates. However, most …

In this paper, we propose a recurrent filter generation methods for visual tracking. We
directly feed the target's image patch to a recurrent neural network (RNN) to estimate an …

目的目标跟踪是计算机视觉中的关键问题, 在人机交互, 行为识别等领域有着非常广泛的应用.
最近, 相关滤波理论由于其高效性和鲁棒性, 被用于目标跟踪领域, 取得了一系列新的进展 …

Abstract Convolutional Neural Networks (CNN) have been demonstrated to achieve state-of-
the-art performance in visual object tracking task. However, existing CNN-based trackers …

Abstract We propose FuCoLoT–a Fu lly Co rrelational Lo ng-term T racker. It exploits the
novel DCF constrained filter learning method to design a detector that is able to re-detect the …

Recent advances in visual tracking have witnessed the importance of discriminative
classifiers tasked with distinguishing the target from the background. However, a single …

We study active object tracking, where a tracker takes as input the visual observation (ie
frame sequence) and produces the camera control signal (eg, move forward, turn left, etc) …

Motion models have been proved to be a crucial part in the visual tracking process. In recent
trackers, particle filter and sliding windows-based motion models have been widely used …