In this paper, we propose a new aerial video dataset and benchmark for low altitude UAV
target tracking, as well as, a photo-realistic UAV simulator that can be coupled with tracking …

In recent years, many tracking algorithms achieve impressive performance via fusing
multiple types of features, however, most of them fail to fully explore the context among the …

Correlation filter (CF) based trackers have recently gained a lot of popularity due to their
impressive performance on benchmark datasets, while maintaining high frame rates. A …

With efficient appearance learning models, discriminative correlation filter (DCF) has been
proven to be very successful in recent video object tracking benchmarks and competitions …

In this paper, we propose a multi-task correlation particle filter (MCPF) for robust visual
tracking. We first present the multi-task correlation filter (MCF) that takes the …

We propose a new Group Feature Selection method for Discriminative Correlation Filters
(GFS-DCF) based visual object tracking. The key innovation of the proposed method is to …

Convolutional neural network (CNN) has drawn increasing interest in visual tracking owing
to its powerfulness in feature extraction. Most existing CNN-based trackers treat tracking as …

In this paper, we propose a multi-task correlation particle filter (MCPF) for robust visual
tracking. We first present the multi-task correlation filter (MCF) that takes the …

Discriminative correlation filters (DCF) with powerful feature descriptors have proven to be
very effective for advanced visual object tracking approaches. However, due to the fixed …

Most correlation filter (CF) based trackers utilize the circulant structure of the training data to
learn a linear filter that best regresses this data to a hand-crafted target response. These …