Pedestrian detection is a key problem in computer vision, with several applications that have
the potential to positively impact quality of life. In recent years, the number of approaches to …

The goal of this paper is to review the state-of-the-art progress on visual tracking methods,
classify them into different categories, as well as identify future trends. Visual tracking is a …

Recently, multi-view representation learning has become a rapidly growing direction in
machine learning and data mining areas. This paper introduces two categories for multi …

This paper introduces VEDAI: Vehicle Detection in Aerial Imagery a new database of aerial
images provided as a tool to benchmark automatic target recognition algorithms in …

This paper deals with semantic segmentation of high-resolution (aerial) images where a
semantic class label is assigned to each pixel via supervised classification as a basis for …

Paper-by-paper results make it easy to miss the forest for the trees. We analyse the
remarkable progress of the last decade by discussing the main ideas explored in the 40+ …

Feature extraction, deformation handling, occlusion handling, and classi? cation are four
important components in pedestrian detection. Existing methods learn or design these …

Multi-resolution image features may be approximated via extrapolation from nearby scales,
rather than being computed explicitly. This fundamental insight allows us to design object …

Pedestrian detection is a problem of considerable practical interest. Adding to the list of
successful applications of deep learning methods to vision, we report state-of-theart and …

Effectively detecting pedestrians in various environments would significantly improve driving
safety for autonomous vehicles. However, the degrpted visibility and blurred outline and …