Deep convolutional and recurrent neural networks have delivered significant advancements
in object detection and tracking. However, current models handle detection and tracking …

While generic object detection has achieved large improvements with rich feature
hierarchies from deep nets, detecting small objects with poor visual cues remains …

Detecting tiny objects in a high-resolution video is challenging because the visual
information is little and unreliable. Specifically, the challenge includes very low resolution of …

A lot a research is focused on object detection and it has achieved significant advances with
deep learning techniques in recent years. Inspite of the existing research, these algorithms …

Multi-object tracking (MOT) has made great progress in recent years, but there are still some
problems. Most MOT algorithms follow tracking-by-detection framework, which separates …

This thesis embarks on an exploration into the evolution of the next generation of visual
detection and tracking systems, delineating four crucial subtopics: 1) model architecture …

Object detection and tracking from airborne imagery draws attention to the parallel
development of UAV systems and computer vision technologies. Aerial imagery has its own …

Object detection and tracking is one of the most important and challenging branches in
computer vision, and have been widely applied in various fields, such as health-care …

Recent advancements in tracking methods, particularly correlative-filter-based methods, can
be utilized to support object detection to achieve the desired accuracy and speed. This is …

Interacting with the environment, such as object detection and tracking, is a crucial ability of
mobile robots. Besides high accuracy, efficiency in terms of processing effort and energy …