Recent years have witnessed enormous progress in AI-related fields such as computer
vision, machine learning, and autonomous vehicles. As with any rapidly growing field, it …

Abstract Multiple Object Tracking (MOT) has gained increasing attention due to its academic
and commercial potential. Although different approaches have been proposed to tackle this …

Standardized benchmarks have been crucial in pushing the performance of computer vision
algorithms, especially since the advent of deep learning. Although leaderboards should not …

Tracking multiple persons in a monocular video of a crowded scene is a challenging task.
Humans can master it even if they loose track of a person locally by re-identifying the same …

The majority of existing solutions to the Multi-Target Tracking (MTT) problem do not combine
cues over a long period of time in a coherent fashion. In this paper, we present an online …

Abstract We propose Quadruplet Convolutional Neural Networks (Quad-CNN) for multi-
object tracking, which learn to associate object detections across frames using quadruplet …

This paper presents a survey on the latest methods of moving object detection in video
sequences captured by a moving camera. Although many researches and excellent works …

This paper introduces a system capable of real-time video surveillance in low-end edge
computing environment by combining object detection tracking algorithm. Recently, the …

Tracking-by-detection has become a popular tracking paradigm in recent years. Due to the
fact that detections within this framework are regarded as points in the tracking process, it …

Standardized benchmarks are crucial for the majority of computer vision applications.
Although leaderboards and ranking tables should not be over-claimed, benchmarks often …