Deep learning in multi-object detection and tracking: state of the art
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 …
computer vision, and have been widely applied in various fields, such as health-care …
Recent advances in deep learning for object detection
Object detection is a fundamental visual recognition problem in computer vision and has
been widely studied in the past decades. Visual object detection aims to find objects of …
been widely studied in the past decades. Visual object detection aims to find objects of …
A comprehensive review of object detection with deep learning
R Kaur, S Singh - Digital Signal Processing, 2023 - Elsevier
In the realm of computer vision, Deep Convolutional Neural Networks (DCNNs) have
demonstrated excellent performance. Video Processing, Object Detection, Image …
demonstrated excellent performance. Video Processing, Object Detection, Image …
A review of object detection based on deep learning
With the rapid development of deep learning techniques, deep convolutional neural
networks (DCNNs) have become more important for object detection. Compared with …
networks (DCNNs) have become more important for object detection. Compared with …
Object detection with deep learning: A review
Due to object detection's close relationship with video analysis and image understanding, it
has attracted much research attention in recent years. Traditional object detection methods …
has attracted much research attention in recent years. Traditional object detection methods …
SA-FPN: An effective feature pyramid network for crowded human detection
X Zhou, L Zhang - Applied Intelligence, 2022 - Springer
The crowded scenario not only contains instances at various scales but also introduces a
variety of occlusion patterns ranging from non-occluded situations to heavily occluded …
variety of occlusion patterns ranging from non-occluded situations to heavily occluded …
Occlusion-aware R-CNN: Detecting pedestrians in a crowd
Pedestrian detection in crowded scenes is a challenging problem since the pedestrians
often gather together and occlude each other. In this paper, we propose a new occlusion …
often gather together and occlude each other. In this paper, we propose a new occlusion …
Computer vision and deep learning techniques for pedestrian detection and tracking: A survey
Pedestrian detection and tracking have become an important field in the computer vision
research area. This growing interest, started in the last decades, might be explained by the …
research area. This growing interest, started in the last decades, might be explained by the …
Citypersons: A diverse dataset for pedestrian detection
S Zhang, R Benenson… - Proceedings of the IEEE …, 2017 - openaccess.thecvf.com
Convnets have enabled significant progress in pedestrian detection recently, but there are
still open questions regard-ing suitable architectures and training data. We revisit CNN …
still open questions regard-ing suitable architectures and training data. We revisit CNN …
Repulsion loss: Detecting pedestrians in a crowd
Detecting individual pedestrians in a crowd remains a challenging problem since the
pedestrians often gather together and occlude each other in real-world scenarios. In this …
pedestrians often gather together and occlude each other in real-world scenarios. In this …