The DOI matches its Crossref record; 113 of the 113 references it cites were found in a registry or an index.
New Generation Deep Learning for Video Object Detection: A Survey
Abstract
Video object detection, a basic task in the computer vision field, is rapidly evolving and widely used. In recent years, deep learning methods have rapidly become widespread in the field of video object detection, achieving excellent results compared with those of traditional methods. However, the presence of duplicate information and abundant spatiotemporal information in video data poses a serious challenge to video object detection. Therefore, in recent years, many scholars have investigated deep learning detection algorithms in the context of video data and have achieved remarkable results. Considering the wide range of applications, a comprehensive review of the research related to video object detection is both a necessary and challenging task. This survey attempts to link and systematize the latest cutting-edge research on video object detection with the goal of classifying and analyzing video detection algorithms based on specific representative models. The differences and connections between video object detection and similar tasks are systematically demonstrated, and the evaluation metrics and video detection performance of nearly 40 models on two data sets are presented. Finally, the various applications and challenges facing video object detection are discussed.
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Cites
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Cited by
PACO: Parts and Attributes of Common Objects
Ramanathan, V., Kalia, A., Petrovic, V., Wen, Y., Zheng, B., Guo, B., Wang, R., Marquez, A., Kovvuri, R., Kadian, A., et al. (2023) · 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr52729.2023.00690 · Cited by 79
Human-inspired Perspectives: A Survey on AI Long-term Memory
He, Z., Lin, W., Zheng, H., Zhang, F., Jones, M. W., Aitchison, L., Xu, X., Liu, M., Kristensson, P. O., & Shen, J. (2024) · arXiv · doi:10.48550/arxiv.2411.00489 · Cited by 3
“Video understanding refers to tasks re-lated to video analysis such as recognition of entities and actions within videos and video content summarization [311, 312, 313, 314].”
Metadata
- Authors
- Jiao, L., Zhang, R., Liu, F., Yang, S., Hou, B., Li, L., & Tang, X.
- Venue
- IEEE Transactions on Neural Networks and Learning Systems
- Published
- 2022-08
- Volume
- 33
- Issue
- 8
- Pages
- 3195-3215
- ISSN
- 2162-237X (ISSN-L)
- 2162-2388
- OpenAlex
- W3127131334
- Cited by
- 259
- References
- 113
- FWCI
- 14.37
- Type
- journal article
- Language
- en
- Open access
- closed
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- Jiao, L., Zhang, R., Liu, F., Yang, S., Hou, B., Li, L., & Tang, X. (2022). New Generation Deep Learning for Video Object Detection: A Survey. IEEE Transactions on Neural Networks and Learning Systems. https://doi.org/10.1109/tnnls.2021.3053249
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