The DOI matches its Crossref record; 38 of the 38 references it cites were found in a registry or an index.
Scale Aggregation Network for Accurate and Efficient Crowd Counting
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Citations
Cites
Very Deep Convolutional Networks for Large-Scale Image Recognition
Simonyan, K., & Zisserman, A. (2014) · arXiv · doi:10.48550/arxiv.1409.1556 · Cited by 114,148
ImageNet classification with deep convolutional neural networks
Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2017) · Communications of the ACM · doi:10.1145/3065386 · Cited by 112,155
Adam: A Method for Stochastic Optimization
Kingma, D. P., & Ba, J. (2014) · arXiv · doi:10.48550/arxiv.1412.6980 · Cited by 98,946
Image quality assessment: from error visibility to structural similarity
Wang, Z., Bovik, A. C., Sheikh, H. R., & Simoncelli, E. P. (2004) · IEEE Transactions on Image Processing · doi:10.1109/tip.2003.819861 · Cited by 57,892
Self-citationGoing deeper with convolutions
Szegedy, C., Liu, W., Jia, Y., Sermanet, P., Reed, S., Anguelov, D., Erhan, D., Vanhoucke, V., & Rabinovich, A. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7298594 · Cited by 48,562
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Ioffe, S., & Szegedy, C. (2015) · arXiv · doi:10.48550/arxiv.1502.03167 · Cited by 27,818
Image-to-Image Translation with Conditional Adversarial Networks
Isola, P., Zhu, J.-Y., Zhou, T., & Efros, A. A. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.632 · Cited by 22,930
GAN（Generative Adversarial Nets）
(2017) · Journal of Japan Society for Fuzzy Theory and Intelligent Informatics · doi:10.3156/jsoft.29.5_177_2 · Cited by 19,270
Object Detection with Discriminatively Trained Part-Based Models
Felzenszwalb, P. F., Girshick, R. B., McAllester, D., & Ramanan, D. (2010) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2009.167 · Cited by 9,853
SIFT: predicting amino acid changes that affect protein function
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Cited by
Learning From Synthetic Data for Crowd Counting in the Wild
Wang, Q., Gao, J., Lin, W., & Yuan, Y. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2019.00839 · Cited by 654
NWPU-Crowd: A Large-Scale Benchmark for Crowd Counting and Localization
Wang, Q., Gao, J., Lin, W., & Li, X. (2021) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2020.3013269 · Cited by 510
Decoupled Two-Stage Crowd Counting and Beyond
Cheng, J., Xiong, H., Cao, Z., & Lu, H. (2021) · IEEE Transactions on Image Processing · doi:10.1109/tip.2021.3055631 · Cited by 103
Attention-Based Deep Bayesian Counting For AI-Augmented Agriculture
Wang, Y., Gu, M., Zhou, M., & Qian, X. (2022) · Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems · doi:10.1145/3560905.3568417 · Cited by 5
Metadata
- Authors
- Cao, X., Wang, Z., Zhao, Y., & Su, F.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2018
- Pages
- 757-773
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2895051362
- Cited by
- 733
- References
- 38
- FWCI
- 23.54
- Type
- conference paper
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Scale Aggregation Network for Accurate and Efficient Crowd Counting. https://app.cochat.ai/papers/10.1007/978-3-030-01228-1_45
- The paper
- Cao, X., Wang, Z., Zhao, Y., & Su, F. (2018). Scale Aggregation Network for Accurate and Efficient Crowd Counting. Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-030-01228-1_45
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
