Human-Motion Guided Frame Selection with Adaptive Gamma Correction for Violent Video Classification
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-58561-6_2
Reference19 articles.
1. Mumtaz, N., et al.: An overview of violence detection techniques: current challenges and future directions. Artif. Intell. Rev. 56, 4641–4666 (2023). https://doi.org/10.1007/s10462-022-10285-3
2. Wang, L., et al.: Temporal segment networks for action recognition in videos. IEEE Trans. Pattern Anal. Mach. Intell. 41(11), 2740–2755 (2018)
3. Yelmanov, S., Romanyshyn, Y.: A new technique for image enhancement by adaptive power-law intensity transformation. In: 2021 IEEE 12th International Conference on Electronics and Information Technologies (ELIT), pp. 90–94. IEEE (2021)
4. Cheng, M., Cai, K., Li, M.: RWF-2000: an open large scale video database for violence detection. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 4183–4190 (2021). https://doi.org/10.1109/ICPR48806.2021.9412502
5. Islam, Z., Rukonuzzaman, M., Ahmed, R., Kabir, M.H., Farazi, M.: Efficient two-stream network for violence detection using separable convolutional LSTM. In: 2021 International Joint Conference on Neural Networks (IJCNN), pp. 1–8. IEEE (2021)
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