Video Codec Using Machine Learning Image Compression Techniques
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-64847-2_6
Reference11 articles.
1. Bidwe, R, Mishra, S. Patil, S., Shaw, K., Vora, D., Kotecha, K., Zope, B.: Deep learning approaches for video compression: a bibliometric analysis. Big Data Cognitive Comput. 6(2), 44 (2022)
2. Liu, D., Li, Y., Lin, J., Li, H., Wu, F.: Deep learning-based video coding: a review and a case study. ACM Comput. Surv. 53(1), 1–35 (2020)
3. Rippel, O., Nair, S., Lew, C., Branson, S., Anderson, A., Bourdev, L.: Learned video compression. In: International Conference on Computer Vision 2019, pp. 3454–3463. IEEE/CVF (2019)
4. Zhang, F., Ma, D., Feng, C., Bull, D.: Video compression With CNN-based postprocessing. IEEE Multimedia 28(4), 74–83 (2021)
5. Liu, Z., Herranz, L., Yang, F., Zhang, S., Wan, S., Mrak, M., Blanch, M.: Slimmable video codec. In: Conference on Computer Vision and Pattern Recognition 2022, pp. 1743–1747. IEEE/CVF (2022)
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