Revisiting Random Channel Pruning for Neural Network Compression

Li, Yawei; Adamczewski, Kamil; Li, Wen; Gu, Shuhang; Timofte, Radu; Van Gool, Luc

doi:10.1109/CVPR52688.2022.00029

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Conference Paper

Revisiting Random Channel Pruning for Neural Network Compression

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Adamczewski, Kamil
Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society;

External Resource

https://doi.org/10.1109/CVPR52688.2022.00029
(Publisher version)

https://doi.org/10.48550/arXiv.2205.05676
(Preprint)

https://openaccess.thecvf.com/content/CVPR2022/papers/Li_Revisiting_Random_Channel_Pruning_for_Neural_Network_Compression_CVPR_2022_paper.pdf
(Publisher version)

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Citation

Li, Y., Adamczewski, K., Li, W., Gu, S., Timofte, R., & Van Gool, L. (2022). Revisiting Random Channel Pruning for Neural Network Compression. In 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 191-201). Piscataway, NJ: IEEE. doi:10.1109/CVPR52688.2022.00029.

Cite as: https://hdl.handle.net/21.11116/0000-000F-E65A-9

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