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Short Communication | Open Access

Jittor-GAN: A fast-training generative adversarial network model zoo based on Jittor

BNRist, Tsinghua University, Beijing 100084, China
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References

[1]
Goodfellow, I. J.; Pouget-Abadie, J.; Mirza, M.; Xu, B.; Warde-Farley, D.; Ozair, S.; Courville, A.; Bengio, Y. Generative adversarial nets. In: Proceedings of the 27th International Conference on Neural Information Processing Systems, Vol. 2, 2672-2680, 2014.
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Hu, S.-M.; Liang, D.; Yang, G.-Y.; Yang, G.-W.; Zhou, W.-Y. Jittor: A novel deep learning framework with meta-operators and unified graph execution. Science China Information Science Vol. 63, No. 12, 222103, 2020.
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Cao, Y.-J.; Jia, L.-L.; Chen, Y.-X.; Lin, N.; Yang, C.; Zhang, B.; Liu, Z.; Li, X.-X.; Dai, H.-H. Recent advances of generative adversarial networks in com-puter vision. IEEE Access Vol. 7, 14985-15006, 2019.
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Computational Visual Media
Volume 7 Issue 1,
March 2021
Pages 153-157
DOI: 10.1007/s41095-021-0203-2
Cite this article:
Zhou W-Y, Yang G-W, Hu S-M. Jittor-GAN: A fast-training generative adversarial network model zoo based on Jittor. Computational Visual Media, 2021, 7(1): 153-157. https://doi.org/10.1007/s41095-021-0203-2

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Received: 26 October 2020
Accepted: 02 January 2021
Published: 15 January 2021
© The Author(s) 2021

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