Content-Aware GAN Compression.
作者： Federico Perazzi , Zhe Lin , Yijun Li , Yuchen Liu , S. Y. Kung
DOI:
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摘要: Generative adversarial networks (GANs), eg, StyleGAN2, play a vital role in various image generation and synthesis tasks, yet their notoriously high computational cost hinders their …
arxiv.org参考文章(53)
Diederik P. Kingma, Jimmy Ba, Adam: A Method for Stochastic Optimization arXiv: Learning. ,(2014)
Vuong Le, Jonathan Brandt, Zhe Lin, Lubomir Bourdev, Thomas S. Huang, Interactive Facial Feature Localization Computer Vision – ECCV 2012. pp. 679- 692 ,(2012) , 10.1007/978-3-642-33712-3_49
Geoffrey Hinton, Oriol Vinyals, Jeff Dean, Distilling the Knowledge in a Neural Network arXiv: Machine Learning. ,(2015)
Max Jaderberg, Andrea Vedaldi, Andrew Zisserman, Speeding up Convolutional Neural Networks with Low Rank Expansions british machine vision conference. ,(2014) , 10.5244/C.28.88
Dong C. Liu, Jorge Nocedal, On the limited memory BFGS method for large scale optimization Mathematical Programming. ,vol. 45, pp. 503- 528 ,(1989) , 10.1007/BF01589116
, Generative Adversarial Nets neural information processing systems. ,vol. 27, pp. 2672- 2680 ,(2014) , 10.3156/JSOFT.29.5_177_2
Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jon Shlens, Zbigniew Wojna, Rethinking the Inception Architecture for Computer Vision computer vision and pattern recognition. pp. 2818- 2826 ,(2016) , 10.1109/CVPR.2016.308
Bolei Zhou, Aditya Khosla, Agata Lapedriza, Aude Oliva, Antonio Torralba, Learning Deep Features for Discriminative Localization computer vision and pattern recognition. pp. 2921- 2929 ,(2016) , 10.1109/CVPR.2016.319
Mohammad Rastegari, Vicente Ordonez, Joseph Redmon, Ali Farhadi, XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks Computer Vision – ECCV 2016. pp. 525- 542 ,(2016) , 10.1007/978-3-319-46493-0_32
Yoshua Bengio, Matthieu Courbariaux, Ran El-Yaniv, Itay Hubara, Daniel Soudry, Binarized Neural Networks: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1 arXiv: Learning. ,(2016)