Dynamic-Net: Tuning the Objective Without Re-training for Synthesis Tasks

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Generative adversarial nets

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Microsoft COCO: Common objects in context

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Image style transfer using convolutional neural networks

Leon A Gatys, Alexander S Ecker, and Matthias Bethge · 2016

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Deep residual learning for image recognition

Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016

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Perceptual losses for real-time style transfer and super-resolution

Justin Johnson, Alexandre Alahi, and Li Fei-Fei · 2016

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Cross-stitch networks for multi-task learning

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Unsupervised representation learning with deep convolutional generative adversarial networks

Alec Radford, Luke Metz, and Soumith Chintala · 2016

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A learned representation for artistic style

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Arbitrary style transfer in real-time with adaptive instance normalization

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Image-to-image translation with conditional adversarial networks

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Learning to discover cross-domain relations with generative adversarial networks

Taeksoo Kim, Moonsu Cha, Hyunsoo Kim, Jung Kwon Lee, and Jiwon Kim · 2017

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Photo-realistic single image super-resolution using a generative adversarial network

Christian Ledig, Lucas Theis, Ferenc Huszár, Jose Caballero, Andrew Cunningham, Alejandro Acosta, Andrew P Aitken, Alykhan Tejani, Johannes Totz, Zehan Wang, et al · 2017

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Learning without forgetting

The perception-distortion tradeoff

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Facelet-bank for fast portrait manipulation

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Gradnorm: Gradient normalization for adaptive loss balancing in deep multitask networks

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Image inpainting for irregular holes using partial convolutions

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Maintaining natural image statistics with the contextual loss

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The contextual loss for image transformation with non-aligned data

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