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Purifying Real Images with an Attention-guided Style Transfer Network for Gaze Estimation
Different from the previous methods, this paper try to purify real image by extracting discriminative and robust features to convert outdoor real images to indoor synthetic images.
Mask-guided Style Transfer Network for Purifying Real Images
To solve this problem, the previous method learned a model to improve the realism of the synthetic images.
Purifying Naturalistic Images through a Real-time Style Transfer Semantics Network
To solve this problem, the previous method learned a model to improve the realism of the synthetic image.
Guiding Intelligent Surveillance System by learning-by-synthesis gaze estimation
In an attempt to address this issue, previous method is to improve the realism of synthetic images by learning a model.
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