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Qiang Wen

5 accepted papers

2021

Discovering Interpretable Latent Space Directions of GANs Beyond Binary Attributes

CVPR 2021poster

Generative adversarial networks (GANs) learn to map noise latent vectors to high-fidelity image outputs. It is found that the input latent space shows semantic correlations with the output image space. Recent works aim to interpret the latent space and discover meaningful directions that correspond…

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