Papers Read on AI

StyleCLIP: Text-Driven Manipulation of StyleGAN Imagery


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In this work, we explore leveraging the power of recently introduced Contrastive Language-Image Pre-training (CLIP) models in order to develop a text-based interface for StyleGAN image manipulation that does not require such manual effort.
2021: Or Patashnik, Zongze Wu, E. Shechtman, D. Cohen-Or, D. Lischinski
Methods: Adaptive Instance Normalization • Convolution • Dense Connections • Feedforward Network • Leaky ReLU • R1 Regularization • StyleGAN
https://arxiv.org/pdf/2103.17249v1.pdf
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