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Found 3 papers, 2 papers with code
FICE: Text-Conditioned Fashion Image Editing With Guided GAN Inversion
We address these constraints by proposing a novel text-conditioned editing model, called FICE (Fashion Image CLIP Editing), capable of handling a wide variety of diverse text descriptions to guide the editing procedure.
High Resolution Face Editing with Masked GAN Latent Code Optimization
The proposed approach is based on an optimization procedure that directly optimizes the latent code of a pre-trained (state-of-the-art) Generative Adversarial Network (i. e., StyleGAN2) with respect to several constraints that ensure: (i) preservation of relevant image content, (ii) generation of the targeted facial attributes, and (iii) spatially--selective treatment of local image areas.
Face Hallucination Revisited: An Exploratory Study on Dataset Bias
This down-sampling (or degradation) procedure not only defines the characteristics of the LR training data, but also determines the type of image degradations the learned FH models are eventually able to handle.
