3 citations · 3 across the 2 of their papers we have counts for
6 papers · 1 filter
Video2StyleGAN: Disentangling Local and Global Variations in a Video
Rameen Abdal, Peihao Zhu, Niloy J. Mitra +1
Image editing using a pretrained StyleGAN generator has emerged as a powerful paradigm for facial editing, providing disentangled controls over age, expression, illumination, etc.…
Labels4Free: Unsupervised Segmentation using StyleGAN
Rameen Abdal, Peihao Zhu, Niloy Mitra +1
We propose an unsupervised segmentation framework for StyleGAN generated objects. We build on two main observations. First, the features generated by StyleGAN hold valuable informa…
Improved StyleGAN Embedding: Where are the Good Latents?
Peihao Zhu, Rameen Abdal, Yipeng Qin +2
StyleGAN is able to produce photorealistic images that are almost indistinguishable from real photos. The reverse problem of finding an embedding for a given image poses a challeng…
SEAN: Image Synthesis with Semantic Region-Adaptive Normalization
Peihao Zhu, Rameen Abdal, Yipeng Qin +1
We propose semantic region-adaptive normalization (SEAN), a simple but effective building block for Generative Adversarial Networks conditioned on segmentation masks that describe…
Image2StyleGAN++: How to Edit the Embedded Images?
Rameen Abdal, Yipeng Qin, Peter Wonka
We propose Image2StyleGAN++, a flexible image editing framework with many applications. Our framework extends the recent Image2StyleGAN in three ways. First, we introduce noise opt…
Image2StyleGAN: How to Embed Images Into the StyleGAN Latent Space?
Rameen Abdal, Yipeng Qin, Peter Wonka
We propose an efficient algorithm to embed a given image into the latent space of StyleGAN. This embedding enables semantic image editing operations that can be applied to existing…