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Found 12 papers, 8 papers with code
Gaussian Shell Maps for Efficient 3D Human Generation
Instead of rasterizing the shells directly, we sample 3D Gaussians on the shells whose attributes are encoded in the texture features.
3DAvatarGAN: Bridging Domains for Personalized Editable Avatars
Finally, we propose a novel inversion method for 3D-GANs linking the latent spaces of the source and the target domains.
Video2StyleGAN: Disentangling Local and Global Variations in a Video
Image editing using a pretrained StyleGAN generator has emerged as a powerful paradigm for facial editing, providing disentangled controls over age, expression, illumination, etc.
CLIP2StyleGAN: Unsupervised Extraction of StyleGAN Edit Directions
The success of StyleGAN has enabled unprecedented semantic editing capabilities, on both synthesized and real images.
Mind the Gap: Domain Gap Control for Single Shot Domain Adaptation for Generative Adversarial Networks
The input to our method is trained GAN that can produce images in domain A and a single reference image I_B from domain B.
Barbershop: GAN-based Image Compositing using Segmentation Masks
Seamlessly blending features from multiple images is extremely challenging because of complex relationships in lighting, geometry, and partial occlusion which cause coupling between different parts of the image.
Labels4Free: Unsupervised Segmentation using StyleGAN
We propose an unsupervised segmentation framework for StyleGAN generated objects.
Improved StyleGAN Embedding: Where are the Good Latents?
First, we introduce a new normalized space to analyze the diversity and the quality of the reconstructed latent codes.
StyleFlow: Attribute-conditioned Exploration of StyleGAN-Generated Images using Conditional Continuous Normalizing Flows
We evaluate our method using the face and the car latent space of StyleGAN, and demonstrate fine-grained disentangled edits along various attributes on both real photographs and StyleGAN generated images.
SEAN: Image Synthesis with Semantic Region-Adaptive Normalization
Using SEAN normalization, we can build a network architecture that can control the style of each semantic region individually, e. g., we can specify one style reference image per region.
Image2StyleGAN++: How to Edit the Embedded Images?
We propose Image2StyleGAN++, a flexible image editing framework with many applications.
Image2StyleGAN: How to Embed Images Into the StyleGAN Latent Space?
We propose an efficient algorithm to embed a given image into the latent space of StyleGAN.
