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Found 9 papers, 6 papers with code
Makeup Prior Models for 3D Facial Makeup Estimation and Applications
Although there is a trade-off between the two models, both are applicable to 3D facial makeup estimation and related applications.
DiffBody: Diffusion-based Pose and Shape Editing of Human Images
Because this initial textured body model has artifacts due to occlusion and the inaccurate body shape, the rendered image undergoes a diffusion-based refinement, in which strong noise destroys body structure and identity whereas insufficient noise does not help.
Masked-Attention Diffusion Guidance for Spatially Controlling Text-to-Image Generation
To address this issue, we propose masked-attention guidance, which can generate images more faithful to semantic masks via indirect control of attention to each word and pixel by manipulating noise images fed to diffusion models.
StyleHumanCLIP: Text-guided Garment Manipulation for StyleGAN-Human
We propose a framework for text-guided full-body human image synthesis via an attention-based latent code mapper, which enables more disentangled control of StyleGAN than existing mappers.
User-Controllable Latent Transformer for StyleGAN Image Layout Editing
In our framework, the user annotates a StyleGAN image with locations they want to move or not and specifies a movement direction by mouse dragging.
Diversifying Semantic Image Synthesis and Editing via Class- and Layer-wise VAEs
To handle individual factors that determine object styles, we propose a class- and layer-wise extension to the variational autoencoder (VAE) framework that allows flexible control over each object class at the local to global levels by learning multiple latent spaces.
Few-shot Semantic Image Synthesis Using StyleGAN Prior
This paper tackles a challenging problem of generating photorealistic images from semantic layouts in few-shot scenarios where annotated training pairs are hardly available but pixel-wise annotation is quite costly.
Animating Landscape: Self-Supervised Learning of Decoupled Motion and Appearance for Single-Image Video Synthesis
Automatic generation of a high-quality video from a single image remains a challenging task despite the recent advances in deep generative models.
Relighting Humans: Occlusion-Aware Inverse Rendering for Full-Body Human Images
Based on supervised learning using convolutional neural networks (CNNs), we infer not only an albedo map, illumination but also a light transport map that encodes occlusion as nine SH coefficients per pixel.
