13 citations · 28 across the 18 of their papers we have counts for
19 papers
AvatarMix: Identity-Preserving Cross-Avatar Composition for Outfit Personalization
Zhaorong Wang, Yoshihiro Kanamori, Yuki Endo
Existing 3D avatar outfit transfer methods face distinct challenges: approaches that lift 2D edits to 3D often suffer from outfit or identity quality degradation, while those that…
FontUse: A Data-Centric Approach to Style- and Use-Case-Conditioned In-Image Typography
Xia Xin, Yuki Endo, Yoshihiro Kanamori
Recent text-to-image models can generate high-quality images from natural-language prompts, yet controlling typography remains challenging: requested typographic appearance is ofte…
Person-In-Situ: Scene-Consistent Human Image Insertion with Occlusion-Aware Pose Control
Shun Masuda, Yuki Endo, Yoshihiro Kanamori
Compositing human figures into scene images has broad applications in areas such as entertainment and advertising. However, existing methods often cannot handle occlusion of the in…
TerraFusion: Joint Generation of Terrain Geometry and Texture Using Latent Diffusion Models
Kazuki Higo, Toshiki Kanai, Yuki Endo +1
3D terrain models are essential in fields such as video game development and film production. Since surface color often correlates with terrain geometry, capturing this relationshi…
FreeUV: Ground-Truth-Free Realistic Facial UV Texture Recovery via Cross-Assembly Inference Strategy
Xingchao Yang, Takafumi Taketomi, Yuki Endo +1
Recovering high-quality 3D facial textures from single-view 2D images is a challenging task, especially under constraints of limited data and complex facial details such as makeup,…
SelfAge: Personalized Facial Age Transformation Using Self-reference Images
Taishi Ito, Yuki Endo, Yoshihiro Kanamori
Age transformation of facial images is a technique that edits age-related person's appearances while preserving the identity. Existing deep learning-based methods can reproduce nat…
All-frequency Full-body Human Image Relighting
Daichi Tajima, Yoshihiro Kanamori, Yuki Endo
Relighting of human images enables post-photography editing of lighting effects in portraits. The current mainstream approach uses neural networks to approximate lighting effects w…
EG-HumanNeRF: Efficient Generalizable Human NeRF Utilizing Human Prior for Sparse View
Zhaorong Wang, Yoshihiro Kanamori, Yuki Endo
Generalizable neural radiance field (NeRF) enables neural-based digital human rendering without per-scene retraining. When combined with human prior knowledge, high-quality human r…
3D View Optimization for Improving Image Aesthetics
Taichi Uchida, Yoshihiro Kanamori, Yuki Endo
Achieving aesthetically pleasing photography necessitates attention to multiple factors, including composition and capture conditions, which pose challenges to novices. Prior resea…
Makeup Prior Models for 3D Facial Makeup Estimation and Applications
Xingchao Yang, Takafumi Taketomi, Yuki Endo +1
In this work, we introduce two types of makeup prior models to extend existing 3D face prior models: PCA-based and StyleGAN2-based priors. The PCA-based prior model is a linear mod…
DiffBody: Diffusion-based Pose and Shape Editing of Human Images
Yuta Okuyama, Yuki Endo, Yoshihiro Kanamori
Pose and body shape editing in a human image has received increasing attention. However, current methods often struggle with dataset biases and deteriorate realism and the person's…
Masked-Attention Diffusion Guidance for Spatially Controlling Text-to-Image Generation
Yuki Endo
Text-to-image synthesis has achieved high-quality results with recent advances in diffusion models. However, text input alone has high spatial ambiguity and limited user controllab…
StyleHumanCLIP: Text-guided Garment Manipulation for StyleGAN-Human
Takato Yoshikawa, Yuki Endo, Yoshihiro Kanamori
This paper tackles text-guided control of StyleGAN for editing garments in full-body human images. Existing StyleGAN-based methods suffer from handling the rich diversity of garmen…
User-Controllable Latent Transformer for StyleGAN Image Layout Editing
Yuki Endo
Latent space exploration is a technique that discovers interpretable latent directions and manipulates latent codes to edit various attributes in images generated by generative adv…
Relighting Humans in the Wild: Monocular Full-Body Human Relighting with Domain Adaptation
Daichi Tajima, Yoshihiro Kanamori, Yuki Endo
The modern supervised approaches for human image relighting rely on training data generated from 3D human models. However, such datasets are often small (e.g., Light Stage data wit…
Diversifying Semantic Image Synthesis and Editing via Class- and Layer-wise VAEs
Yuki Endo, Yoshihiro Kanamori
Semantic image synthesis is a process for generating photorealistic images from a single semantic mask. To enrich the diversity of multimodal image synthesis, previous methods have…
Few-shot Semantic Image Synthesis Using StyleGAN Prior
Yuki Endo, Yoshihiro Kanamori
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 pix…
Animating Landscape: Self-Supervised Learning of Decoupled Motion and Appearance for Single-Image Video Synthesis
Yuki Endo, Yoshihiro Kanamori, Shigeru Kuriyama
Automatic generation of a high-quality video from a single image remains a challenging task despite the recent advances in deep generative models. This paper proposes a method that…
Relighting Humans: Occlusion-Aware Inverse Rendering for Full-Body Human Images
Yoshihiro Kanamori, Yuki Endo
Relighting of human images has various applications in image synthesis. For relighting, we must infer albedo, shape, and illumination from a human portrait. Previous techniques rel…