4 citations · 7 across the 3 of their papers we have counts for
5 papers
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…