1 citations · 1 across the 7 of their papers we have counts for
Showing cs.CVShow all
3 papers · 1 filter
cs.CV2026
Astrolabe: Spherical-Map Guidance Across Diffusion Pipelines for Full-Body Capture from Unconstrained Images
Shuliang Zhu, Qi Wang, Ryugo Morita +1
Full-body capture from unconstrained photographs requires global correspondence across arbitrary views, poses, crops, and occlusions. Yet pose, geometry, and foundation features es…
cs.CV2026
Few-step Generative Models as Lossy Compression
Fuma Kimishima, Jinjia Zhou
DiffC provides a principled way to reuse pre-trained diffusion models for lossy compression, but its encoding and decoding procedures remain slow because they require many discreti…
cs.CV2024
TKG-DM: Training-free Chroma Key Content Generation Diffusion Model
Ryugo Morita, Stanislav Frolov, Brian Bernhard Moser +4
Diffusion models have enabled the generation of high-quality images with a strong focus on realism and textual fidelity. Yet, large-scale text-to-image models, such as Stable Diffu…