3 papers
cs.CV2025
SALAD: Skeleton-aware Latent Diffusion for Text-driven Motion Generation and Editing
Seokhyeon Hong, Chaelin Kim, Serin Yoon +3
Text-driven motion generation has advanced significantly with the rise of denoising diffusion models. However, previous methods often oversimplify representations for the skeletal…
cs.GR2025
ASMR: Adaptive Skeleton-Mesh Rigging and Skinning via 2D Generative Prior
Seokhyeon Hong, Soojin Choi, Chaelin Kim +2
Despite the growing accessibility of skeletal motion data, integrating it for animating character meshes remains challenging due to diverse configurations of both skeletons and mes…
cs.GR2025
AnyMoLe: Any Character Motion In-betweening Leveraging Video Diffusion Models
Kwan Yun, Seokhyeon Hong, Chaelin Kim +1
Despite recent advancements in learning-based motion in-betweening, a key limitation has been overlooked: the requirement for character-specific datasets. In this work, we introduc…