6 papers
Skinned Motion Retargeting with Spatially Adaptive Interaction Guidance
Soojin Choi, Seokhyeon Hong, Chaelin Kim +3
Retargeting motion across characters with varying body shapes while preserving interaction semantics, such as self-contact and near-body proximity, remains a challenging problem. W…
Deep Learning Based Facial Retargeting Using Local Patches
Yeonsoo Choi, Inyup Lee, Sihun Cha +3
In the era of digital animation, the quest to produce lifelike facial animations for virtual characters has led to the development of various retargeting methods. While the retarge…
FFaceNeRF: Few-shot Face Editing in Neural Radiance Fields
Kwan Yun, Chaelin Kim, Hangyeul Shin +1
Recent 3D face editing methods using masks have produced high-quality edited images by leveraging Neural Radiance Fields (NeRF). Despite their impressive performance, existing meth…
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…
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…
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…