2 citations · 2 across the 8 of their papers we have counts for
9 papers
Length-varying Neural Motion Stitching via Cluster Transition Graph
Haemin Kim, Junghyun Nam, Seokhyeon Hong +2
Motion stitching aims to create new character animations by seamlessly combining existing motion sequences. Existing approaches often require manual selection of transition range o…
ReCHOIR: Contact-guided Human Object Interaction Retargeting to Diverse Characters
Chaelin Kim, Seokhyeon Hong, Kwan Yun +3
We present ReCHOIR, a novel contact-guided motion retargeting method for transferring human object interaction (HOI) motions across diverse humanoid characters. Unlike prior motion…
Skinned Motion Retargeting via Artifact-driven Kinematic Prior Refinement
Seokhyeon Hong, Chaelin Kim, Inseo Jang +2
Motion retargeting aims to transfer a source motion to target characters with different skeletal structures, proportions, and body shapes. Although recent neural retargeting method…
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…