activity
20232026
most citedPMP: Learning to Physically Interact with Environments using Part-wise Motion Priors

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV2026

EgoForce: Robust Online Egocentric Motion Reconstruction via Diffusion Forcing

Inwoo Hwang, Donggeun Lim, Hojun Jang +1

With recent advances in embodied agents and AR devices, egocentric observations are readily available as input for real-world interactive online applications. However, egocentric v…

cs.CV2025

Event-Driven Storytelling with Multiple Lifelike Humans in a 3D Scene

Donggeun Lim, Jinseok Bae, Inwoo Hwang +3

In this work, we propose a framework that creates a lively virtual dynamic scene with contextual motions of multiple humans. Generating multi-human contextual motion requires holis…

cs.GR2025

Versatile Physics-based Character Control with Hybrid Latent Representation

Jinseok Bae, Jungdam Won, Donggeun Lim +2

We present a versatile latent representation that enables physically simulated character to efficiently utilize motion priors. To build a powerful motion embedding that is shared a…

cs.GR2025

Motion Synthesis with Sparse and Flexible Keyjoint Control

Inwoo Hwang, Jinseok Bae, Donggeun Lim +1

Creating expressive character animations is labor-intensive, requiring intricate manual adjustment of animators across space and time. Previous works on controllable motion generat…

cs.GR2023★ 1 cited

PMP: Learning to Physically Interact with Environments using Part-wise Motion Priors

Jinseok Bae, Jungdam Won, Donggeun Lim +2

We present a method to animate a character incorporating multiple part-wise motion priors (PMP). While previous works allow creating realistic articulated motions from reference da…