8 papers
Accelerated Likelihood Maximization for Diffusion-based Versatile Content Generation
Hyunsoo Lee, Inwoo Hwang, Young Min Kim
Generating diverse, coherent, and plausible content from partially given inputs remains a fundamental challenge for diffusion models. Existing approaches face clear limitations: tr…
Analogical Trajectory Transfer
Junho Kim, Eun Sun Lee, Gwangtak Bae +2
We study analogical trajectory transfer, where the goal is to translate motion trajectories in one 3D environment to a semantically analogous location in another. Such a capacity w…
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…
ScaleMoGen: Autoregressive Next-Scale Prediction for Human Motion Generation
Inwoo Hwang, Hojun Jang, Bing Zhou +3
We present ScaleMoGen, a scale-wise autoregressive framework for text-driven human motion generation. Unlike conventional autoregressive approaches that rely on standard next-token…
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…
SceneMI: Motion In-betweening for Modeling Human-Scene Interactions
Inwoo Hwang, Bing Zhou, Young Min Kim +2
Modeling human-scene interactions (HSI) is essential for understanding and simulating everyday human behaviors. Recent approaches utilizing generative modeling have made progress i…