6 papers
SnapPhysics: A Physics-Aware Scene Graph from a Single View for Interactive Mixed Reality Scenes
Suji Kang, Seok-Young Kim, Young Bin Kim +4
We propose SnapPhysics, a training-free framework that reconstructs 3D objects and estimates their physical properties such as mass, friction, and center of gravity from a single i…
DeWorldSG: Depth-Aware 3D Semantic Scene Graph Generation via World-Model Priors
Seok-Young Kim, Abdelrahman Elskhawy, Taewook Ha +4
We present DeWorldSG, a novel framework that generates spatio-temporally robust 3D Semantic Scene Graphs from RGB-D sequences. Existing methods often struggle to construct reliable…
Int3DNet: Scene-Motion Cross Attention Network for 3D Intention Prediction in Mixed Reality
Taewook Ha, Woojin Cho, Dooyoung Kim +1
We propose Int3DNet, a scene-aware network that predicts 3D intention areas directly from scene geometry and head-hand motion cues, enabling robust human intention prediction witho…
Task Breakpoint Generation using Origin-Centric Graph in Virtual Reality Recordings for Adaptive Playback
Selin Choi, Dooyoung Kim, Taewook Ha +2
We propose a method for generating task breakpoints based on an Origin-Centric Graph (OCG) to segment goal-oriented activity recordings into task units for adaptive playback in Vir…
Dense Hand-Object(HO) GraspNet with Full Grasping Taxonomy and Dynamics
Woojin Cho, Jihyun Lee, Minjae Yi +8
Existing datasets for 3D hand-object interaction are limited either in the data cardinality, data variations in interaction scenarios, or the quality of annotations. In this work,…
Meta-Objects: Interactive and Multisensory Virtual Objects Learned from the Real World for Use in Augmented Reality
Dooyoung Kim, Taewook Ha, Jinseok Hong +4
We introduce the concept of a meta-object, a next-generation virtual object that inherits the form, properties, and functions of its real-world counterpart, enabling seamless synch…