3 papers
cs.CV2026
A Semantically Disentangled Unified Model for Multi-category 3D Anomaly Detection
SuYeon Kim, Wongyu Lee, MyeongAh Cho
3D anomaly detection targets the detection and localization of defects in 3D point clouds trained solely on normal data. While a unified model improves scalability by learning acro…
cs.CV2026
Object-Centric Representation Learning for Enhanced 3D Semantic Scene Graph Prediction
KunHo Heo, GiHyun Kim, SuYeon Kim +1
3D Semantic Scene Graph Prediction aims to detect objects and their semantic relationships in 3D scenes, and has emerged as a crucial technology for robotics and AR/VR applications…
cs.CV2026
ParTY: Part-Guidance for Expressive Text-to-Motion Synthesis
KunHo Heo, SuYeon Kim, Yonghyun Gwon +2
Text-to-motion synthesis aims to generate natural and expressive human motions from textual descriptions. While existing approaches primarily focus on generating holistic motions f…