arXiv AI
Oct 21

GALA: Geometry-Aware Language Model for Controllable Object Arrangement

arXiv:2610.28280v1 Announce Type: cross Abstract: Reasoning about fine-grained placement constraints, such as support and containment, is essential for realistic 3D scene creation. It remains a signi...

By Chucheng Xiang, Runze Wang, Zhi Deng, Ruchao Bao, Yuanwei Zhang, Yuxuan Xie, Hanliu Wang, Liangzhen Fei, Wenzheng Wu, Cheng Wan, Peifeng Li, Zhongyuan Liu, Ligang Liu
arXiv Computer Vision
Oct 5

RYOPO: Bringing End-to-End Category-Level Object Pose Estimation into Real Time

RYOPO is an end‑to‑end query‑based RGB‑D set predictor that jointly detects, segments, and estimates 9‑DoF poses of unseen instances within known categories without relying on external instance segmentation or CAD priors. It uses shared image and scene encoding, a query‑conditioned geometry pathway, and object‑centric refinement with pose‑conditioned cross‑attention to achieve accurate pose estimation. On benchmark datasets such as NOCS, REAL275, and HouseCat6D, RYOPO outperforms published methods and runs in real time at 31.8 FPS on an RTX A6000.

By Hakjin Lee, Junghoon Seo, Jaehoon Sim