Qingyuan Wang — accepted AI-conference papers

2026

Aligning Cross-View Visual Geometries in LVLMs Through Human-Like Reasoning Learning

Yuming Qiao, Liang Luo, Dan Meng, Yifan Yang, Qingyuan Wang, Juntuo Wang +5

AAAI 2026technical

Spatial understanding is a critical capability for LVLMs (Large Vision-Language Models) to advance embodied AI applications. Existing works primarily focus on enhancing spatial understanding within a single frame, i.e., injecting 3D spatial concepts into LVLMs under single coordinate system. However

Cited by 0 Source ↗PDF ↗Scholar ↗

2025

SCFlow2: Plug-and-Play Object Pose Refiner with Shape-Constraint Scene Flow

Qingyuan Wang, Rui Song, Jiaojiao Li, Kerui Cheng, David Ferstl, Yinlin Hu

CVPR 2025poster

We introduce SCFlow2, a plug-and-play refinement framework for 6D object pose estimation. Most recent 6D object pose methods rely on refinement to get accurate results. However, most existing refinements either suffer from noises in establishing correspondences, or rely on retraining for novel objec…

Cited by 0 Source ↗PDF ↗Scholar ↗