Qingyu Fan — accepted AI-conference papers

2025

MISCGrasp: Leveraging Multiple Integrated Scales and Contrastive Learning for Enhanced Volumetric Grasping

Qingyu Fan, Yinghao Cai, Chao Li, Chunting Jiao, Xudong Zheng, Tao Lu +2

IROS 2025

Robotic grasping faces challenges in adapting to objects with varying shapes and sizes. In this paper, we introduce MISCGrasp, a volumetric grasping method that integrates multi-scale feature extraction with contrastive feature enhancement for self-adaptive grasping. We propose a query-based interac

Cited by 2 Source ↗code ↗Scholar ↗

2025

NeuGrasp: Generalizable Neural Surface Reconstruction with Background Priors for Material-Agnostic Object Grasp Detection

Qingyu Fan, Yinghao Cai, Chao Li, Wenzhe He, Xudong Zheng, Tao Lu +2

ICRA 2025

Robotic grasping in scenes with transparent and specular objects presents great challenges for methods relying on accurate depth information. In this paper, we introduce NeuGrasp, a neural surface reconstruction method that leverages background priors for material-agnostic grasp detection. NeuGrasp

Cited by 3 Source ↗code ↗Scholar ↗