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Hong Nie

2 accepted papers

2025

Domain-Invariant Feature Learning via Margin and Structure Priors for Robotic Grasping

RA-L 2025

Existing grasp detection methods usually rely on data-driven strategies to learn grasping features from labeled data, restricting their generalization to new scenes and objects. Preliminary researches introduce domain-invariant methods which tend to simply consider single visual representations and

Cited by 11SourceScholar
2024

Smaller and Faster Robotic Grasp Detection Model via Knowledge Distillation and Unequal Feature Encoding

RA-L 2024

In order to achieve higher accuracy, the complexity of grasp detection network increases accordingly with complicated model structures and tremendous parameters. Although various light-weight strategies are adopted, directly designing the compact network can be sub-optimal and difficult to strike th

Cited by 12SourceScholar