Jinghe Yang — accepted AI-conference papers

2025

Knowledge Distillation for Underwater Feature Extraction and Matching via GAN-Synthesized Images

RA-L 2025

Autonomous Underwater Vehicles (AUVs) play a crucial role in underwater exploration. Vision-based methods offer cost-effective solutions for localization and mapping in the absence of conventional sensors like GPS and LiDAR. However, underwater environments present significant challenges for feature

Cited by 2 Source ↗Scholar ↗

2023

Knowledge Distillation for Feature Extraction in Underwater VSLAM

Jinghe Yang, Mingming Gong, Girish Nair, Jung Hoon Lee, Jason Monty, Ye Pu

ICRA 2023poster

In recent years, learning-based feature detection and matching have outperformed manually-designed methods in in-air cases. However, it is challenging to learn the features in the underwater scenario due to the absence of annotated underwater datasets. This paper proposes a cross-modal knowl-edge di…

Cited by 9 Source ↗code ↗Scholar ↗