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Ruiyuan Li

2 accepted papers

2025

NCNet: Learning to Find Non-Consistent Correspondence Using Learnable Frequency Response Function

ICASSP 2025accepted

False correspondence removal is a persistent challenge in image feature-matching-based applications, especially in complex scenes. Traditional methods often rely on the consistency assumption to model the motion of correct correspondences, which neglects non-consistent correct correspondences, resul…

Cited by 0SourceScholar
2022

MDOE: A Spatiotemporal Event Representation Considering the Magnitude and Density of Events

RA-L 2022

Event-based sensors (e.g., DVS cameras) are capable of higher dynamic range, higher temporal resolution, lower time latency, and better power efficiency compared to conventional devices (e.g., RGB cameras). However, learning from these sensors remains challenging; event-based sensors output a stream

Cited by 4SourceScholar