EIC-LIE uses an event-illumination collaborative module and illumination-aware event filter plus a new real-world dataset to improve low-light image enhancement over prior methods.
Lightweight adaptive feature de-drifting for compressed im- age classification.IEEE Transactions on Multimedia, 26: 6424–6436
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Tracker is a self-supervised VL tracker that uses a Dynamic Token Aggregation Module to learn instance tracking from single language descriptions in unlabeled videos and outperforms prior self-supervised methods.
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Event-Illumination Collaborative Low-light Image Enhancement with a High-resolution Real-world Dataset
EIC-LIE uses an event-illumination collaborative module and illumination-aware event filter plus a new real-world dataset to improve low-light image enhancement over prior methods.
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Learning to Track Instance from Single Nature Language Description
Tracker is a self-supervised VL tracker that uses a Dynamic Token Aggregation Module to learn instance tracking from single language descriptions in unlabeled videos and outperforms prior self-supervised methods.