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arXiv · 2410.19164

HUE Dataset: High-Resolution Event and Frame Sequences for Low-Light Vision

Burak Ercan·Onur Eker·Aykut Erdem·Erkut Erdem
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Abstract

Low-light environments pose significant challenges for image enhancement methods. To address these challenges, in this work, we introduce the HUE dataset, a comprehensive collection of high-resolution event and frame sequences captured in diverse and challenging low-light conditions. Our dataset includes 106 sequences, encompassing indoor, cityscape, twilight, night, driving, and controlled scenarios, each carefully recorded to address various illumination levels and dynamic ranges. Utilizing a hybrid RGB and event camera setup. we collect a dataset that combines high-resolution event data with complementary frame data. We employ both qualitative and quantitative evaluations using no-reference metrics to assess state-of-the-art low-light enhancement and event-based image reconstruction methods. Additionally, we evaluate these methods on a downstream object detection task. Our findings reveal that while event-based methods perform well in specific metrics, they may produce false positives in practical applications. This dataset and our comprehensive analysis provide valuable insights for future research in low-light vision and hybrid camera systems.

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Burak Ercan, Onur Eker, Aykut Erdem, Erkut Erdem. 2024-10-24. HUE Dataset: High-Resolution Event and Frame Sequences for Low-Light Vision. https://arxiv.org/abs/2410.19164

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