To explore the joint task, we first establish real-world datasets for event-guided low-light enhancement and deblurring using a hybrid cam-era system based on beam splitters. Subsequently, we introduce an end-to-end framework to efectively handle these tasks. While event cameras offer potential solutions with superior low-light sensitivity and high temporal resolution, existing fusion methods typically employ staged strategies, limiting their effectiveness against combined low-light and motion blur degradations. They provide two key advantages: capturing scene details well even in low light due to their high dynamic range, and efectively capturing motion information during. The Low Light Image Enhancement (LLIE) task has been a hotspot in low-level computer vision research. e 10 different conditions) with 12 object classes (similar to PASCAL VOC) annotated on both image class level and local object bounding boxes. A small amount of unpaired images for testing.
[PDF Version]