April 26, 2024, 4:46 a.m. | Caixin Wang, Jie Zhang, Matthew A. Wilson, Ralph Etienne-Cummings

cs.CV updates on arXiv.org arxiv.org

arXiv:2310.16139v2 Announce Type: replace-cross
Abstract: Accurately capturing dynamic scenes with wide-ranging motion and light intensity is crucial for many vision applications. However, acquiring high-speed high dynamic range (HDR) video is challenging because the camera's frame rate restricts its dynamic range. Existing methods sacrifice speed to acquire multi-exposure frames. Yet, misaligned motion in these frames can still pose complications for HDR fusion algorithms, resulting in artifacts. Instead of frame-based exposures, we sample the videos using individual pixels at varying exposures and …

abstract acquisition applications arxiv cs.cv deep learning dynamic eess.iv however intensity light pixel rate speed synthesis type video videos vision wise

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