Journal
2020 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR)
Volume -, Issue -, Pages 2765-2773Publisher
IEEE
DOI: 10.1109/CVPR42600.2020.00284
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Funding
- National Research Foundation of Korea (NRF) - Korea government (MSIT) [2019R1C1C1009283, NRF-2018R1A2B3008640]
- Next-Generation Information Computing Development Program through the NRF - MSIT, ICT [NRF-2017M3C4A7069369]
- Institute of Information & communications Technology Planning & Evaluation (IITP) - Korea government (MSIT) [2019-0-01842, 2019-0-01351]
- National Research Foundation of Korea [2019R1C1C1009283] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
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An event camera detects per-pixel intensity difference and produces asynchronous event stream with low latency, high dynamic range, and low power consumption. As a trade-off the event camera has low spatial resolution. We propose an end-to-end network to reconstruct high resolution, high dynamic range (HDR) images directly from the event stream. We evaluate our algorithm on both simulated and real-world sequences and verify that it captures fine details of a scene and outperforms the combination of the state-of-the-art event to image algorithms with the state-of-the-art super resolution schemes in many quantitative measures by large margins. We further extend our method by using the active sensor pixel (APS) frames or reconstructing images iteratively.
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