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PyNet-V2 Mobile: Efficient On-Device Photo Processing With Neural Networks., , , , , , , , , and 1 other author(s). ICPR, page 677-684. IEEE, (2022)LAN: Lightweight Attention-based Network for RAW-to-RGB Smartphone Image Processing., , and . CVPR Workshops, page 807-815. IEEE, (2022)Fast and Accurate Single-Image Depth Estimation on Mobile Devices, Mobile AI 2021 Challenge: Report., , , , and . CVPR Workshops, page 2545-2557. Computer Vision Foundation / IEEE, (2021)Learned Smartphone ISP on Mobile NPUs With Deep Learning, Mobile AI 2021 Challenge: Report., , , , and . CVPR Workshops, page 2503-2514. Computer Vision Foundation / IEEE, (2021)Real-Time Video Super-Resolution on Smartphones With Deep Learning, Mobile AI 2021 Challenge: Report., , , and . CVPR Workshops, page 2535-2544. Computer Vision Foundation / IEEE, (2021)Fast and Accurate Quantized Camera Scene Detection on Smartphones, Mobile AI 2021 Challenge: Report., , , , , , , , , and 21 other author(s). CoRR, (2021)AIM 2020 Challenge on Learned Image Signal Processing Pipeline., , , , , , , , , and 29 other author(s). CoRR, (2020)MicroISP: Processing 32MP Photos on Mobile Devices with Deep Learning., , , , , , , , , and 1 other author(s). ECCV Workshops (2), volume 13802 of Lecture Notes in Computer Science, page 729-746. Springer, (2022)Power Efficient Video Super-Resolution on Mobile NPUs with Deep Learning, Mobile AI & AIM 2022 Challenge: Report., , , , , , , , , and 43 other author(s). ECCV Workshops (3), volume 13803 of Lecture Notes in Computer Science, page 130-152. Springer, (2022)AI Benchmark: All About Deep Learning on Smartphones in 2019., , , , , , , , and . ICCV Workshops, page 3617-3635. IEEE, (2019)