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"Rawgment: Noise-Accounted RAW Augmentation Enables Recognition in a Wide ..."

Masakazu Yoshimura et al. (2023)

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DOI: 10.1109/CVPR52729.2023.01346

access: closed

type: Conference or Workshop Paper

metadata version: 2023-08-29

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  - conf/cvpr/YoshimuraOIO23
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Masakazu Yoshimura, Junji Otsuka, Atsushi Irie, Takeshi Ohashi:
Rawgment: Noise-Accounted RAW Augmentation Enables Recognition in a Wide Variety of Environments. CVPR 2023: 14007-14017

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