%0 Conference Paper %1 conf/cvpr/YoshimuraOIO23 %A Yoshimura, Masakazu %A Otsuka, Junji %A Irie, Atsushi %A Ohashi, Takeshi %B CVPR %D 2023 %I IEEE %K dblp %P 14007-14017 %T Rawgment: Noise-Accounted RAW Augmentation Enables Recognition in a Wide Variety of Environments. %U http://dblp.uni-trier.de/db/conf/cvpr/cvpr2023.html#YoshimuraOIO23 %@ 979-8-3503-0129-8

@inproceedings{conf/cvpr/YoshimuraOIO23, added-at = {2023-08-29T00:00:00.000+0200}, author = {Yoshimura, Masakazu and Otsuka, Junji and Irie, Atsushi and Ohashi, Takeshi}, biburl = {https://www.bibsonomy.org/bibtex/23a46d50ca119c1bc53b1e13a75ff28b3/dblp}, booktitle = {CVPR}, crossref = {conf/cvpr/2023}, ee = {https://doi.org/10.1109/CVPR52729.2023.01346}, interhash = {5284c78d2a5528990e298e82389b4109}, intrahash = {3a46d50ca119c1bc53b1e13a75ff28b3}, isbn = {979-8-3503-0129-8}, keywords = {dblp}, pages = {14007-14017}, publisher = {IEEE}, timestamp = {2024-04-09T20:51:49.000+0200}, title = {Rawgment: Noise-Accounted RAW Augmentation Enables Recognition in a Wide Variety of Environments.}, url = {http://dblp.uni-trier.de/db/conf/cvpr/cvpr2023.html#YoshimuraOIO23}, year = 2023 }