Corpus ID: 234777870

Fast and Accurate Quantized Camera Scene Detection on Smartphones, Mobile AI 2021 Challenge: Report

@article{Ignatov2021FastAA,
  title={Fast and Accurate Quantized Camera Scene Detection on Smartphones, Mobile AI 2021 Challenge: Report},
  author={Andrey D. Ignatov and Grigory Malivenko and R. Timofte and Sheng Chen and Xin Xia and Zhaoyang Liu and Yuwei Zhang and Feng Zhu and Jiashi Li and XueFeng Xiao and Yuan Tian and Xinglong Wu and C. Kyrkou and Yixin Chen and Zexin Zhang and Yunbo Peng and Yue Lin and S. Dutta and Sourya Dipta Das and Nisarg A. Shah and Himanshu Kumar and Chao Ge and Pei Wu and Jin-Hua Du and Andrew Batutin and Juan Pablo Federico and Konrad Lyda and Levon Khojoyan and Abhishek Thanki and Sayak Paul and Shahid Siddiqui},
  journal={ArXiv},
  year={2021},
  volume={abs/2105.08819}
}
Camera scene detection is among the most popular computer vision problem on smartphones. While many custom solutions were developed for this task by phone vendors, none of the designed models were available publicly up until now. To address this problem, we introduce the first Mobile AI challenge, where the target is to develop quantized deep learning-based camera scene classification solutions that can demonstrate a real-time performance on smartphones and IoT platforms. For this, the… Expand
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