1 code implementation • 9 Feb 2023 • Dichao Liu, Toshihiko Yamasaki, Yu Wang, Kenji Mase, Jien Kato
Experimental results on the Statefarm Distracted Driver Detection Dataset and AUC Distracted Driver Dataset show that the proposed approach is highly effective for recognizing distracted driving behaviors from photos: (1) the teacher network's accuracy surpasses the previous best accuracy; (2) the student network achieves very high accuracy with only 0. 42M parameters (around 55% of the previous most lightweight model).
1 code implementation • BMVC 2020 • Dichao Liu, Yu Wang, Jien Kato, Kenji Mase
The evaluation information is backpropagated and forces the classification stream to improve its awareness of visual attention, which helps classification.
Ranked #25 on Fine-Grained Image Classification on Stanford Cars