Paying more attention to attention: improving the performance of convolutional neural networks via attention transfer

Conference object, Preprint English OPEN
Komodakis , Nikos; Zagoruyko , Sergey;
(2017)
  • Publisher: HAL CCSD
  • Subject: Computer Science - Computer Vision and Pattern Recognition | [ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]

International audience; Attention plays a critical role in human visual experience. Furthermore, it has recently been demonstrated that attention can also play an important role in the context of applying artificial neural networks to a variety of tasks from fields such... View more
  • References (19)
    19 references, page 1 of 2

    Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. Neural machine translation by jointly learning to align and translate. CoRR, abs/1409.0473, 2014. URL http://arxiv.org/ abs/1409.0473.

    Cristian Bucila, Rich Caruana, and Alexandru Niculescu-Mizil. Model compression. In KDD, pp. 535-541, 2006.

    Taco S. Cohen and Max Welling. Group equivariant convolutional networks. abs/1602.07576, 2016. URL http://arxiv.org/abs/1602.07576.

    Volodymyr Mnih, Nicolas Heess, Alex Graves, and koray kavukcuoglu. Recurrent models of visual attention. In Z. Ghahramani, M. Welling, C. Cortes, N. D. Lawrence, and K. Q. Weinberger (eds.), Advances in Neural Information Processing Systems 27, pp. 2204-2212. Curran Associates, Inc., 2014. URL http://papers.nips.cc/paper/ 5542-recurrent-models-of-visual-attention.pdf.

    M. Oquab, L. Bottou, I. Laptev, and J. Sivic. Is object localization for free? weakly-supervised learning with convolutional neural networks. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015.

    O. M. Parkhi, A. Vedaldi, and A. Zisserman. Deep face recognition. In British Machine Vision Conference, 2015.

    A. Quattoni and A. Torralba. Recognizing indoor scenes. In CVPR, 2009.

    Ronald A. Rensink. The dynamic representation of scenes. In Visual Cognition, pp. 17-42, 2000.

    Adriana Romero, Nicolas Ballas, Samira Ebrahimi Kahou, Antoine Chassang, Carlo Gatta, and Yoshua Bengio. FitNets: Hints for thin deep nets. Technical Report Arxiv report 1412.6550, arXiv, 2014.

    Ramprasaath R. Selvaraju, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, and Dhruv Batra. Grad-cam: Why did you say that? visual explanations from deep networks via gradient-based localization. 2016.

  • Related Organizations (3)
  • Metrics
Share - Bookmark