Publications

  1. Ak, A., and Callet, P. 2019. Towards Perceptually Plausible Training of Image Restoration Neural Networks. International Conference on Image Processing Theory, Tools and Applications.
    Open Access
  2. Ak, A., and Callet, P. 2019. Investigating Epipolar Plane Image Representations for Objective Quality Evaluation of Light Field Images. European Workshop on Visual Information Processing.
    Best Student Paper
    Open Access
  3. Gul, M. S. K., Bätz, M., and Keinert, J. 2019. Pixel-Wise Confidences for Stereo Disparities Using Recurrent Neural Networks. British Machine Vision Conference.
    Open Access
  4. Agrawal, S., Simon, A., Bech, S., Bærentsen, K., and Forchhammer, S. 2019. Defining Immersion: Literature Review and Implications for Research on Immersive Audiovisual Experiences. Audio Engineering Society Convention 147, 10275.
    Open Access
  5. Zhong, F., Koulieris, G. and Drettakis, G. et al. 2019. DiCE: Dichoptic Contrast Enhancement for VR and Stereo Displays. ACM Transactions on Graphics 38, 6, Article 211.
    DOI: 10.1145/3355089.3356552
    Open Access
    Project Page
  6. Ye, N., Wolski, K. and Mantiuk, R. 2019. Predicting Visible Image Differences Under Varying Display Brightness and Viewing Distance. The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 5434-5442.
    Open Access
    Project Page
  7. Wolski, K., Giunchi, D. and Ye, N. et al. 2018. Dataset and Metrics for Predicting Local Visible Differences. ACM Transactions on Graphics 37, 5, 1-14.
    DOI: 10.1145/3196493
    Open Access
    Project Page
http://www.realvision-itn.eu/dissemination
22 NOVEMBER 2019