Publications

Wolski, K., Giunchi, D. and Kinuwaki, S. et al. 2019. Selecting texture resolution using a task‐specific visibility metric. Computer Graphics Forum 38, 7, 685-696.
DOI: 10.1111/cgf.13871
Project Page
Ak, A., and Callet, P. 2019. Towards Perceptually Plausible Training of Image Restoration Neural Networks. International Conference on Image Processing Theory, Tools and Applications.
DOI: 10.1109/IPTA.2019.8936096
Open Access
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
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
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
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
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
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

Updated by Jingyu Liu on 3 January 2020

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Publications