M.Sc. Oliver Wiedemann

Status and Interests

I'm a Ph.D. student working on adaptive image and video compression algorithms and concepts of perceptual quality. Methods used in my research work range from machine learning and computer vision to eye-tracking and crowdsourcing.

I was awarded a Fellowship by the SFB-TRR 161 on Quantitative Methods for Visual Computing  in 2019, to which I'm still closely associated.

For more information about my work, projects and publications please visit my personal website, my profile on Google Scholar, or send me an email.

Short Vita

Publications

Conference Papers

  • O. Wiedemann, V. Hosu, H. Lin and D. Saupe, "Foveated Video Coding for Real Time Streaming Applications", 12th International Conference on Quality of Multimedia Experience (QoMEX), IEEE, 2020. PDF
  • O. Wiedemann, V. Hosu, H. Lin and D. Saupe, "Disregarding the Big Picture: Towards Local Image Quality Assessment", 10th International Conference on Quality of Multimedia Experience (QoMEX), IEEE, 2018. PDF
  • V. Hosu, F. Hahn, O. Wiedemann, S. Jung and D. Saupe, "Saliency-Driven Image Coding Improves Overall Perceived JPEG Quality", Picture Coding Symposium (PCS), IEEE, 2016. PDF

Workshop Papers and Posters

  •  O. Wiedemann and D. Saupe, "Gaze Data for Quality Assessment of Foveated Video", Workshop on Eye Tracking for Quality of Experience in Multimedia (ET-MM) at ACM ETRA, Stuttgart, 2020
  •  O. Wiedemann, V. Hosu, F. Götz-Hahn and D. Saupe, "Predicted Local Quality as a Resource Allocation Scheme in Variable Image Compression", 1st International Conference on Quantification in Visual Computing, SFB-TRR 161 conference at GCPR/VMV, Stuttgart, 2018.

Talks and Presentations

  • "Foveated Video Coding for Real Time Streaming Applications", 5th  Summer School on Video Compression and Processing (SVCP), Konstanz, 2019.

Teaching

  • SS 2018: Tutorial: Deep Learning Programming
  • WS 2015/16: Tutorial: Systems Programming (PK3)