Fakultät Informatik

Master-Seminar – Machine Learning in Graphics

Lecturer

 Prof. Dr. Nils Thuerey and  Prof. Dr. Rüdiger Westermann

Studies

Master Informatics

Time, Place

Mondays 16:00-18:00, Seminarraum MI   02.13.010

Begin

24 Oct 2016

Content

In this course, students will autonomously investigate recent research about machine learning techniques in the computer graphics area. Independent investigation for further reading, as well as a critical analysis and evaluation of the topic are required. Finally, the attendants have to present their results in a talk which should last 40-50 minutes. Talks will be given in English. Supplementary, a short written workout (approximately 4-6 pages) should be prepared.

Preliminary Schedule

30.06.2016

Kick-off meeting in room MI 02.13.010 at 16:15

16.09.2016

Deadline for sending an e-mail with 3 preferences

30.09.2016

Notification of assigned paper

Papers

Date

Presenter

Paper

24.10.2016

Jing Yi Wang

2016, Dong et al.,  Image Super-Resolution Using Deep Convolutional Networks, IEEE Transactions on Pattern Analysis and Machine Intelligence

31.10.2016

Benedikt Schlagberger

2016, Yan et al.,  Automatic Photo Adjustment Using Deep Neural Networks, ACM Trans. Graph.

07.11.2016

Steen Müller

2014, Goodfellow et al.,  Generative Adversarial Networks, Advances in Neural Information Processing Systems 27 (NIPS 2014)

14.11.2016

Sebastian Weiß

2016, Ruder et al.,  Artistic Style Transfer for Videos, arXiv.org
(optional) 2015, Gatys et al.,  A Neural Algorithm of Artistic Style, arXiv.org

21.11.2016

Alexander Thole

2016, Ren et al.,  Image Based Relighting Using Neural Networks, ACM Trans. Graph.

28.11.2016

Stefan Kreisig

2015, Kalantari et al.,  A Machine Learning Approach for Filtering Monte Carlo Noise, ACM Trans. Graph.

05.12.2016

Andreas Reiser

2015, Ladický et al.,  Data-driven Fluid Simulations Using Regression Forests, ACM Trans. Graph.

12.12.2016

Jan Fahlbusch

2015, Mnih et al.,  Human-Level Control Through Deep Reinforcement Learning, Nature

19.12.2016

Anastasia Pomelova

2015, Guo et al.,  3D Mesh Labeling via Deep Convolutional Neural Networks, ACM Trans. Graph.

26.12.2016

No talk (Weihnachtsferien)

02.01.2017

No talk (Weihnachtsferien)

09.01.2017

Valentin Beck

2016, Nishida et al.,  Interactive Sketching of Urban Procedural Models, ACM Trans. Graph.

16.01.2017

Daniel Schubert

2016, Peng et al.,  Terrain-adaptive Locomotion Skills Using Deep Reinforcement Learning, ACM Trans. Graph.

23.01.2017

Steffen Wiewel

2016, Holden et al.,  A Deep Learning Framework for Character Motion Synthesis and Editing, ACM Trans. Graph.

References

 

News

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