Master-Seminar – Machine Learning in Graphics

LecturerN. ThuereyR. WestermannM. NiessnerKiwon Um
StudiesMaster Informatics
Time, PlaceMondays 16:00-18:00, Seminarraum MI 02.13.010


In this course, students will autonomously investigate recent research about machine learning techniques in the computer graphics area. Independent investigation for further reading, critical analysis, and evaluation of the topic are required.


  • The participants have to present their topics in a talk (in English), which should last 30 minutes.
  • The semi-final slides (PDF) should be sent one week before the talk; otherwise, the talk will be canceled.
  • A short report (approximately 3-4 pages in the ACM SIGGRAPH TOG format (acmtog)) should be prepared and sent within two weeks after the talk. When you send the report, please send the final slides (PDF) together.

Preliminary Schedule

24.03.2017Deadline for sending an e-mail with 3 preferences
31.03.2017Notification of assigned paper


24 Apr 2017Michael2016, Dong et al., Image Super-Resolution Using Deep Convolutional Networks, IEEE Transactions on Pattern Analysis and Machine Intelligence
24 Apr 2017Thomas2017, Dahl et al., Pixel Recursive Super Resolution,
01 May 2017No talkMay Day (Maifeiertag)
08 May 2017Elisabeth2016, Yan et al., Automatic Photo Adjustment Using Deep Neural Networks, ACM Trans. Graph.
08 May 2017Jonas2015, Gryka et al., Learning to Remove Soft Shadows, ACM Trans. Graph.
15 May 2017Julius2014, Goodfellow et al., Generative Adversarial Networks, Advances in Neural Information Processing Systems 27 (NIPS 2014)
15 May 2017Simon2016, Ruder et al., Artistic Style Transfer for Videos,
(optional) 2015, Gatys et al., A Neural Algorithm of Artistic Style,
22 May 2017Anna2015, Kalantari et al., A Machine Learning Approach for Filtering Monte Carlo Noise, ACM Trans. Graph.
22 May 2017Hans Theobald2016, Ren et al., Image Based Relighting Using Neural Networks, ACM Trans. Graph.
29 May 2017Oliver Jamal2017, Zheng and Zheng, NeuroLens: Data-Driven Camera Lens Simulation Using Neural Networks, Computer Graphics Forum
29 May 2017Moritz2015, Ladický et al., Data-driven Fluid Simulations Using Regression Forests, ACM Trans. Graph.
05 Jun 2017No talkWhit Monday (Pfingstmontag)
12 Jun 2017Eric2017, Kim et al., Category-Specific Salient View Selection via Deep Convolutional Neural Networks, Computer Graphics Forum
12 Jun 2017Lukas2015, Mnih et al., Human-Level Control Through Deep Reinforcement Learning, Nature
19 Jun 2017Sebastian2015, Guo et al., 3D Mesh Labeling via Deep Convolutional Neural Networks, ACM Trans. Graph.
19 Jun 2017Benedikt2016, Simo-Serra et al., Learning to Simplify: Fully Convolutional Networks for Rough Sketch Cleanup, ACM Trans. Graph.
26 Jun 2017Gerhard‑Mathias2016, Nishida et al., Interactive Sketching of Urban Procedural Models, ACM Trans. Graph.
26 Jun 2017Florian2016, Zeng et al., 3DMatch: Learning Local Geometric Descriptors from RGB-D Reconstructions,
03 Jul 2017Niklas2016, Peng et al., Terrain-adaptive Locomotion Skills Using Deep Reinforcement Learning, ACM Trans. Graph.
03 Jul 2017Jan2016, Holden et al., A Deep Learning Framework for Character Motion Synthesis and Editing, ACM Trans. Graph.