Visual Computing

Headed by Rudolf Mößbauer Tenure Track Professor Matthias Nießner, the Visual Computing Lab at TUM is a group of research enthusiasts pushing the state of the art at the intersection of computer vision, computer graphics, and machine learning. Our research mission is to obtain high-quality digital models of the real world, which include detailed geometry, surface texture, and material in both static and dynamic environments. In our research, we heavily exploit the capabilities of RGB-D and range sensing devices that are now widely available. However, we ultimately aim to achieve both 3D and 4D recordings from monocular sensors - essentially, we want to record holograms with a simple webcam or mobile phone. We further employ our reconstructed models for specific use cases, such as video editing, immersive AR/VR, semantic scene understanding, and many others. Aside from traditional convex and non-convex optimization techniques, we see great potential in modern artificial intelligence, mainly deep learning, in order to achieve these goals.

For a very successful example of the work of the Visual Computing group, see their project Face2Face – Real-time Face Capture and Reenactment of RGB Videos.

Since 2018, Hans Fischer Senior Fellow Prof. Leonidas Guibas (Stanford University) and Hans Fischer Fellow Dr. Angel Xuan Chang (Eloquent Labs, Simon Fraser University) have joined the Focus Group.

TUM-IAS funded doctoral candidates:
Armen Avetisyan, Visual Computing, TUM
Ji Hou, Visual Computing, TUM
Andreas Rössler, Visual Computing, TUM

Publications by the Focus Group

2018

  • Dai, Angela; Nießner, Matthias: 3DMV: Joint 3D-Multi-view Prediction for 3D Semantic Scene Segmentation. In: Computer Vision – ECCV 2018. Springer International Publishing, 2018 mehr…
  • Dai, Angela; Ritchie, Daniel; Bokeloh, Martin; Reed, Scott; Sturm, Jurgen; Niessner, Matthias: ScanComplete: Large-Scale Scene Completion and Semantic Segmentation for 3D Scans. 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, IEEE, 2018 mehr…
  • Fang, Xianzhong; Bao, Hujun; Tong, Yiying; Desbrun, Mathieu; Huang, Jin: Quadrangulation through morse-parameterization hybridization. ACM Transactions on Graphics 37 (4), 2018, 1-15 mehr…
  • Ganapathi-Subramanian, Vignesh; Diamanti, Olga; Pirk, Soeren; Tang, Chengcheng; Niessner, Matthias; Guibas, Leonidas: Parsing Geometry Using Structure-Aware Shape Templates. 2018 International Conference on 3D Vision (3DV), IEEE, 2018 mehr…
  • Hepp, Benjamin; Nießner, Matthias; Hilliges, Otmar: Plan3D. ACM Transactions on Graphics 38 (1), 2018, 1-17 mehr…
  • Jan Svoboda, Jonathan Masci, Federico Monti, Michael M. Bronstein, Leonidas Guibas: PeerNets: Exploiting Peer Wisdom Against Adversarial Attacks. Proceedings of the International Conference on Learning Representations, 2018 mehr…
  • Kim, Hyeongwoo; Theobalt, Christian; Carrido, Pablo; Tewari, Ayush; Xu, Weipeng; Thies, Justus; Niessner, Matthias; Pérez, Patrick; Richardt, Christian; Zollhöfer, Michael: Deep video portraits. ACM Transactions on Graphics 37 (4), 2018, 1-14 mehr…
  • Shi, Yifei; Xu, Kai; Nießner, Matthias; Rusinkiewicz, Szymon; Funkhouser, Thomas: PlaneMatch: Patch Coplanarity Prediction for Robust RGB-D Reconstruction. In: Computer Vision – ECCV 2018. Springer International Publishing, 2018 mehr…
  • Thies, Justus; Zollhöfer, Michael; Stamminger, Marc; Theobalt, Christian; Nießner, Matthias: FaceVR. ACM Transactions on Graphics 37 (2), 2018, 1-15 mehr…
  • Thies, Justus; Zollhöfer, Michael; Theobalt, Christian; Stamminger, Marc; Niessner, Matthias: Headon. ACM Transactions on Graphics 37 (4), 2018, 1-13 mehr…
  • Zollhöfer, M.; Thies, J.; Garrido, P.; Bradley, D.; Beeler, T.; Pérez, P.; Stamminger, M.; Nießner, M.; Theobalt, C.: State of the Art on Monocular 3D Face Reconstruction, Tracking, and Applications. Computer Graphics Forum 37 (2), 2018, 523-550 mehr…
  • Zollhöfer, Michael; Stotko, Patrick; Görlitz, Andreas; Theobalt, Christian; Nießner, Matthias; Klein, Reinhard; Kolb, Andreas: State of the Art on 3D Reconstruction with RGB-D Cameras. Computer Graphics Forum 37 (2), 2018, 625-652 mehr…