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

2019

  • Andreas Rössler, Davide Cozzolino, Luisa Verdoliva, Christian Riess, Justus Thies, Matthias Nießner: FaceForensics++: Learning to Detect Manipulated Facial Images. 2019 more…
  • Angela Dai, Christian Diller, Matthias Nießner: SG-NN: Sparse Generative Neural Networks for Self-Supervised Scene Completion of RGB-D Scans. 2019 more…
  • Armen Avetisyan, Angela Dai, Matthias Nießner: End-to-End CAD Model Retrieval and 9DoF Alignment in 3D Scans. 2019 more…
  • Chiyu "Max" Jiang, Dana Lynn Ona Lansigan, Philip Marcus, Matthias Nießner: DDSL: Deep Differentiable Simplex Layer for Learning Geometric Signals. 2019 more…
  • Chiyu "Max" Jiang, Dequan Wang, Jingwei Huang, Philip Marcus, Matthias Nießner: Convolutional Neural Networks on non-uniform geometrical signals using Euclidean spectral transformation. 2019 more…
  • Chiyu "Max" Jiang, Jingwei Huang, Karthik Kashinath, Prabhat, Philip Marcus, Matthias Niessner: Spherical CNNs on Unstructured Grids. 2019 more…
  • Davide Cozzolino, Justus Thies, Andreas Rössler, Matthias Nießner, Luisa Verdoliva: SpoC: Spoofing Camera Fingerprints. 2019 more…
  • Dejan Azinović, Tzu-Mao Li, Anton Kaplanyan, Matthias Nießner: Inverse Path Tracing for Joint Material and Lighting Estimation. 2019 more…
  • Dong, Siyan; Xu, Kai; Zhou, Qiang; Tagliasacchi, Andrea; Xin, Shiqing; Nießner, Matthias; Chen, Baoquan: Multi-robot collaborative dense scene reconstruction. ACM Transactions on Graphics 38 (4), 2019, 1-16 more…
  • Ji Hou, Angela Dai, Matthias Nießner: 3D-SIC: 3D Semantic Instance Completion for RGB-D Scans. 2019 more…
  • Johanna Wald, Armen Avetisyan, Nassir Navab, Federico Tombari, Matthias Nießner: RIO: 3D Object Instance Re-Localization in Changing Indoor Environments. 2019 more…
  • Justus Thies, Michael Zollhöfer, Matthias Nießner: Deferred Neural Rendering: Image Synthesis using Neural Textures. 2019 more…
  • Manuel Dahnert, Angela Dai, Leonidas Guibas, Matthias Nießner: Joint Embedding of 3D Scan and CAD Objects. 2019 more…
  • Yawar Siddiqui, Julien Valentin, Matthias Nießner: ViewAL: Active Learning with Viewpoint Entropy for Semantic Segmentation. 2019 more…

2018

  • Angela Dai, Matthias Nießner: Scan2Mesh: From Unstructured Range Scans to 3D Meshes. 2018 more…
  • Armen Avetisyan, Manuel Dahnert, Angela Dai, Manolis Savva, Angel X. Chang, Matthias Nießner: Scan2CAD: Learning CAD Model Alignment in RGB-D Scans. 2018 more…
  • Dai, Angela; Nießner, Matthias: 3DMV: Joint 3D-Multi-view Prediction for 3D Semantic Scene Segmentation. In: Computer Vision – ECCV 2018. Springer International Publishing, 2018 more…
  • 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 more…
  • Fang, Xianzhong; Bao, Hujun; Tong, Yiying; Desbrun, Mathieu; Huang, Jin: Quadrangulation through morse-parameterization hybridization. ACM Transactions on Graphics 37 (4), 2018, 1-15 more…
  • 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 more…
  • Hepp, Benjamin; Nießner, Matthias; Hilliges, Otmar: Plan3D. ACM Transactions on Graphics 38 (1), 2018, 1-17 more…
  • 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 more…
  • Ji Hou, Angela Dai, Matthias Nießner: 3D-SIS: 3D Semantic Instance Segmentation of RGB-D Scans. 2018 more…
  • Jingwei Huang, Haotian Zhang, Li Yi, Thomas Funkhouser, Matthias Nießner, Leonidas Guibas: TextureNet: Consistent Local Parametrizations for Learning from High-Resolution Signals on Meshes. 2018 more…
  • Kaichun Mo, Shilin Zhu, Angel X. Chang, Li Yi, Subarna Tripathi, Leonidas J. Guibas, Hao Su: PartNet: A Large-scale Benchmark for Fine-grained and Hierarchical Part-level 3D Object Understanding. 2018 more…
  • Kaichun Mo, Shilin Zhu, Angel X. Chang, Li Yi, Subarna Tripathi, Leonidas J. Guibas, Hao Su: PartNet: A Large-scale Benchmark for Fine-grained and Hierarchical Part-level 3D Object Understanding. 2018 more…
  • 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 more…
  • 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 more…
  • Thies, Justus; Zollhöfer, Michael; Stamminger, Marc; Theobalt, Christian; Nießner, Matthias: FaceVR. ACM Transactions on Graphics 37 (2), 2018, 1-15 more…
  • Thies, Justus; Zollhöfer, Michael; Stamminger, Marc; Theobalt, Christian; Nießner, Matthias: Face2Face. Communications of the ACM 62 (1), 2018, 96-104 more…
  • Thies, Justus; Zollhöfer, Michael; Theobalt, Christian; Stamminger, Marc; Niessner, Matthias: Headon. ACM Transactions on Graphics 37 (4), 2018, 1-13 more…
  • Vincent Sitzmann, Justus Thies, Felix Heide, Matthias Nießner, Gordon Wetzstein, Michael Zollhöfer: DeepVoxels: Learning Persistent 3D Feature Embeddings. 2018 more…
  • 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 more…
  • 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 more…