We in the Visual Computing Focus Group are research enthusiasts pushing the state of the art at the intersection of computer vision, 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. full report
Short CV
Professor Nießner (b. 1986) studied computer science at the Friedrich-Alexander-Universität Erlangen-Nürnberg and received his Diploma degree in 2010. He then began his doctoral research under the supervision of Professor Günther Greiner. His thesis on the topic of “Subdivision Surface Rendering using Hardware Tessellation” was submitted in 2013 and was awarded the highest honors. From 2013 to 2017 Professor Nießner was a visiting assistant professor at Stanford University. Since 2017 he has been a professor at TUM, where he heads the Visual Computing Lab.
Selected Awards
2018, ERC Starting Grant
2016, SIGGRAPH’16: Best Emerging Technologies Award for the Face2Face Live Demo
2013, MPC-VCC Fellowship: Research group funding, including 2 PhDs, over 2 years
2010, ASQF advancement award for excellent graduation, Diploma thesis
Research Interest
Prof. Nießner‘s research focuses on the area of 3D digitization at the intersection between Computer Graphics, Computer Vision, and Artificial Intelligence. The main theme of this research is to obtain 3D models of real-world environments captured by video and range cameras. In this context, the main focus lies on the representation of the obtained 3D geometry, as well as the processing and its analysis by leveraging cutting-edge machine learning techniques (e.g., Deep Learning). In addition to the analysis of semantic understanding of 3D environments, which is a key element of modern robotics, the research in the Visual Computing Lab touches many fascinating applications, including the editing of videos, numerical optimization, and many more.
Selected Publications
Dai A, Chang A, Savva M, Halber M, Funkhouser T, Nießner M: "ScanNet: Richly-annotated 3D Reconstructions of Indoor Scenes". CVPR. Honolulu, HI, USA. 22.-25.07.2017.
Thies J, Zollhöfer M, Stamminger M, Theobalt C, Nießner M: "Face2Face: Real-time Face Capture and Reenctment of RGB Videos". CVPR. Las Vegas, NV, USA. 27.-30.06.2016: 2387-2395.
Zollhöfer M, Nießner M, Izadi S, Rhemann C, Zach C, Fisher M, Wu C, Fitzgibbon A, Loop C, Theobalt C, Stamminger M: "Real-time Non-rigid Reconstruction using an RGB-D Camera". ACM Transactions on Graphics. 2014; 33(4): 156-168.
Nießner M, Zollhöfer M, Izadi S, Stamminger M: "Voxel Hashing". ACM Transactions on Graphics. 2013; 32(6): 169-180.
Nießner M, Loop C, Meyer M, DeRose T: "Feature Adaptive GPU Rendering of Catmull-Clark Subdivision Surfaces". ACM Transactions on Graphics. 2012; 31(1): 6-17.
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…
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…
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…
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…