Publications
Research in agentic models, controllable video generation, 3D generation, reconstruction, and visual understanding.
2026
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MAI-Thinking-1
Contributed to its agentic coding capabilities, achieving state-of-the-art performance in its weight classCitation
@misc{microsoft2026maithinking1, title = {{MAI-Thinking-1}}, author = {{Microsoft AI}}, year = {2026}, note = {Contributed to its agentic coding capabilities, achieving state-of-the-art performance in its weight class} } -
LuxRemix: Lighting Decomposition and Remixing for Indoor Scenes
Edit individual light sources in a captured scene, consistently across viewpoints.
Citation
@inproceedings{liang2026luxremix, title = {LuxRemix: Lighting Decomposition and Remixing for Indoor Scenes}, author = {Liang, Ruofan and Müller, Norman and Weber, Ethan and Zauss, Duncan and Vijaykumar, Nandita and Kontschieder, Peter and Richardt, Christian}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}, year = {2026}, url = {https://luxremix.github.io/}, } -
MapAnything: Universal Feed-Forward Metric 3D Reconstruction
Recover metric 3D geometry from images and optional camera or depth inputs.
Citation
@inproceedings{keetha2026mapanything, title = {{MapAnything}: Universal Feed-Forward Metric {3D} Reconstruction}, author = {Keetha, Nikhil and M\"{u}ller, Norman and Sch\"{o}nberger, Johannes and Porzi, Lorenzo and Zhang, Yuchen and Fischer, Tobias and Knapitsch, Arno and Zauss, Duncan and Weber, Ethan and Antunes, Nelson and Luiten, Jonathon and Lopez-Antequera, Manuel and Bul\`{o}, Samuel Rota and Richardt, Christian and Ramanan, Deva and Scherer, Sebastian and Kontschieder, Peter}, booktitle = {International Conference on 3D Vision (3DV)}, year = {2026}, organization = {IEEE}, url = {https://arxiv.org/abs/2509.13414}, }
2025
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FlowR: Flowing from Sparse to Dense 3D Reconstructions
Citation
@article{fischer2025flowr, author = {Fischer, Tobias and Bul{\`o}, Samuel Rota and Yang, Yung-Hsu and Keetha, Nikhil Varma and Porzi, Lorenzo and M{\"u}ller, Norman and Schwarz, Katja and Luiten, Jonathon and Pollefeys, Marc and Kontschieder, Peter}, title = {{FlowR}: Flowing from Sparse to Dense 3D Reconstructions}, journal = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) [Highlight]}, year = {2025}, url = {https://arxiv.org/abs/2504.01647}, eprint = {2504.01647} } -
Easy3D: A Simple Yet Effective Method for 3D Interactive Segmentation
Citation
@article{simonelli2025easy3d, title = {Easy3D: A Simple Yet Effective Method for 3D Interactive Segmentation}, author = {Simonelli, Andrea and M{\"u}ller, Norman and Kontschieder, Peter}, journal = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) [Oral]}, year = {2025}, url = {https://arxiv.org/abs/2504.11024}, eprint = {2504.11024} } -
Generative Gaussian splatting: Generating 3D scenes with video diffusion priors
Citation
@article{schwarz2025generative, title = {Generative Gaussian splatting: Generating 3D scenes with video diffusion priors}, author = {Schwarz, Katja and M{\"u}ller, Norman and Kontschieder, Peter}, journal = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)}, year = {2025}, url = {https://arxiv.org/abs/2503.13272}, eprint = {2503.13272} }
2024
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Coherent 3D Scene Diffusion From a Single RGB Image
Citation
@inproceedings{dahnert2024coherent, title = {Coherent 3D Scene Diffusion From a Single {RGB} Image}, author = {Dahnert, Manuel and Dai, Angela and M{\"u}ller, Norman and Nie{\ss}ner, Matthias}, booktitle = {The Thirty-eighth Annual Conference on Neural Information Processing Systems}, year = {2024}, url = {https://openreview.net/forum?id=lckAdnVzsT}, } -
L3DG: Latent 3D Gaussian Diffusion
Citation
@inproceedings{roessle2024l3dg, title = {{L3DG}: Latent {3D} Gaussian Diffusion}, author = {Roessle, Barbara and M{\"u}ller, Norman and Porzi, Lorenzo and Rota Bul{\`o}, Samuel and Kontschieder, Peter and Dai, Angela and Nie{\ss}ner, Matthias}, booktitle = {SIGGRAPH Asia 2024 Conference Papers}, pages = {1--11}, year = {2024} } -
Surf-D: High-Quality Surface Generation for Arbitrary Topologies using Diffusion Models
Citation
@inproceedings{yu2023surf, title = {Surf-D: High-Quality Surface Generation for Arbitrary Topologies using Diffusion Models}, author = {Yu, Zhengming and Dou, Zhiyang and Long, Xiaoxiao and Lin, Cheng and Li, Zekun and Liu, Yuan and Müller, Norman and Komura, Taku and Habermann, Marc and Theobalt, Christian and others}, booktitle = {The European Conference on Computer Vision (ECCV)}, year = {2024}, month = sep, } -
MultiDiff: Consistent Novel View Synthesis from a Single Image
Citation
@inproceedings{muller2024multidiff, title = {MultiDiff: Consistent Novel View Synthesis from a Single Image}, author = {M\"uller, Norman and Schwarz, Katja and R\"ossle, Barbara and Porzi, Lorenzo and Bul\`o, Samuel Rota and Nie{\ss}ner, Matthias and Kontschieder, Peter}, year = {2024}, month = jun, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)} } -
ConsistDreamer: 3D-Consistent 2D Diffusion for High-Fidelity Scene Editing
Citation
@inproceedings{consistdreamer, title = {{ConsistDreamer}: {3D}-Consistent {2D} Diffusion for High-Fidelity Scene Editing}, author = {Chen, Jun-Kun and Rota Bulò, Samuel and Müller, Norman and Porzi, Lorenzo and Kontschieder, Peter and Wang, Yu-Xiong}, booktitle = {CVPR}, year = {2024}, } -
ViewDiff: 3D-Consistent Image Generation with Text-To-Image Models
Citation
@inproceedings{hollein2024viewdiff, title = {ViewDiff: 3D-Consistent Image Generation with Text-To-Image Models}, author = {H{\"o}llein, Lukas and Bo\v{z}i\v{c}, Alja\v{z} and M{\"u}ller, Norman and Novotny, David and Tseng, Hung-Yu and Richardt, Christian and Zollh{\"o}fer, Michael and Nie{\ss}ner, Matthias}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition}, year = {2024}, }
2023
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Ganerf: Leveraging discriminators to optimize neural radiance fields
Citation
@article{roessle2023ganerf, title = {Ganerf: Leveraging discriminators to optimize neural radiance fields}, author = {Roessle, Barbara and M{\"u}ller, Norman and Porzi, Lorenzo and Bul{\`o}, Samuel Rota and Kontschieder, Peter and Nie{\ss}ner, Matthias}, journal = {ACM Transactions on Graphics (TOG)}, volume = {42}, number = {6}, pages = {1--14}, year = {2023}, publisher = {ACM New York, NY, USA} } -
DiffRF: Rendering-Guided 3D Radiance Field Diffusion
Generate 3D radiance fields directly with rendering-guided diffusion.
Citation
@inproceedings{muller2023diffrf, title = {DiffRF: Rendering-Guided 3D Radiance Field Diffusion}, author = {M{\"u}ller, Norman and Siddiqui, Yawar and Porzi, Lorenzo and Bul{\`o}, Samuel Rota and Kontschieder, Peter and Nie{\ss}ner, Matthias}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) [Spotlight]}, pages = {12568--12577}, year = {2023}, } -
Panoptic Lifting for 3D Scene Understanding with Neural Fields
Citation
@inproceedings{siddiqui2022panoptic, title = {Panoptic Lifting for 3D Scene Understanding with Neural Fields}, author = {Siddiqui, Yawar and Porzi, Lorenzo and Bul{\'o}, Samuel Rota and M{\"u}ller, Norman and Nie{\ss}ner, Matthias and Dai, Angela and Kontschieder, Peter}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) [Spotlight]}, pages = {12568--12577}, year = {2023}, }
2022
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AutoRF: Learning 3D Object Radiance Fields From Single View Observations
Learn 3D object representations from single-view observations.
Citation
@inproceedings{Muller_2022_CVPR, title = {AutoRF: Learning 3D Object Radiance Fields From Single View Observations}, author = {M\"uller, Norman and Simonelli, Andrea and Porzi, Lorenzo and Bul\`o, Samuel Rota and Nie{\ss}ner, Matthias and Kontschieder, Peter}, year = {2022}, month = jun, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}, pages = {3971--3980} } -
3D Multi-Object Tracking with Differentiable Pose Estimation
Citation
@article{schmauser20223d, title = {3D Multi-Object Tracking with Differentiable Pose Estimation}, author = {Schmauser, Dominik and Qiu, Zeju and M{\"u}ller, Norman and Nie{\ss}ner, Matthias}, journal = {arXiv preprint arXiv:2206.13785}, year = {2022} }
2021
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Seeing Behind Objects for 3D Multi-Object Tracking in RGB-D Sequences
Citation
@inproceedings{mueller2021completetracking, title = {Seeing Behind Objects for 3D Multi-Object Tracking in RGB-D Sequences}, author = {M{\"u}ller, Norman and Wong, Yu-Shiang and Mitra, Niloy J. and Dai, Angela and Nie{\ss}ner, Matthias}, year = {2021}, booktitle = {Proc. Computer Vision and Pattern Recognition (CVPR), IEEE} }
2016
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Hypotheses testing for generalized order statistics with simple order restrictions on model parameters under the alternative
Citation
@article{doi:10.1080/02331888.2015.1094070, author = {Stefan Bedbur, Norman Müller and Kamps, Udo}, title = {Hypotheses testing for generalized order statistics with simple order restrictions on model parameters under the alternative}, journal = {Statistics}, volume = {50}, number = {4}, pages = {775--790}, year = {2016}, publisher = {Taylor \& Francis}, doi = {10.1080/02331888.2015.1094070} }
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