| Occupancy networks: Learning 3d reconstruction in function space L Mescheder, M Oechsle, M Niemeyer, S Nowozin, A Geiger Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 1989 | 2019 |
| Differentiable volumetric rendering: Learning implicit 3d representations without 3d supervision M Niemeyer, L Mescheder, M Oechsle, A Geiger Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 677 | 2020 |
| Convolutional occupancy networks S Peng, M Niemeyer, L Mescheder, M Pollefeys, A Geiger Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 621 | 2020 |
| Giraffe: Representing scenes as compositional generative neural feature fields M Niemeyer, A Geiger Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 576 | 2021 |
| Graf: Generative radiance fields for 3d-aware image synthesis K Schwarz, Y Liao, M Niemeyer, A Geiger Advances in Neural Information Processing Systems 33, 20154-20166, 2020 | 561 | 2020 |
| Texture fields: Learning texture representations in function space M Oechsle, L Mescheder, M Niemeyer, T Strauss, A Geiger Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 241 | 2019 |
| Occupancy flow: 4d reconstruction by learning particle dynamics M Niemeyer, L Mescheder, M Oechsle, A Geiger Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 226 | 2019 |
| Regnerf: Regularizing neural radiance fields for view synthesis from sparse inputs M Niemeyer, JT Barron, B Mildenhall, MSM Sajjadi, A Geiger, N Radwan Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 170 | 2022 |
| Monosdf: Exploring monocular geometric cues for neural implicit surface reconstruction Z Yu, S Peng, M Niemeyer, T Sattler, A Geiger Advances in neural information processing systems 35, 25018-25032, 2022 | 105 | 2022 |
| Shape as points: A differentiable poisson solver S Peng, C Jiang, Y Liao, M Niemeyer, M Pollefeys, A Geiger Advances in Neural Information Processing Systems 34, 13032-13044, 2021 | 93 | 2021 |
| Voxgraf: Fast 3d-aware image synthesis with sparse voxel grids K Schwarz, A Sauer, M Niemeyer, Y Liao, A Geiger Advances in Neural Information Processing Systems 35, 33999-34011, 2022 | 61 | 2022 |
| Campari: Camera-aware decomposed generative neural radiance fields M Niemeyer, A Geiger 2021 International Conference on 3D Vision (3DV), 951-961, 2021 | 55 | 2021 |
| Learning implicit surface light fields M Oechsle, M Niemeyer, C Reiser, L Mescheder, T Strauss, A Geiger 2020 International Conference on 3D Vision (3DV), 452-462, 2020 | 36 | 2020 |
| DreamBooth3D: Subject-Driven Text-to-3D Generation A Raj, S Kaza, B Poole, M Niemeyer, N Ruiz, B Mildenhall, S Zada, ... arXiv preprint arXiv:2303.13508, 2023 | 13 | 2023 |
| Automatic Semantic Labelling of Images by Their Content Using Non-Parametric Bayesian Machine Learning and Image Search Using Synthetically Generated Image Collages M Niemeyer, O Arandjelović 2018 IEEE 5th International Conference on Data Science and Advanced …, 2018 | 9 | 2018 |
| TextMesh: Generation of Realistic 3D Meshes From Text Prompts C Tsalicoglou, F Manhardt, A Tonioni, M Niemeyer, F Tombari arXiv preprint arXiv:2304.12439, 2023 | 8 | 2023 |
| NeRFMeshing: Distilling Neural Radiance Fields into Geometrically-Accurate 3D Meshes MJ Rakotosaona, F Manhardt, DM Arroyo, M Niemeyer, A Kundu, ... arXiv preprint arXiv:2303.09431, 2023 | 4 | 2023 |
| NEWTON: Neural View-Centric Mapping for On-the-Fly Large-Scale SLAM H Matsuki, K Tateno, M Niemeyer, F Tombari arXiv preprint arXiv:2303.13654, 2023 | | 2023 |
| MonoSDF: Exploring Monocular Geometric Cues for Neural Implicit Surface Reconstruction Y Zehao, S Peng, M Niemeyer, T Sattler, A Geiger arXiv, 2022 | | 2022 |
| Open-Set 3D Scene Segmentation with Rendered Novel Views F Engelmann, F Manhardt, M Niemeyer, K Tateno, M Pollefeys, F Tombari | | |
Andreas GeigerProfessor of Computer Science, University of Tübingen and Tübingen AI CenterVerified email at uni-tuebingen.de
