| Scannet: Richly-annotated 3d reconstructions of indoor scenes A Dai, AX Chang, M Savva, M Halber, T Funkhouser, M Nießner Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 4590 | 2017 |
| Matterport3d: Learning from rgb-d data in indoor environments A Chang, A Dai, T Funkhouser, M Halber, M Niessner, M Savva, S Song, ... arXiv preprint arXiv:1709.06158, 2017 | 2109 | 2017 |
| Volumetric and multi-view cnns for object classification on 3d data CR Qi, H Su, M Nießner, A Dai, M Yan, LJ Guibas Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 2025 | 2016 |
| Bundlefusion: Real-time globally consistent 3d reconstruction using on-the-fly surface reintegration A Dai, M Nießner, M Zollhöfer, S Izadi, C Theobalt ACM Transactions on Graphics (ToG) 36 (4), 1, 2017 | 1098 | 2017 |
| Shape completion using 3d-encoder-predictor cnns and shape synthesis A Dai, C Ruizhongtai Qi, M Nießner Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 764 | 2017 |
| 3d-sis: 3d semantic instance segmentation of rgb-d scans J Hou, A Dai, M Nießner Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 547 | 2019 |
| 3dmv: Joint 3d-multi-view prediction for 3d semantic scene segmentation A Dai, M Nießner Proceedings of the European Conference on Computer Vision (ECCV), 452-468, 2018 | 397 | 2018 |
| Scancomplete: Large-scale scene completion and semantic segmentation for 3d scans A Dai, D Ritchie, M Bokeloh, S Reed, J Sturm, M Nießner Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 369 | 2018 |
| Scan2cad: Learning cad model alignment in rgb-d scans A Avetisyan, M Dahnert, A Dai, M Savva, AX Chang, M Nießner Proceedings of the IEEE/CVF Conference on computer vision and pattern …, 2019 | 279 | 2019 |
| Database‐assisted object retrieval for real‐time 3d reconstruction Y Li, A Dai, L Guibas, M Nießner Computer graphics forum 34 (2), 435-446, 2015 | 253 | 2015 |
| Learning to navigate the energy landscape J Valentin, A Dai, M Nießner, P Kohli, P Torr, S Izadi, C Keskin 2016 Fourth International Conference on 3D Vision (3DV), 323-332, 2016 | 174 | 2016 |
| Sg-nn: Sparse generative neural networks for self-supervised scene completion of rgb-d scans A Dai, C Diller, M Nießner Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 169 | 2020 |
| Language-grounded indoor 3d semantic segmentation in the wild D Rozenberszki, O Litany, A Dai European Conference on Computer Vision, 125-141, 2022 | 163 | 2022 |
| Scannet++: A high-fidelity dataset of 3d indoor scenes C Yeshwanth, YC Liu, M Nießner, A Dai Proceedings of the IEEE/CVF International Conference on Computer Vision, 12-22, 2023 | 154 | 2023 |
| Transformerfusion: Monocular rgb scene reconstruction using transformers A Bozic, P Palafox, J Thies, A Dai, M Nießner Advances in Neural Information Processing Systems 34, 1403-1414, 2021 | 153 | 2021 |
| Shading-based refinement on volumetric signed distance functions M Zollhöfer, A Dai, M Innmann, C Wu, M Stamminger, C Theobalt, ... ACM Transactions on Graphics (ToG) 34 (4), 1-14, 2015 | 153 | 2015 |
| Hyperdiffusion: Generating implicit neural fields with weight-space diffusion Z Erkoç, F Ma, Q Shan, M Nießner, A Dai Proceedings of the IEEE/CVF international conference on computer vision …, 2023 | 118 | 2023 |
| Npms: Neural parametric models for 3d deformable shapes P Palafox, A Božič, J Thies, M Nießner, A Dai Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 116 | 2021 |
| Panoptic lifting for 3d scene understanding with neural fields Y Siddiqui, L Porzi, SR Buló, N Müller, M Nießner, A Dai, P Kontschieder Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 115 | 2023 |
| Scan2mesh: From unstructured range scans to 3d meshes A Dai, M Nießner Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 112 | 2019 |
Matthias NießnerProfessor of Computer Science, Technical University of MunichBestätigte E-Mail-Adresse bei tum.de