| Same same but differnet: Semi-supervised defect detection with normalizing flows M Rudolph, B Wandt, B Rosenhahn Proceedings of the IEEE/CVF winter conference on applications of computer …, 2021 | 348 | 2021 |
| Repnet: Weakly supervised training of an adversarial reprojection network for 3d human pose estimation B Wandt, B Rosenhahn Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 271 | 2019 |
| Fully convolutional cross-scale-flows for image-based defect detection M Rudolph, T Wehrbein, B Rosenhahn, B Wandt Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2022 | 192 | 2022 |
| Canonpose: Self-supervised monocular 3d human pose estimation in the wild B Wandt, M Rudolph, P Zell, H Rhodin, B Rosenhahn Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 118 | 2021 |
| Probabilistic monocular 3d human pose estimation with normalizing flows T Wehrbein, M Rudolph, B Rosenhahn, B Wandt Proceedings of the IEEE/CVF international conference on computer vision …, 2021 | 112 | 2021 |
| Asymmetric student-teacher networks for industrial anomaly detection M Rudolph, T Wehrbein, B Rosenhahn, B Wandt Proceedings of the IEEE/CVF winter conference on applications of computer …, 2023 | 95 | 2023 |
| 3d reconstruction of human motion from monocular image sequences B Wandt, H Ackermann, B Rosenhahn IEEE transactions on pattern analysis and machine intelligence 38 (8), 1505-1516, 2016 | 64 | 2016 |
| Optical flow-based 3d human motion estimation from monocular video T Alldieck, M Kassubeck, B Wandt, B Rosenhahn, M Magnor Pattern Recognition: 39th German Conference, GCPR 2017, Basel, Switzerland …, 2017 | 58 | 2017 |
| Diffpose: Multi-hypothesis human pose estimation using diffusion models K Holmquist, B Wandt Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 45 | 2023 |
| Elepose: Unsupervised 3d human pose estimation by predicting camera elevation and learning normalizing flows on 2d poses B Wandt, JJ Little, H Rhodin Computer Vision and Pattern Recognition (CVPR) 1, 2022 | 45 | 2022 |
| Adaptpose: Cross-dataset adaptation for 3d human pose estimation by learnable motion generation M Gholami, B Wandt, H Rhodin, R Ward, ZJ Wang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 40 | 2022 |
| A kinematic chain space for monocular motion capture B Wandt, H Ackermann, B Rosenhahn Proceedings of the European Conference on Computer Vision (ECCV) Workshops, 0-0, 2018 | 40 | 2018 |
| Joint 3d human motion capture and physical analysis from monocular videos P Zell, B Wandt, B Rosenhahn Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017 | 35 | 2017 |
| Structuring autoencoders M Rudolph, B Wandt, B Rosenhahn Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 30 | 2019 |
| Region-based cycle-consistent data augmentation for object detection F Kluger, C Reinders, K Raetz, P Schelske, B Wandt, H Ackermann, ... 2018 IEEE International Conference on Big Data (Big Data), 5205-5211, 2018 | 26 | 2018 |
| Ganseg: Learning to segment by unsupervised hierarchical image generation X He, B Wandt, H Rhodin Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 20 | 2022 |
| Weakly-supervised learning of human dynamics P Zell, B Rosenhahn, B Wandt Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 19 | 2020 |
| Latentkeypointgan: Controlling gans via latent keypoints X He, B Wandt, H Rhodin arXiv preprint arXiv:2103.15812, 2021 | 17 | 2021 |
| Autolink: Self-supervised learning of human skeletons and object outlines by linking keypoints X He, B Wandt, H Rhodin Advances in Neural Information Processing Systems 35, 36123-36141, 2022 | 13 | 2022 |
| 3D human motion capture from monocular image sequences B Wandt, H Ackermann, B Rosenhahn Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2015 | 11 | 2015 |
Bodo RosenhahnL3S Research Center / Leibniz Universität Hannover在 tnt.uni-hannover.de 的电子邮件经过验证
