Hanno Ackermann
About
In The Last Decade
Hanno Ackermann
18 papers receiving 263 citations
Peers
Comparison fields: 5 of 48
- Computer Vision and Pattern Recognition 229
- Artificial Intelligence 59
- Computational Mechanics 58
- Civil and Structural Engineering 18
- Control and Systems Engineering 17
Countries citing papers authored by Hanno Ackermann
This map shows the geographic impact of Hanno Ackermann's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Hanno Ackermann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hanno Ackermann more than expected).
Fields of papers citing papers by Hanno Ackermann
This network shows the impact of papers produced by Hanno Ackermann. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Hanno Ackermann. The network helps show where Hanno Ackermann may publish in the future.
Co-authorship network of co-authors of Hanno Ackermann
This figure shows the co-authorship network connecting the top 25 collaborators of Hanno Ackermann. A scholar is included among the top collaborators of Hanno Ackermann based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Hanno Ackermann. Hanno Ackermann is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Title | Journal | Authors | Indexed citations |
|---|---|---|---|---|
| 1 | Spatial-Temporal Transformer for Dynamic Scene Graph Generation | 2021 IEEE/CVF International Conference on Computer Vision (ICCV) | Yuren Cong, Wentong Liao et al. | 95 |
| 2 | Object Recognition from very few Training Examples for Enhancing Bicycle Maps | University of Twente Research Information | Hanno Ackermann, Michael Ying Yang et al. | 11 |
| 3 | Region-based Cycle-Consistent Data Augmentation for Object Detection | Hanno Ackermann, Bodo Rosenhahn et al. | 17 | |
| 4 | Physical High Dynamic Range Imaging with Conventional Sensors | Hanno Ackermann, Bodo Rosenhahn et al. | 1 | |
| 5 | Projective structure from facial motion | Hanno Ackermann, Jörn Östermann et al. | 2 | |
| 6 | On support relations and semantic scene graphs | ISPRS Journal of Photogrammetry and Remote Sensing | Michael Ying Yang, Wentong Liao et al. | 27 |
| 7 | Motion Segmentation Using Global and Local Sparse Subspace Optimization | Photogrammetric Engineering & Remote Sensing | Michael Ying Yang, Hanno Ackermann et al. | 1 |
| 8 | Apathy Is the Root of All Expressions | Hanno Ackermann, Sami S. Brandt et al. | 5 | |
| 9 | In-loop radial distortion compensation for long-term mosaicing of aerial videos | Hanno Ackermann, Jörn Östermann et al. | 1 | |
| 10 | 3D Reconstruction of Human Motion from Monocular Image Sequences | IEEE Transactions on Pattern Analysis and Machine Intelligence | Hanno Ackermann, Bodo Rosenhahn et al. | 25 |
| 11 | GLOBAL AND LOCAL SPARSE SUBSPACE OPTIMIZATION FOR MOTION SEGMENTATION | SHILAP Revista de lepidopterología | Michael Ying Yang, Hanno Ackermann et al. | 3 |
| 12 | 3D human motion capture from monocular image sequences | Hanno Ackermann, Bodo Rosenhahn et al. | 3 | |
| 13 | Projective Reconstruction from Incomplete Trajectories by Global and Local Constraints | Hanno Ackermann, Bodo Rosenhahn | 1 | |
| 14 | Multilinear pose and body shape estimation of dressed subjects from image sets | Max Planck Institute for Plasma Physics | Nils Hasler, Hanno Ackermann et al. | 69 |
| 15 | Trajectory reconstruction for affine structure-from-motion by global and local constraints | 2009 IEEE Conference on Computer Vision and Pattern Recognition | Hanno Ackermann, Bodo Rosenhahn | 2 |
| 16 | Fast Projective Reconstruction: Toward Ultimate Efficiency | Hanno Ackermann, Kenichi Kanatani | 1 | |
| 17 | Robust and Efficient 3-D Reconstruction by Self-Calibration. | Machine Vision and Applications | Hanno Ackermann, Kenichi Kanatani | 5 |
| 18 | Uncalibrated Factorization Using a Variable Symmetric Affine Camera | IEICE Transactions on Information and Systems | Kenichi Kanatani, Yasuyuki Sugaya et al. | 5 |
| 19 | 3-D Reconstruction by Uncalibrated Factorization: Comparative Experiments | Kenichi Kanatani, Yasuyuki Sugaya et al. | 0 |
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.