L. Mehl, J. Schmalfuss, A. Jahedi, Y. Nalivayko, and A. Bruhn. Dataset, (2023)Related to: Lukas Mehl, Jenny Schmalfuss, Azin Jahedi, Yaroslava Nalivayko, Andrés Bruhn: Spring: A High-Resolution High-Detail Dataset and Benchmark for Scene Flow, Optical Flow and Stereo. Proc. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023. arXiv: 2303.01943.
Y. Wang. Software, (2023)Related to: Y. Wang, M. Bâce and A. Bulling, "Scanpath Prediction on Information Visualisations," in IEEE Transactions on Visualization and Computer Graphics. doi: 10.1109/TVCG.2023.3242293.
J. Görtler, T. Spinner, D. Weiskopf, and O. Deussen. Software, (2022)Related to: J. Görtler, T. Spinner, D. Streeb, D. Weiskopf and O. Deussen, Üncertainty-Aware Principal Component Analysis," in IEEE Transactions on Visualization and Computer Graphics, vol. 26, no. 1, pp. 822-831, Jan. 2020. doi: 10.1109/TVCG.2019.2934812.
D. Hägele, T. Krake, and D. Weiskopf. Dataset, (2022)Related to: D. Hägele, T. Krake and D. Weiskopf, Üncertainty-Aware Multidimensional Scaling," in IEEE Transactions on Visualization and Computer Graphics, 2022. doi: 10.1109/TVCG.2022.3209420.
D. Garkov, C. Müller, M. Braun, D. Weiskopf, and F. Schreiber. Dataset, (2022)Related to: Garkov, D., Müller, C., Braun, M., Weiskopf, D., Schreiber, F., “Research Data Curation in Visualization : Position Paper”, in 2022 IEEE Workshop on Evaluation and Beyond - Methodological Approaches for Visualization (BELIV), IEEE, 2022. doi: 10.1109/BELIV57783.2022.00011.
N. Rodrigues, C. Schulz, S. Döring, D. Baumgartner, T. Krake, and D. Weiskopf. Software, (2022)Related to: Nils Rodrigues, Christoph Schulz, Sören Döring, Daniel Baumgartner, Tim Krake, and Daniel Weiskopf, "Relaxed Dot Plots: Faithful Visualization of Samples and Their Distribution," in IEEE Transactions on Visualization and Computer Graphics, vol. 29, no. 1, Jan. 2023, accepted.
L. Mehl, C. Beschle, A. Barth, and A. Bruhn. Dataset, (2022)Related to: L. Mehl, C. Beschle, A. Barth, A. Bruhn: An Anisotropic Selection Scheme for Variational Optical Flow Methods with Order-Adaptive Regularisation. Proc. International Conference on Scale Space and Variational Methods in Computer Vision (SSVM). Lecture Notes in Computer Science, Vol. 10302, 140-152, Springer, 2021. doi: 10.1007/978-3-030-75549-2_12.
K. Angerbauer, N. Rodrigues, R. Cutura, S. Öney, N. Pathmanathan, C. Morariu, D. Weiskopf, and M. Sedlmair. Dataset, (2022)Related to: Katrin Angerbauer, Nils Rodrigues, Rene Cutura, Seyda Öney, Nelusa Pathmanathan, Cristina Morariu, Daniel Weiskopf, and Michael Sedlmair. 2022. Accessibility for Color Vision Deficiencies: Challenges and Findings of a Large Scale Study on Paper Figures. In CHI Conference on Human Factors in Computing Systems (CHI '22). Association for Computing Machinery, New York, NY, USA, Article 134, 1-23. doi: 10.1145/3491102.3502133.
Y. Wang. Software, (2022)Related to: Y. Wang, C. Jiao, M. Bâce and A. Bulling, "VisRecall: Quantifying Information Visualisation Recallability via Question Answering," in IEEE Transactions on Visualization and Computer Graphics, vol. 28, no. 12, pp. 4995-5005, 1 Dec. 2022. doi: 10.1109/TVCG.2022.3198163.
V. Bruder, C. Müller, S. Frey, and T. Ertl. Software, (2020)Related to: Bruder, V., Müller, C., Frey, S., Ertl, T. (2019). On Evaluating Runtime Performance of Interactive Visualizations. IEEE Transactions on Visualization and Computer Graphics, 10.1109/TVCG.2019.2898435. Advance online publication. doi: 10.1109/TVCG.2019.2898435.
