1 code implementation • 3 Apr 2024 • Deng Luo, Zainab Alsuwaykit, Dawar Khan, Ondřej Strnad, Tobias Isenberg, Ivan Viola
To ensure a meaningful correlation between the sampled densities and the protein structure, we propose a novel loss function based on a multi-resolution volume-array approach and the exploitation of the negative space.
no code implementations • 7 Mar 2024 • Jian Chen, Petra Isenberg, Robert S. Laramee, Tobias Isenberg, Michael Sedlmair, Torsten Moeller, Rui Li
In addition to the visualization typology from images, we provide a dataset of 6, 833 tagged images and an online tool that can be used to explore and analyze the large set of labeled images.
no code implementations • 20 May 2021 • Meng Ling, Jian Chen, Torsten Möller, Petra Isenberg, Tobias Isenberg, Michael Sedlmair, Robert S. Laramee, Han-Wei Shen, Jian Wu, C. Lee Giles
We present document domain randomization (DDR), the first successful transfer of convolutional neural networks (CNNs) trained only on graphically rendered pseudo-paper pages to real-world document segmentation.
no code implementations • 22 Dec 2020 • Jian Chen, Meng Ling, Rui Li, Petra Isenberg, Tobias Isenberg, Michael Sedlmair, Torsten Möller, Robert S. Laramee, Han-Wei Shen, Katharina Wünsche, Qiru Wang
We present the VIS30K dataset, a collection of 29, 689 images that represents 30 years of figures and tables from each track of the IEEE Visualization conference series (Vis, SciVis, InfoVis, VAST).