101 citations · 282 across the 22 of their papers we have counts for
5 papers · 1 filter
Deep Hierarchical Super Resolution for Scientific Data
Skylar W. Wurster, Hanqi Guo, Han-Wei Shen +2
We present a novel technique for hierarchical super resolution (SR) with neural networks (NNs), which upscales volumetric data represented with an octree data structure to a high-r…
DeepGD: A Deep Learning Framework for Graph Drawing Using GNN
Xiaoqi Wang, Kevin Yen, Yifan Hu +1
In the past decades, many graph drawing techniques have been proposed for generating aesthetically pleasing graph layouts. However, it remains a challenging task since different la…
Document Domain Randomization for Deep Learning Document Layout Extraction
Meng Ling, Jian Chen, Torsten Möller +7
We present document domain randomization (DDR), the first successful transfer of convolutional neural networks (CNNs) trained only on graphically rendered pseudo-paper pages to rea…
Local Latent Representation based on Geometric Convolution for Particle Data Feature Exploration
Haoyu Li, Han-Wei Shen
Feature related particle data analysis plays an important role in many scientific applications such as fluid simulations, cosmology simulations and molecular dynamics. Compared to…
VIS30K: A Collection of Figures and Tables from IEEE Visualization Conference Publications
Jian Chen, Meng Ling, Rui Li +8
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…