12 citations · 42 across the 15 of their papers we have counts for
4 papers · 1 filter
Curve-based Neural Style Transfer
Yu-hsuan Chen, Levent Burak Kara, Jonathan Cagan
This research presents a new parametric style transfer framework specifically designed for curve-based design sketches. In this research, traditional challenges faced by neural sty…
Automating Style Analysis and Visualization With Explainable AI -- Case Studies on Brand Recognition
Yu-hsuan Chen, Levent Burak Kara, Jonathan Cagan
Incorporating style-related objectives into shape design has been centrally important to maximize product appeal. However, stylistic features such as aesthetics and semantic attrib…
StressGAN: A Generative Deep Learning Model for 2D Stress Distribution Prediction
Haoliang Jiang, Zhenguo Nie, Roselyn Yeo +2
Using deep learning to analyze mechanical stress distributions has been gaining interest with the demand for fast stress analysis methods. Deep learning approaches have achieved ex…
Data-driven Upsampling of Point Clouds
Wentai Zhang, Haoliang Jiang, Zhangsihao Yang +3
High quality upsampling of sparse 3D point clouds is critically useful for a wide range of geometric operations such as reconstruction, rendering, meshing, and analysis. In this pa…