19 citations · 22 across the 19 of their papers we have counts for
3 papers · 1 filter
3DMorph: Single-Image-Guided Local 3D Shape Editing and Morphing
Tobias Preintner, Yunfei Deng, Phillip Müller +5
Despite recent progress in 3D generation, intuitive editing of existing shapes remains limited. Unlike images, which benefit from well-established inpainting tools, general 3D obje…
EvoCAD: Evolutionary CAD Code Generation with Vision Language Models
Tobias Preintner, Weixuan Yuan, Adrian König +3
Combining large language models with evolutionary computation algorithms represents a promising research direction leveraging the remarkable generative and in-context learning capa…
On the Noise Scheduling for Generating Plausible Designs with Diffusion Models
Jiajie Fan, Laure Vuaille, Thomas Bäck +1
Deep Generative Models (DGMs) are widely used to create innovative designs across multiple industries, ranging from fashion to the automotive sector. In addition to generating imag…