Frequency Deformation

Frequency deformation research focuses on efficiently and accurately modeling and manipulating the shape of objects, particularly meshes and implicit surfaces, by separating and controlling deformations at different frequency levels (low and high). Current approaches utilize various techniques, including graph neural networks operating on spectral mesh representations, and model-driven decoders working in the Fourier domain to achieve faster and more accurate deformation prediction. This work is significant for applications ranging from virtual world creation and computer-aided design to robotics and minimally invasive surgery, improving the realism and efficiency of shape manipulation in these fields.