Kushal Vyas

Learning Transferable Features for Implicit Neural Representations

Kushal Vyas Ahmed Imtiaz Humayun Aniket Dashpute Richard G Baranuik Ashok Veeraraghavan Guha Balakrishnan

NeurIPS, 2024

We showcase STRAINER: A framework to learn transferable and generalizable features for implicit neural representations(INRs) by capturing the underlying low-frequency structural prior from limited data extremely powerful for signal fitting and inverse problems. We use only 10 images as training dataset and achieve superior reconstruction quality compared to recent meta-learing and transformer networks.