Paper submitted to MICCAI‘25.
Alpine PyTorch Library is now released. Excited to announce that Alpine - a flexible, distributed and user-friendly library for implicit neural representations is now released! Paper accepted at CVPR 2025, Workshop on Neural Fields beyond Conventional Cameras.
Learning Transferable features for Implicit Neural Representations, Kushal Vyas, Ahmed Imtiaz Humayun, Aniket Dashpute, Richard G. Baranuik, Ashok Veeraraghavan and Guha Balakrishnan, accepted at NeurIPS 2024!
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.