2 papers
cs.CV2025
Upsample Anything: A Simple and Hard to Beat Baseline for Feature Upsampling
Minseok Seo, Mark Hamilton, Changick Kim
We present \textbf{Upsample Anything}, a lightweight test-time optimization (TTO) framework that restores low-resolution features to high-resolution, pixel-wise outputs without any…
cs.LG2025
I-Con: A Unifying Framework for Representation Learning
Shaden Alshammari, John Hershey, Axel Feldmann +2
As the field of representation learning grows, there has been a proliferation of different loss functions to solve different classes of problems. We introduce a single information-…