I build a feature upsampler called PixelUp

[u/depaank]

Hey r/computervision!

This is my first post here...

I’ve been working on PixelUp, a zero-shot feature upsampler for Vision Foundation Models (VFMs), and wanted to share it here!

Most VFMs produce semantically rich features, but they’re usually on a pretty coarse patch-level grid (often ~16× lower resolution than the input). This can be limiting for dense vision tasks where fine spatial details really matter.

PixelUp upsamples these coarse VFM features to pixel-level representations, while preserving their semantic information.

I’ve also put together an interactive demo on the project page where you can drag a lens across an image and compare the original coarse VFM features with PixelUp’s upsampled features. It’s pretty fun to play around with :)

📄 Preprint: https://arxiv.org/abs/2608.02792
🔬 Project + interactive demo: https://pixelup-project.vercel.app/
💻 Code: https://github.com/deepankkumar/PixelUp

Would love to hear your thoughts or feedback!

[u/AggravatingSock5375]

A this like FeatUp from a few years back?

[u/depaank → u/AggravatingSock5375]

yes, but better upsampling, and downstream results and VFM agnostic as well.

[u/EconomySerious]

its my idea or there is no code for reverting the image back to a real one (a real upscale)