Functional programming be like:

Me to my models in wandb

Steer!

How are these so accurate

Oof

Accepted to the Image Matching Workshop at #CVPR26!

Introducing LoMa-R! A rotation invariant version of LoMa. Code: github.com/davnords/loma Paper: arxiv.org/abs/2604.11809

Checking my training batch

Introducing HardMatch!

Introducing LoMa, the next generation of feature matcher!

from loma import LoMa

Out in a few hours!

The keynotes and award talks at 3DV 2026 have been made available, with talks by Christian Rupprecht ("3D computer vision done and Dusted?", Angela Dai, Alec Jacobson, Jitendra Malik, Songyou Peng and Michael Niemeyer. www.youtube.com/playlist?lis...

Had a shampoo that bragged about having 92% natural ingredients. Checked the back and it was 89% water.

Make sure to come by our poster right now if you are at #3DV2026!

Yesterday, @parskatt.bsky.social and the RoMa v2 team got an award at the annual Swedish Symposium on Image Analysis. FeelsGoodMan. @bokmangeorg.bsky.social @fredkahl.bsky.social @jastermark.bsky.social @liucvl.bsky.social et. al.

Coming soon

Putting a vowel before 3R should be illegal.

Take me down to the Parallax city where the far moves slow and the near moves quickly

Is there any current 3/4D reconstruction method able to accurately reconstruct this scene? (with correct size of thunderstorm)

regardless of your views on AI, i strongly agree with this viewpoint! you are not funded by taxpayers to optimize your knowledge consumption workflows. it's good that you enjoy your job, you are getting paid to enjoy your job

Correspondence is a much prettier word than match. Pixel correspondence makes more sense than feature matching (what is a feature?).

you're welcome

Can someone please explain why 3DV papers are consistently interesting and ICCV/CVPR (3D) papers are consistently boring?

Something I predict for academic papers is that (complex) implementations/proofs will get significantly less credit than previously due to LLMs. Not sure if this will be a good or bad thing.

Have to say I like the "Nice ---" style of GPT models.

Sad to report that I now have the type of brain damage where you have to write 1024 instead of 1000.

Since this take is so completely wrong I have to repost as well. The posted figure is only showing the top-50. No shit it's gonna show the biggest companies and unis. There's a productive conversation to be had, but this aint it. aiworld.eu/story/from-b...

At this point I'm extremely allergic to any non top-level defaults.

CVPR submissions now have this retracted look, presumably due to previous OpenReview leaks.

Not sure if anyone noticed but there are pycolmap CUDA wheels since a month back: pypi.org/project/pyco...

My predictions: - debacle will not impact reviewing in a significant way - ratings will likely be similar next year - peer review will continue to struggle with review load

Oof

SPIDER: Spatial Image CorresponDence Estimator for Robust Calibration Zhimin Shao, Abhay Yadav, Rama Chellappa, Cheng Peng tl;dr: 3D VFM+2D ConvNet->feature extraction backbone; 3D descriptor head (for geometry)+2D warp head (for pattern) fusion arxiv.org/abs/2511.17750

Pixel reconstruction has recently been somewhat overshadowed by latent SSL approaches such as DINO. However, for 3D tasks we show that a scaled and simplified version of multi-view MAE (which we call MuM) can outperform DINOv3, all while using orders of magnitude less compute!

Put up my simple skysegmentation model on github over at github.com/Parskatt/sky... Results are pretty crisp, but it doesn't really deal with clouds (it's literally just a linear model on top of some coarse segmentation output).

RoMa v2 is now out! (github.com/Parskatt/rom..., arxiv.org/abs/2511.15706) Here are the main improvements we made since RoMa: