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:

Can someone more familiar with sota diffusion tell me what's currently typically used, and does it matter at scale?

Reviewers will be released upon acceptance of the manuscript.

somewhat niche meme

Accepted to #3DV2026!

wandb down

I don't want to submit to any conference that would accept my paper.

CVPR compute form is so incredibly dumb.

Did everyone get this?

why is this so true

I just put `MultiScaleDeformableAttention` wheels on pypi under `ms-deform-attn`. Should make stuff involving mask2former a bit smoother.

Gonna start using this

Pro-tip: Set the loss range in your wandb plot unreasonably low to motivate your models to try harder.

AGI is when models write good multi-dim torch indexing code.

Cursor tab likes to sprinkle in some "delete 20 lines of code" seemingly at random. I like that it adds a bit of excitement to the coding experience.

Spooky features

Sweden is a Monarchy that functions like a Democracy. Some other countries do it the other way round. Must say I prefer the former.

All papers I was assigned for 3DV were significantly higher quality than the papers I was assigned for ICCV.

Yesterday I (successfully) defended my doctoral thesis 🎉 You are now forced to call me Dr. Edstedt.

Worth going!

Hinton, the random plumber of AI

Went to Carolina Revidiva in Uppsala to see Carta Marina (my thesis cover) in person