Maximilian Weiherer

🚀 Excited to share that our paper "Towards Integrating Multi-Spectral Imaging with Gaussian Splatting" was accepted at VMV 2025! 🎉

🔗 Project: meyerls.github.io/towards_mult...
📄 Paper: arxiv.org/pdf/2509.00989
💻 Code: github.com/j-gruen/MS-S...

#VMV25 #GaussianSplatting #NeRF #Multispectral

I still remember the moment you first had this idea—during lunch at York University about 1.5 years ago. These guys have been working on this for more than ONE YEAR!!! This is insane, and way beyond a normal Sigbovik paper. Congrats on this huge success and an amazing paper!

Tired of seeing your papers being rejected from @cvprconference.bsky.social ? Let's revisit our 2023 #SIGBOVIK paper: "From Zero to Hero: Convincing with Extremely Complicated Math", led by @maxweiherer.bsky.social

Paper: mweiherer.github.io/zero2hero.pdf
Code: github.com/mweiherer/ze...
1/4

Absolut. Und dann auch noch j = sqrt(-1).

Jetzt weißt du wieso ich mich angegriffen fühle wenn mich jemand als Ingenieur bezeichnet. Ich möchte freundlich darauf hinweisen dass nicht alle Ingenieure pi auf 3 abrunden, oder e auf 2.

(5/5) Huge thanks to my co-authors, Antonia von Riedheim, Vanessa Brébant, @visionbernie.bsky.social, and Christoph Palm.

(4/5) The resulting model is free of correspondence errors, captures detailed surface geometry, and outperforms the RBSM in various surface reconstruction tasks.

The iRBSM is publicly available for research purposes!

Model: rbsm.re-mic.de/implicit
Code: github.com/mweiherer/ir...

(3/5) Using an implicit (correspondence-free) representation to model breast shapes from surface-only 3D scans is highly advantageous, as registering these scans is extremely hard: almost no features, large deformations, and severe occlusions (esp. underbust).

(2/5) Our model uses a DeepSDF architecture and is trained directly on 168 raw 3D breast scans--without ground truth supervision. Contrary to the RBSM, no surface registration is required to bring training data into correspondence.

Happy to share our latest 3D generative breast model: the *implicit* RBSM, or iRBSM for short. As opposed to its PCA-based predecessor, the iRBSM leverages implicit neural representations, yielding a highly detailed and expressive 3D breast model.

Paper: arxiv.org/abs/2412.13244

I am very excited to announce our paper “DynaMoN: Motion-Aware Fast and Robust Camera Localization for Dynamic Neural Radiance Fields” has been accepted to #IEEE RA-L.

Paper: ieeexplore.ieee.org/document/107...
Project page: hannahhaensen.github.io/DynaMoN/
Code: github.com/HannahHaense...

The coffee machine in our lab broke, and won’t be fixed by the end of January 2025. This is just so unfair. I’ll better stay at home for the next two months.

Excited to share our paper which will be presented at #3DV2025

✨ Gen3DSR: Generalizable 3D Scene Reconstruction via Divide and Conquer from a Single View ✨
🌐 Project page: andreeadogaru.github.io/Gen3DSR
📄 Paper: arxiv.org/abs/2404.03421
👩‍💻 Code: github.com/AndreeaDogar...
(1/5)