PhD student @UniFAU. Part of @CogCoVi. I’m working at the intersection of computer vision, graphics, and machine learning. I like kernels and the @Chiefs.

Joined December 2021
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Maximilian Weiherer retweeted
Proud to present SchmidhubAI What do you think @SchmidhuberAI ? #SIGBOVIK
Excited to announce our latest (submitted to) SIGBOVIK 2026 @sigbovik paper: "SchmidhubAI: Accurate Historical Paper Attribution". We built an AI system that, given any modern AI paper, automatically determines which of its ideas were already published by Jürgen Schmidhuber.
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Maximilian Weiherer retweeted
We congratulate Gerd Faltings as the 2026 Abel Prize laureate! 🎉 He recives the Abel Prize "for introducing powerful tools in arithmetic geometry and resolving long-standing diophantine conjectures of Mordell and Lang".
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Maximilian Weiherer retweeted
Happy to share a major milestone: after years of development, we are officially launching Version 1.0 of the GeometricKernels library! To top it off, our accompanying paper has just been published in JMLR (MLOSS)! 🎉 github.com/geometric-kernels…
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Was super cool to have you here @UniFAU, @CSProfKGD!
Thank you @VisionBernie for being an AWESOME host! ❤️
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Maximilian Weiherer retweeted
We will have @CSProfKGD presenting on Friday 13th at noon in lecture hall 13 at @UniFAU "In Search of Universal Concepts" Very much looking forward to this visit! (twitter was the platform that initiated our contact, this is why I break my silence on this platform)
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Maximilian Weiherer retweeted
19 Nov 2025
Today we’re excited to unveil a new generation of Segment Anything Models: 1️⃣ SAM 3 enables detecting, segmenting and tracking of objects across images and videos, now with short text phrases and exemplar prompts. 🔗 Learn more about SAM 3: go.meta.me/591040 2️⃣ SAM 3D brings the model collection into the 3rd dimension to enable precise reconstruction of 3D objects and people from a single 2D image. 🔗 Learn more about SAM 3D: go.meta.me/305985 These models offer innovative capabilities and unique tools for developers and researchers to create, experiment and uplevel media workflows.
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🚀Excited to share our paper "Towards Integrating Multi-Spectral Imaging with Gaussian Splatting" was accepted at VMV 2025! 🎉 We fuse RGB & multi-spectral imagery (red, green, red-edge, near-infrared) into the 3D Gaussian Splatting framework. 🔗Project: meyerls.github.io/towards_mu…
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(3/4) To explore this, we systematically compare three strategies for incorporating multi-spectral data into 3DGS and show how spectral cross-talk (the exchange of information between RGB and multi-spectral data) enhances both RGB and spectral reconstructions.
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(4/4) Great work led by Josef Grün & Lukas Meyer and with @maxweiherer, @VisionBernie, Marc Stamminger, and @_linus_franke! 📄Paper: arxiv.org/pdf/2509.00989 📷Code: github.com/j-gruen/MS-Splatt… #VMV25 #GaussianSplatting #NeRF #Multispectral #Rendering

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Maximilian Weiherer retweeted
3 Sep 2025
Towards Integrating Multi-Spectral Imaging with Gaussian Splatting Contributions: • Formulation and comparison of multi-spectral integration strategies: We introduce and systematically evaluate three optimization paradigms—SEPARATE, SPLIT, and JOINT—for incorporating additional spectral bands into 3DGS. • We propose a set of optimizations for the JOINT strategy for multi-spectral reconstruction, along with practical insights from this analysis. • We examine how spectral cross-talk between spectral bands can improve reconstruction quality.
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Maximilian Weiherer retweeted
NeurIPS is pleased to officially endorse EurIPS, an independently-organized meeting taking place in Copenhagen this year, which will offer researchers an opportunity to additionally present their accepted NeurIPS work in Europe, concurrently with NeurIPS. Read more in our blog post and on the EurIPS website: blog.neurips.cc/2025/07/16/n… eurips.cc/

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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
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(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/irbsm
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(5/5) Huge thanks to my co-authors, Antonia von Riedheim, Vanessa Brébant, @VisionBernie, and Christoph Palm.
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Maximilian Weiherer retweeted
Huge progress by @artuursberzins @AndyRadler @e_volkmann on Geometry-Informed Neural Networks (GINNs)! Faster training, better shapes, and surprising insights from enforcing diversity. 📜: arxiv.org/abs/2402.14009 🖥️: arturs-berzins.github.io/GIN…
We introduce Geometry-Informed Neural Networks to train shape generative models without any data (!!), combining learning under constraints, neural fields as a suitable representation, and generating diverse solutions to under-determined problems: 🖥️: arturs-berzins.github.io/GIN…
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Maximilian Weiherer retweeted
Want to do 2 years of postdoc @CogCoVi @UniFAU in Germany with me? Open Topic around 3D Computer Vision, Neural Rendering, Human Vision, Inverse Rendering, Statistical Shape Modelling or related See the following tweets to see our featured research:
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Maximilian Weiherer retweeted
What are the odds that 5 labs start to work on a very similar story simultaneously? 4 papers on NeRFs with thermal rgb images released within one week on arXiv! I think this example visualizes the crazy speed of the @CVPR community Now let the Gaussians be splatted...
How can we learn a multi-modal neural radiance field? What’s the best way to integrate images from a second modality, other than RGB, into NeRF? Check out our new paper! Project page: mert-o.github.io/ThermalNeRF… Paper: arxiv.org/abs/2403.11865 Dataset: zenodo.org/records/11065834 1/6
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