Nicolas von Lützow
@nicolasvluetzow
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PhD Student @ TUM Visual Computing & AI Lab
Joined April 2025
The code for “LinPrim: Linear Primitives for Differentiable Volumetric Rendering” is now out! 🧩 → Code: https://t.co/4YvQl1NkYf → Paper: https://t.co/VT1yxFA7cv
#NeurIPS2025
arxiv.org
Volumetric rendering has become central to modern novel view synthesis methods, which use differentiable rendering to optimize 3D scene representations directly from observed views. While many...
Thrilled to share that our work LinPrim has been accepted to NeurIPS 2025! 🎉 A big thank you to my advisor @MattNiessner for the guidance and support throughout the project! ✨ Also, make sure to check out the other amazing papers from our lab - lots of exciting research! 🚀
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Thrilled to share that our work LinPrim has been accepted to NeurIPS 2025! 🎉 A big thank you to my advisor @MattNiessner for the guidance and support throughout the project! ✨ Also, make sure to check out the other amazing papers from our lab - lots of exciting research! 🚀
All six of our submissions were accepted to #NeurIPS2025 🎉🥳 Awesome works about Gaussian Splatting Primitives, Lighting Estimation, Texturing, and much more GenAI :) Great work by @Peter4AI, @YujinChen_cv, @ZheningHuang, @jiapeng_tang, @nicolasvluetzow, @jnthnschmdt 🔥🔥🔥
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All six of our submissions were accepted to #NeurIPS2025 🎉🥳 Awesome works about Gaussian Splatting Primitives, Lighting Estimation, Texturing, and much more GenAI :) Great work by @Peter4AI, @YujinChen_cv, @ZheningHuang, @jiapeng_tang, @nicolasvluetzow, @jnthnschmdt 🔥🔥🔥
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📢 LinPrim: Linear Primitives for Differentiable Volumetric Rendering 📢 We use octahedra or tetrahedra as explicit as volumetric building blocks for gradient-based novel view synthesis - as an alternative to 3D Gaussians with discrete, bounded geometry. We show how it can be
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