Aaron Lefohn Profile
Aaron Lefohn

@aaronlefohn

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Vice President of Graphics Research at NVIDIA. Opinions are my own.

Joined June 2011
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@aaronlefohn
Aaron Lefohn
1 year
RT @wenzeljakob: If you try to optimize geometry using a differentiable renderer, there is an elephant in the room: geometry causes discont…
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@aaronlefohn
Aaron Lefohn
1 year
@wenzeljakob Congratulations!
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@aaronlefohn
Aaron Lefohn
1 year
RT @wenzeljakob: The free web version of "Physically Based Rendering: From Theory To Practice" is now based on the 4th edition of the book.…
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@aaronlefohn
Aaron Lefohn
1 year
RT @mmalex: so excited by the explosion of gaussian splatting; cant wait for the community to start playing with painterly styles; on dream…
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@aaronlefohn
Aaron Lefohn
1 year
RT @DaqiLin: Our new conditional resampled importance sampling (CRIS) opens up possibilities for designing resampling algorithms where mar…
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@aaronlefohn
Aaron Lefohn
1 year
This great foundational advancement in ReSTIR now enables reuse of sub-paths. Our theory research directly targets the needs of real-time rendering.
@nmkettunen
Markus Kettunen
1 year
Thrilled to announce our work "Conditional Resampled Importance Sampling and ReSTIR" (SIGGRAPH Asia 2023). We extend RIS and ReSTIR into conditional probability spaces, enabling novel forms of sample reuse. 1/7
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@aaronlefohn
Aaron Lefohn
1 year
RT @NVIDIAAIDev: Differentiable Slang easily integrates with existing codebases—from #Python, PyTorch, and #CUDA to HLSL. Here we introdu…
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@aaronlefohn
Aaron Lefohn
1 year
RT @NVIDIAAIDev: New #NVIDIAResearch paper: SLANG.D: Fast, Modular and Differentiable Shader Programming: shows how a single language serve…
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@aaronlefohn
Aaron Lefohn
1 year
RT @TangentVector: The Slang project is seeking experienced GPU/graphics/AI compiler programmers who want to be part of the development of…
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@aaronlefohn
Aaron Lefohn
1 year
RT @marcosalvi: I have been working with machine learning in graphics for a few years now and SLANG.D is the tool I wished I had from the s…
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@aaronlefohn
Aaron Lefohn
1 year
RT @BartWronsk: Some awesome work of my teammates on differentiable shading language, compatible with HLSL, and interoperable with CUDA/Pyt…
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@aaronlefohn
Aaron Lefohn
1 year
RT @csyonghe: Bringing autodiff to shaders is a challenging task. It takes years of effort to design the language that integrates different…
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@aaronlefohn
Aaron Lefohn
1 year
RT @csyonghe: Slang's Visual Studio Code extension fully supports the autodiff features.
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@aaronlefohn
Aaron Lefohn
1 year
Slang is now fully differentiable. Generate PyTorch plugins from shader code. Create rendering algorithms using appearance-based optimization. Build differentiable renderers using your current shader codebase. DiffSlang connects real-time rendering and learning.
@csyonghe
Yong He
1 year
Slang is an open-source, cross-platform shading language that targets D3D, Vulkan, GLSL, CUDA and C++. Today, it is fully differentiable, which means you can autodiff your existing shader code!
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@aaronlefohn
Aaron Lefohn
1 year
RT @NVIDIAAIDev: 🏃 Rapid recap of #NVIDIAResearch released recently at #SIGGRAPH2023 👇
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@aaronlefohn
Aaron Lefohn
1 year
Fantastic collaboration with @FidlerSanja's team. Working together to improve the quality of geometry extracted with inverse rendering.
@TianchangS
Tianchang Shen
2 years
Excited to share our #SIGGRAPH2023 project for better mesh extraction in learning & reconstruction pipelines. Project page: Joint work w/ @yoslber Jon Hasselgren @kangxue_yin @zianwang97 @ChenWenzheng @ZGojcic @FidlerSanja @nmwsharp @JunGao33210520 (1/n)
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@aaronlefohn
Aaron Lefohn
2 years
RT @kayvonf: 🎾 Haotian's AI tennis players are back... in 3D. 🎾 AI characters learn to play full 3D simulated tennis points by watching pr…
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@aaronlefohn
Aaron Lefohn
2 years
RT @jankautz: Honored to see that our work on Precomputed Radiance Transfer (2002) made it onto the SIGGRAPH Seminal Graphics Papers list:…
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@aaronlefohn
Aaron Lefohn
2 years
RT @SebAaltonen: The FlexiCubes technique by Nvidia (Flexible Isosurface Extraction for Gradient-based Mesh Optimization) seems very promis…
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@aaronlefohn
Aaron Lefohn
2 years
Buildings graphics systems for RL is an opportunity to completely rethink graphics system design.
@kayvonf
Kayvon Fatahalian
2 years
Why does RL need large-scale computing resources? Spoiler: it can get by with a lot less! Stanford's Madrona project is an ECS-based game engine that runs 10,000s of environments in parallel on a single GPU, reducing training from hours to minutes. 1/
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