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Christoph Lassner
@chlassner
Co-founder of World Labs; spatial intelligence for 3D and 4D perception, rendering and generation.
San Francisco, CA
Joined October 2015
Posts
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    Hey researcher friends! How are you discovering interesting papers outside of your network these days? @karpathy’s arxiv-sanity-lite.com? @labmlai’s overview papers.labml.ai? Something else? :)
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    Couldn't be more excited to share World Labs today, our journey towards Spatial Intelligence! We are making the world your oyster with @drfeifei, @BenMildenhall, @jcjohnss and a world class team - more to come!
    Hello, world! We are World Labs, a spatial intelligence company building Large World Models (LWMs) to perceive, generate, and interact with the 3D world. Read more: worldlabs.ai/about
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    Mark showed some really exciting tech today at #metaconnect2022 ! With my team @BozicAljaz, @denglide, @LukeDoukakis we created the object reconstruction and rendering using neural radiance fields youtu.be/hvfV-iGwYX8?t=… and can share a few more details.
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    The #CVPR motion on authors being added to the reviewer pool has interesting consequences: what happens to engineer contributors? They can pass all tests to be authors: contributed to idea ✅, implementation ✅, paper ✅. But they might not be well qualified reviewers. #CVPR2023
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    youtube.com/watch?v=gUARgo… Demoing our real-time #NeRF and object reconstruction to @jetscott from @CNET - fully interactive in #VR! Thanks for the kind words! Co-presented with the excellent inverse-rendering work by @flycooler and team.
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    Replying to @chlassner
    This technology expands the range of objects that can be scanned very far and is very easy to use, yet produces incredibly detailed results that were impossible to create before---so you can take with you, share or present objects in VR with true-to-life fidelity.
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    Replying to @wenzeljakob @seb_spe and @DelioVicini
    I just searched a lot for different options to write high performance (auto-)differentiable CUDA code and did not find frameworks that satisfied the constraints I had in mind. Will check out Dr. Jit!
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    Replying to @chlassner
    Why is this exciting? Photogrammetry has been used in the past to create assets for CG/games, but could not be used for certain object classes (for example, objects with fur such as the teddy bear or semi-transparent objects).
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    Does anyone have experience with using Rust-GPU (buff.ly/3Vsrdhr) for larger or performance-critical projects? How does the performance compare to CUDA? Any other interesting initiatives for language embedded and platform independent GPGPU programming?
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    Getting ready to head out to NeurIPS tomorrow. If you’re around and would like to chat in person, let me know! See you in Vancouver!
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    RT @[email protected] Dear network: do you know who is working on the macOS dynamic linker (/usr/bin/ld) at #Apple? Not to be overly dramatic, but it has started warning about an issue that (if true) will soon break every compiled Python extension (NumPy, PyTorch, (1/2)
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    Replying to @chlassner
    These are results of a fully automatic pipeline - what you see is what you get purely from a phone video with no depth information, markers, etc., and there has been no artist editing, refinement or cleanup.
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    Replying to @chlassner
    We manage to reconstruct the semi-transparent parts of the objects from the phone video directly and, thanks to volumetric rendering, they are composited correctly with the environment and other objects. The scientific fine-print: