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View Dependent

View Dependent
View Dependent
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5 of 18
  • Gaussian Splatting with Bernhard Kerbl
    Co-hosts Michael Rubloff and MrNeRF speak to co-first author of Gaussian Splatting, Bernhard Kerbl. Papers 3D Gaussian Splatting for Real Time Radiance Field Rendering Taming 3DGS: High-Quality Radiance Fields with Limited Hierarchical 3D Gaussian Representation for Real-Time Rendering
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    1:05:44
  • Radiance Fields and The Future with Jon Barron
    Co-hosts Michael Rubloff and Mr. NeRF speak to co-author of NeRF and Google researcher, Jon Barron. This is an exciting episode covering everything from the discovery of NeRF, subsequent Radiance Field methods, things yet to come, and more!
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    59:53
  • Gaussian Splatting Surface Reconstruction with Antoine Guédon
    Co-hosts Michael Rubloff and Mr. NeRF talk to researcher, Antoine Guédon about his work on Gaussian Splatting to Mesh. Check out Antoine's work here: https://anttwo.github.io/ Gaussian Frosting Blender Plugin: https://github.com/Anttwo/sugar_frosting_blender_addon
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    1:11:44
  • Gaussian Splatting on Mac and AMD with Brush
    Co-hosts Michael Rubloff and Mr.NeRF talk to Arthur Brussee, whose creation Brush, is allowing people to train Gaussian Splatting in a web browser. If you've been wanting to try 3DGS on Mac, AMD, Intel or NVIDIA cards, this episode is for you! Brush (On Chrome only): https://arthurbrussee.github.io/brush-demo/ GitHub page: https://github.com/ArthurBrussee/brush Rerun Data Visualizer: https://rerun.io/ CAT3D: https://cat3d.github.io/
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    58:12
  • MonST3R and Spann3R
    Co-hosts Michael Rubloff and MrNeRF speak to the authors of MonST3R and Spann3R, Junyi Zhang and Hengyi Wang. https://monst3r-project.github.io/ https://hengyiwang.github.io/projects/spanner
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    1:00:14

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About View Dependent

Welcome to the View Dependent podcast, where we talk to leaders in the 3D reconstruction space of Radiance Field technologies, focusing on methods like Neural Radiance Fields (#NeRFs), Gaussian Splatting (#3DGS), Gaussian Ray Tracing (#3DGRT), and Diffusion based models.
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