View Dependent

View Dependent
  • ٥٫٠ (١)
  • التكنولوجيا
  • يتم التحديث أسبوعيًا

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.

  1. ٢٣‏/١٢‏/٢٠٢٤

    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

    ١ س ٦ د

  2. ٠٥‏/١٢‏/٢٠٢٤

    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!

    ١ من الساعات

  3. ٠٤‏/١٢‏/٢٠٢٤

    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

    ١ س ١٢ د

  4. ١٨‏/١١‏/٢٠٢٤

    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/

    ٥٨ من الدقائق

  5. ١٨‏/١١‏/٢٠٢٤

    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

    ١ من الساعات

  6. ١٨‏/١١‏/٢٠٢٤

    Compressing Gaussian Splatting with Wieland Morgenstern

    Co-hosts Michael Rubloff and MrNeRF speak to Wieland Morgenstern about Gaussian Splatting compression and his paper, Self Organizing Gaussians. Self Organizing Gaussians can compress 90% of a .ply and is what Nerfstudio currently uses as their compression method. Project: https://fraunhoferhhi.github.io/Self-Organizing-Gaussians/ Code: https://github.com/fraunhoferhhi/Self-Organizing-Gaussians

    ١ س ٤ د

  7. ١٨‏/١١‏/٢٠٢٤

    Gaussian Splatting in SideFX Houdini with GSOPS

    This week on The View Dependent Podcast, co-hosts Michael Rubloff and MrNeRF speak to David Rhodes and Ruben Diaz of GSOPS 2.0. We'll discuss why Radiance Field methods, such as 3DGS are perfect fits for Houdini, what you can do within Houdini, and more! GSOPs Github: https://github.com/david-rhodes/GSOPs... GSOPs Discord Link:  https://discord.com/invite/BEm46CDjAg Video shown in Episode:  https://www.youtube.com/watch?v=5V7mBuVxlt4&t=0s

    ١ س ١ د

  8. ١٨‏/١٠‏/٢٠٢٤

    How to use SuperSplat for Gaussian Splatting Editing featuring Will Eastcott

    Join co-hosts Michael Rubloff and MrNeRF as they speak to the CEO of SuperSplat and PlayCanvas, Will Eastcott. SuperSplat is a cutting-edge editor that allows you to edit, crop, compress, merge, and more with your Gaussian Splatting captures. https://playcanvas.com/supersplat/editor

    ١ من الساعات
مشاهدة الكل (١٨)

التقييمات والمراجعات

حول

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.

المعلومات

  • صناع العمل
    View Dependent
  • سنوات النشاط
    ٢٠٢٣ - ٢٠٢٤
  • الحلقات
    ١٨
  • التقييم
    ملائم
  • حقوق النشر
    © View Dependent
  • موقع البرنامج على الويب
    View Dependent