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Episode 06: Julian Chibane, MPI-INF, on 3D reconstruction using implicit functions
Manage episode 289279641 series 2906499
Julian Chibane (Google Scholar) is a PhD student at the Real Virtual Humans group at the Max Planck Institute for Informatics in Germany. His recent work centers around intrinsic functions for 3D reconstruction.
Highlights from our conversation:
🖼 How, surprisingly, the IF-Net architecture learned reasonable representations of humans & objects without priors
🔢 A simple observation that led to Neural Unsigned Distance Fields, which handle 3D scenes without a clear inside vs. outside (most scenes!)
📚 Navigating open questions in 3D representation, and the importance of focusing on what's working
36 episodes
Manage episode 289279641 series 2906499
Julian Chibane (Google Scholar) is a PhD student at the Real Virtual Humans group at the Max Planck Institute for Informatics in Germany. His recent work centers around intrinsic functions for 3D reconstruction.
Highlights from our conversation:
🖼 How, surprisingly, the IF-Net architecture learned reasonable representations of humans & objects without priors
🔢 A simple observation that led to Neural Unsigned Distance Fields, which handle 3D scenes without a clear inside vs. outside (most scenes!)
📚 Navigating open questions in 3D representation, and the importance of focusing on what's working
36 episodes
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