8/n Huge thanks to my co-authors
@antoine-guedon.bsky.social, Nissim Maruani, @s2.hk, and Maks Ovsjanikov, the supporting institutions, and to the "Objects as Volumes" team for the inspiring framework! 🙏
Check out the full paper and code here:
diego1401.github.io/BlobsToSpoke...
7/n Primal Adaptive Meshing (PAM)🕸️
Standard meshing ties vertices to Gaussian positions, so resolution is stuck.
PAM fully decouples mesh resolution from the Gaussians, enabling region-of-interest meshing at arbitrary resolution. 🚀
6/n 🛡️How do we ensure no gaps?
Two complementary mechanisms:
1️⃣ Normal alignment loss: aligns rendered normals with image-space depth gradients.
2️⃣ Normal-aware densification: detects gaps in the shell, clones Gaussians with flipped normals, and closes the holes.