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BEGIN:VEVENT
DTSTAMP:20260805T205559Z
LOCATION:Room 408 B
DTSTART;TZID=America/Los_Angeles:20260722T113500
DTEND;TZID=America/Los_Angeles:20260722T114500
UID:siggraph_SIGGRAPH 2026_sess153_paperstog_118@linklings.com
SUMMARY:Resolution Where It Counts: Hash-based GPU-Accelerated 3D Reconstr
 uction via Variance-Adaptive Voxel Grids
DESCRIPTION:Lorenzo De Rebotti, Emanuele Giacomini, Giorgio Grisetti, and 
 Luca Di Giammarino (University of Rome La Sapienza) and Lorenzo De Rebotti
 \n\nWe propose a variance-adaptive voxel grid that adjusts size based on l
 ocal SDF variance. Using a flat spatial hash table, it achieves constant-t
 ime access, memory efficiency, and full GPU parallelism. Additionally, a p
 arallel quad-tree structure supports GPU-accelerated Gaussian Splatting re
 ndering, enabling effective control over splat density.\n\nInterest Area: 
 Research & Education\n\nKeyword: Artificial Intelligence/Machine Learning,
  Generative AI, Geometry, Modeling, Rendering, Simulation\n\nRegistration 
 Category: Full Conference Supporter, Full Conference\n\nSession Chair: Ode
 d Stein (Technion, University of Southern California)\n\n
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