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BEGIN:VEVENT
DTSTAMP:20240214T070311Z
LOCATION:Meeting Room C4.11\, Level 4 (Convention Centre)
DTSTART;TZID=Australia/Melbourne:20231214T140000
DTEND;TZID=Australia/Melbourne:20231214T150000
UID:siggraphasia_SIGGRAPH Asia 2023_sess130@linklings.com
SUMMARY:Reconstruction
DESCRIPTION:Technical Papers\n\nNeural Stochastic Poisson Surface Reconstr
 uction\n\nReconstructing a surface from a point cloud is an underdetermine
 d problem. We propose using a neural network to study and quantify this re
 construction uncertainty under a Poisson smoothness prior. Our algorithm a
 ddresses the main limitations of existing work and can be fully integrated
  into the 3D s...\n\n\nSilvia Sellán (University of Toronto) and Alec Jaco
 bson (University of Toronto, Adobe Research)\n---------------------\nRobus
 t Zero Level-Set Extraction from Unsigned Distance Fields Based on Double 
 Covering\n\nIn this paper, we propose a new method, called DoubleCoverUDF,
  for extracting the zero level-set from unsigned distance fields (UDFs). D
 oubleCoverUDF takes a learned UDF and a user-specified parameter r (a smal
 l positive real number) as input and extracts an iso-surface with an iso-v
 alue r using the...\n\n\nFei Hou (Institute of Software, Chinese Academy o
 f Sciences; University of Chinese Academy of Sciences); Xuhui Chen and Wen
 cheng Wang (Institute of Software, Chinese Academy Of Sciences; University
  of Chinese Academy of Sciences); Hong Qin (Stony Brook University); and Y
 ing He (Nanyang Technological University)\n---------------------\nReach Fo
 r the Spheres: Tangency-aware surface reconstruction of SDFs\n\nSigned dis
 tance fields (SDFs) are a widely utilized implicit surface representation 
 that has applications in various fields such as computer graphics, compute
 r vision, and applied mathematics. Despite their frequent use, traditional
  methods such as Marching Cubes and its variants often overlook fund...\n\
 n\nSilvia Sellán (University of Toronto), Christopher Batty (University of
  Waterloo), and Oded Stein (University of Southern California)\n----------
 -----------\nMIPS-Fusion: Multi-Implicit-Submaps for Scalable and Robust O
 nline Neural RGB-D Reconstruction\n\nWe introduce MIPS-Fusion, a robust an
 d scalable online RGB-D reconstruction method based on a novel neural impl
 icit representation -- multi-implicit-submap. Different from existing neur
 al RGB-D reconstruction methods lacking either flexibility with a single n
 eural map or scalability due to extra sto...\n\n\nYijie Tang (National Uni
 versity of Defense Technology (NUDT)), Jiazhao Zhang (Peking University), 
 Zhinan Yu (National University of Defense Technology (NUDT)), He Wang (Pek
 ing University), and Kai Xu (National University of Defense Technology (NU
 DT))\n---------------------\n360° Reconstruction From a Single Image Using
  Space Carved Outpainting\n\nWe introduce POP3D, a novel framework that cr
 eates a full $360^\circ$-view 3D model from a single image. POP3D resolves
  two prominent issues that limit the single-view reconstruction. Firstly, 
 POP3D offers substantial generalizability to arbitrary categories, a trait
  that previous methods struggle t...\n\n\nNuri Ryu, Minsu Gong, and Geonun
 g Kim (POSTECH); Joo-Haeng Lee (Pebblous Inc.); and Sunghyun Cho (POSTECH,
  Pebblous Inc.)\n\nRegistration Category: Full Access\n\nSession Chair: Ba
 oquan Chen (Peking University)
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