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TZID:Asia/Seoul
X-LIC-LOCATION:Asia/Seoul
BEGIN:STANDARD
TZOFFSETFROM:+0900
TZOFFSETTO:+0900
TZNAME:KST
DTSTART:18871231T000000
DTSTART:19881009T020000
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BEGIN:VEVENT
DTSTAMP:20230103T035346Z
LOCATION:Room 325-AB\, Level 3\, West Wing
DTSTART;TZID=Asia/Seoul:20221206T140000
DTEND;TZID=Asia/Seoul:20221206T153000
UID:siggraphasia_SIGGRAPH Asia 2022_sess156@linklings.com
SUMMARY:Distances and Matching
DESCRIPTION:Technical Communications, Technical Papers, TOG\n\nThe present
 ations will be followed by a 30-min Interactive Discussion Session at Room
  325-CD.\n\nThe Technical Papers program is the premier international foru
 m for disseminating new scholarly work in computer graphics and interactiv
 e techniques. Technical Papers are published as a special issue of ACM Tra
 nsactions on Graphics. In addition to papers selected by the SIGGRAPH Asia
  2022 Technical Papers Jury, the conference presents papers that have been
  published in ACM Transactions on Graphics during the past year. Accepted 
 papers adhere to the highest scientific standards.\n\nThe Technical Commun
 ications program is a premier forum for presenting the latest developments
  and research still in progress. Leading international experts in academia
  and industry present work that showcase actual implementations of researc
 h ideas, works at the crossroads of computer graphics with computer vision
 , machine learning, HCI, VR, CAD, visualization, and many others\n\nSurfac
 eVoronoi: Efficiently Computing Voronoi Diagrams Over Mesh Surfaces with A
 rbitrary Distance Solvers\n\nXin, Wang, Xu, Yan, Chen...\n\nIn this paper,
  we propose to compute Voronoi diagrams over mesh surfaces driven by an ar
 bitrary geodesic distance solver, assuming that the input is a triangle me
 sh as well as a collection of sites mathbf{P}={p_i}_{i=1}^m on the surface
 . We propose two key techniques to solve this problem. First, as...\n\n---
 ------------------\nSHRED: 3D Shape Region Decomposition with Learned Loca
 l Operations\n\nJones, Habib, Ritchie\n\nWe present SHRED, a method for 3D
  SHape REgion Decomposition. SHRED takes a 3D point cloud as input and use
 s learned local operations to produce a segmentation that approximates fin
 e-grained part instances. We endow SHRED with three decomposition operatio
 ns: splitting regions, fixing the boundaries ...\n\n---------------------\
 nComputing Medial Axis Transform with Feature Preservation via Restricted 
 Power Diagram\n\nWang, Wang, Wang, Guo\n\nWe propose a novel framework for
  computing the medial axis transform of 3D shapes while preserving their m
 edial features via restricted power diagram (RPD). Medial features, includ
 ing external features such as the sharp edges and corners of the input mes
 h surface and internal features such as the se...\n\n---------------------
 \n3QNet: 3D Point Cloud Geometry Quantization Compression Network\n\nHuang
 , zhang, Chen, Ding, Tai...\n\nSince the development of 3D applications, t
 he point cloud, as a spatial description easily acquired by sensors, has b
 een widely used in multiple areas such as SLAM and 3D reconstruction. Poin
 t Cloud Compression (PCC) has also attracted more attention as a primary s
 tep before point cloud transferring...\n\n---------------------\nDiscretiz
 ation-Agnostic Deep Self-Supervised 3D Surface Parameterization\n\nPokhari
 ya, Naik, Srivastava, Sharma\n\nWe present a novel, self-supervised framew
 ork for learning the discretization-agnostic surface parameterization of a
 rbitrary 3D objects with both bounded and unbounded surfaces.\n\n---------
 ------------\nCompressing Geodesic Information for Fast Point-to-Point Geo
 desic Distance Queries\n\nGotsman, Hormann\n\nGeodesic distances between p
 airs of points on a 3D mesh surface are a crucial ingredient of many geome
 try processing tasks, but are notoriously difficult to compute efficiently
  on demand. We propose a novel method for the compact storage of geodesic 
 distance information, which enables answering poin...\n\n-----------------
 ----\nAugmented Paths and Reodesics for Topologically-Stable Matching\n\nS
 ahillioğlu, Horsman\n\nWe present a fully-automatic 3D isometric shape cor
 respondence method that computes point-to-point dense correspondences in t
 he presence of topological noise. In order to make this process work well,
  we introduce two novel concepts: path augmentation with heat vectors and 
 robust geodesics, reodesics...\n\n\nRegistration Category: FULL ACCESS, ON
 -DEMAND ACCESS\n\nLanguage: ENGLISH\n\nFormat: IN-PERSON, ON-DEMAND
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