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DTSTAMP:20240214T070243Z
LOCATION:Meeting Room C4.9+C4.10\, Level 4 (Convention Centre)
DTSTART;TZID=Australia/Melbourne:20231212T174000
DTEND;TZID=Australia/Melbourne:20231212T175000
UID:siggraphasia_SIGGRAPH Asia 2023_sess162_papers_350@linklings.com
SUMMARY:VMesh: Hybrid Volume-Mesh Representation for Efficient View Synthe
 sis
DESCRIPTION:Technical Papers\n\nYuan-Chen Guo (Tsinghua University, Tencen
 t); Yan-Pei Cao (Tencent); Chen Wang (Tsinghua University); Yu He (Chinese
  Academy of Sciences); Ying Shan (Tencent); and Song-Hai Zhang (Tsinghua U
 niversity)\n\nWith the emergence of neural radiance fields (NeRFs), view s
 ynthesis quality has reached an unprecedented level. Compared to tradition
 al mesh-based assets, this volumetric representation is more powerful in e
 xpressing scene geometry but inevitably suffers from high rendering costs 
 and can hardly be involved in further processes like editing, posing signi
 ficant difficulties in combination with the existing graphics pipeline. In
  this paper, we present a hybrid volume-mesh representation, VMesh, which 
 depicts an object with a textured mesh along with an auxiliary sparse volu
 me. VMesh retains the advantages of mesh-based assets, such as efficient r
 endering and compact storage, while also incorporating the ability to repr
 esent subtle geometric structures provided by the volumetric counterpart. 
 VMesh can be obtained from multi-view images of an object and renders at 2
 K 60FPS on common consumer devices with high fidelity, unleashing new oppo
 rtunities for real-time immersive applications.\n\nRegistration Category: 
 Full Access\n\nSession Chair: Binh-Son Hua (Trinity College Dublin)
URL:https://asia.siggraph.org/2023/full-program?id=papers_350&sess=sess162
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