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DTSTAMP:20240214T070250Z
LOCATION:Meeting Room C4.8\, Level 4 (Convention Centre)
DTSTART;TZID=Australia/Melbourne:20231215T114000
DTEND;TZID=Australia/Melbourne:20231215T115500
UID:siggraphasia_SIGGRAPH Asia 2023_sess156_papers_442@linklings.com
SUMMARY:Efficient Hybrid Zoom using Camera Fusion on Mobile Phones
DESCRIPTION:Technical Communications, Technical Papers\n\nXiaotong Wu, Wei
 -Sheng Lai, and Yichang Shih (Google Inc.); Charles Herrmann and Michael K
 rainin (Google Research); Deqing Sun (Google); and Chia-Kai Liang (Google 
 Inc.)\n\nDSLR cameras can achieve multiple zoom levels via shifting lens d
 istances or swapping lens types. However, these techniques are not possibl
 e on smartphone devices due to space constraints. Most smartphone manufact
 urers adopt a hybrid zoom system: commonly a Wide (W) camera at a low zoom
  level and a Telephoto (T) camera at a high zoom level. To simulate zoom l
 evels between W and T, these systems crop and digitally upsample images fr
 om W, leading to significant detail loss. In this paper, we propose an eff
 icient system for hybrid zoom super-resolution on mobile devices, which ca
 ptures a synchronous pair of W and T shots and leverages machine learning 
 models to align and transfer details from T to W. We further develop an ad
 aptive blending method that accounts for depth-of-field mismatches, scene 
 occlusion, flow uncertainty, and alignment errors. To minimize the domain 
 gap, we design a dual-phone camera rig to capture real-world inputs and gr
 ound-truths for supervised training. Our method generates a 12-megapixel i
 mage in 500ms on a mobile platform and compares favorably against state-of
 -the-art methods under extensive evaluation on real-world scenarios.\n\nRe
 gistration Category: Full Access\n\nSession Chair: Sergi Pujades (National
  Institute for Research in Computer Science and Automation (INRIA), Univer
 sité Grenoble Alpes)
URL:https://asia.siggraph.org/2023/full-program?id=papers_442&sess=sess156
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