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DTSTAMP:20240214T070241Z
LOCATION:Darling Harbour Theatre\, Level 2 (Convention Centre)
DTSTART;TZID=Australia/Melbourne:20231212T093000
DTEND;TZID=Australia/Melbourne:20231212T124500
UID:siggraphasia_SIGGRAPH Asia 2023_sess209_papers_442@linklings.com
SUMMARY:Efficient Hybrid Zoom using Camera Fusion on Mobile Phones
DESCRIPTION:Technical Papers\n\nXiaotong Wu, Wei-Sheng Lai, and Yichang Sh
 ih (Google Inc.); Charles Herrmann and Michael Krainin (Google Research); 
 Deqing Sun (Google); and Chia-Kai Liang (Google Inc.)\n\nDSLR cameras can 
 achieve multiple zoom levels via shifting lens distances or swapping lens 
 types. However, these techniques are not possible on smartphone devices du
 e to space constraints. Most smartphone manufacturers 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 levels between W and T, the
 se systems crop and digitally upsample images from W, leading to significa
 nt detail loss. In this paper, we propose an efficient system for hybrid z
 oom super-resolution on mobile devices, which captures a synchronous pair 
 of W and T shots and leverages machine learning models to align and transf
 er details from T to W. We further develop an adaptive blending method tha
 t accounts for depth-of-field mismatches, scene occlusion, flow uncertaint
 y, and alignment errors. To minimize the domain gap, we design a dual-phon
 e camera rig to capture real-world inputs and ground-truths for supervised
  training. Our method generates a 12-megapixel image in 500ms on a mobile 
 platform and compares favorably against state-of-the-art methods under ext
 ensive evaluation on real-world scenarios.\n\nRegistration Category: Full 
 Access, Enhanced Access, Trade Exhibitor, Experience Hall Exhibitor
URL:https://asia.siggraph.org/2023/full-program?id=papers_442&sess=sess209
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