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TZID:Asia/Seoul
X-LIC-LOCATION:Asia/Seoul
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DTSTART:18871231T000000
DTSTART:19881009T020000
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BEGIN:VEVENT
DTSTAMP:20230103T035306Z
LOCATION:Auditorium\, Level 5\, West Wing
DTSTART;TZID=Asia/Seoul:20221206T100000
DTEND;TZID=Asia/Seoul:20221206T120000
UID:siggraphasia_SIGGRAPH Asia 2022_sess153_papers_560@linklings.com
SUMMARY:Depth of Field Aware Differentiable Rendering
DESCRIPTION:Technical Papers\n\nDepth of Field Aware Differentiable Render
 ing\n\nPidhorskyi, Bagautdinov, Ma, Saragih, Schwartz...\n\nCameras with a
  finite aperture diameter exhibit defocus for scene elements that are not 
 at the focus distance and have only a limited depth of field within which 
 objects appear acceptably sharp. In this work, we address the problem of a
 pplying inverse rendering techniques to input data that exhibits such defo
 cus blurring. We present differentiable depth-of-field rendering technique
 s that are applicable to both rasterization-based methods using mesh repre
 sentations, as well as ray-marching-based methods using volumetric radianc
 e fields. Our approach learns significantly sharper scene reconstructions 
 on data containing blur due to depth of field and recovers aperture and fo
 cus distance parameters that result in plausible forward-rendered images. 
 We show applications to macro photography, where typical lens configuratio
 ns result in a very narrow depth of field, and to multi-camera video captu
 re, where maintaining sharp focus across a large capture volume for a movi
 ng subject is difficult.\n\nRegistration Category: FULL ACCESS, EXPERIENCE
  PLUS ACCESS, EXPERIENCE ACCESS, TRADE EXHIBITOR\n\nLanguage: ENGLISH\n\nF
 ormat: IN-PERSON
URL:https://sa2022.siggraph.org/en/full-program/?id=papers_560&sess=sess15
 3
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