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DTSTAMP:20240214T070245Z
LOCATION:Meeting Room C4.11\, Level 4 (Convention Centre)
DTSTART;TZID=Australia/Melbourne:20231213T171600
DTEND;TZID=Australia/Melbourne:20231213T173100
UID:siggraphasia_SIGGRAPH Asia 2023_sess153_papers_480@linklings.com
SUMMARY:A Neural Implicit Representation for the Image Stack: Depth, All i
 n Focus, and High Dynamic Range
DESCRIPTION:Technical Communications, Technical Papers\n\nChao Wang (Max-P
 lanck-Institut für Informatik); Ana Serrano (Universidad de Zaragoza); and
  Xingang Pan, Bin Chen, Hans-Peter Seidel, Karol Myszkowski, Christian The
 obalt, Krzysztof Wolski, and Thomas Leimkühler (Max-Planck-Institut für In
 formatik)\n\nIn everyday photography, physical limitations of camera senso
 rs and lenses frequently lead to a variety of degradations in captured ima
 ges such as saturation or defocus blur. A common approach to overcome thes
 e limitations is to resort to image stack fusion, which involves capturing
  multiple images with different focal distances or exposures. For instance
 , to obtain an all-in-focus image, a set of multi-focus images is captured
 . Similarly, capturing multiple exposures allows for the reconstruction of
  high dynamic range (HDR).\nIn this paper, we present a novel approach tha
 t combines neural fields with an expressive camera model to achieve a unif
 ied reconstruction of an all-in-focus HDR image from an image stack. \nOur
  approach is composed of a set of specialized neural fields tailored to ad
 dress specific sub-problems along our pipeline:\nWe use fields to predict 
 flow to overcome misalignments arising from lens breathing, depth and all-
 in-focus images to account for depth of field, as well as tonemapping to d
 eal with sensor responses and saturation -- all trained using a physically
  inspired supervision structure with a differentiable thin lens model at i
 ts core.\nAn important benefit of our approach is its ability to handle th
 ese tasks simultaneously or independently, providing flexible post-editing
  capabilities such as refocusing and exposure adjustment.\nBy sampling the
  three primary factors in photography within our framework (focal distance
 , aperture, and exposure time), we conduct a thorough exploration to gain 
 valuable insights into their significance and impact on the overall image 
 quality. \nThrough extensive validation, we demonstrate that our method ou
 tperforms existing approaches in both depth-from-defocus and all-in-focus 
 image reconstruction tasks. Moreover, our approach exhibits promising resu
 lts in each of these three dimensions, showcasing its potential to enhance
  captured image quality and provide greater control in post-processing.\n\
 nRegistration Category: Full Access\n\nSession Chair: Jonah Brucker-Cohen 
 (Lehman College / CUNY, New Inc.)
URL:https://asia.siggraph.org/2023/full-program?id=papers_480&sess=sess153
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