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DTSTAMP:20240214T070244Z
LOCATION:Meeting Room C4.11\, Level 4 (Convention Centre)
DTSTART;TZID=Australia/Melbourne:20231213T140000
DTEND;TZID=Australia/Melbourne:20231213T141500
UID:siggraphasia_SIGGRAPH Asia 2023_sess128_papers_321@linklings.com
SUMMARY:Neural Field Convolutions by Repeated Differentiation
DESCRIPTION:Technical Papers\n\nNtumba Elie Nsampi, Adarsh Djeacoumar, and
  Hans-Peter Seidel (Max-Planck-Institut für Informatik); Tobias Ritschel (
 University College London (UCL)); and Thomas Leimkühler (Max-Planck-Instit
 ut für Informatik)\n\nNeural fields are evolving towards a general-purpose
  continuous representation for visual computing. Yet, despite their numero
 us appealing properties, they are hardly amenable to signal processing. As
  a remedy, we present a method to perform general continuous convolutions 
 with general continuous signals such as neural fields. Observing that piec
 ewise polynomial kernels reduce to a sparse set of Dirac deltas after repe
 ated differentiation, we leverage convolution identities and train a repea
 ted integral field to efficiently execute large-scale convolutions. We dem
 onstrate our approach on a variety of data modalities and spatially-varyin
 g kernels.\n\nRegistration Category: Full Access\n\nSession Chair: Jianfei
  Cai (Monash University)
URL:https://asia.siggraph.org/2023/full-program?id=papers_321&sess=sess128
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