arXiv Artificial Intelligence

SloMoDeblur: A Large-Scale Smartphone Image Deblurring Dataset

1 hour ago 11.09.2026 07:00 👁 2 views
SloMoDeblur: A Large-Scale Smartphone Image Deblurring Dataset

Quick summary

arXiv:2506.19445v5 Announce Type: replace-cross Abstract: Motion blur remains one of the most common and visually disruptive degradations in real-world smartphone imaging, yet existing deblurring benchmarks are often limited in scale, resolution, or domain relevance. This gap is especially pronounced for smartphones, where rolling shutter, small sensors, and ISP processing produce blur statistics that differ from GoPro/DSLR-based benchmarks. We introduce a large-scale smartphone-oriented deblurring dataset constructed from 240~fps slow-motion video. To approximate exposure-time radiance integr

Key takeaways

  • arXiv:2506.19445v5 Announce Type: replace-cross Abstract: Motion blur remains one of the most common and visually disruptive degradations in real-world smartphone imaging, yet existing deblurring benchmarks are often limited in scale, resolution, or domain relevance.
  • This gap is especially pronounced for smartphones, where rolling shutter, small sensors, and ISP processing produce blur statistics that differ from GoPro/DSLR-based benchmarks.
  • We introduce a large-scale smartphone-oriented deblurring dataset constructed from 240~fps slow-motion video.

Why it matters

The importance of “SloMoDeblur: A Large-Scale Smartphone Image Deblurring Dataset” will be measured by what changes in practice. User behavior, access conditions, verifiable performance and responsible-use outcomes are the signals worth following.

Kaynak sitede devamını oku: arXiv Artificial Intelligence ↗