• Skip navigation
  • Skip to navigation
  • Skip to the bottom
Simulate organization breadcrumb open Simulate organization breadcrumb close
Friedrich-Alexander-Universität Pattern Recognition Lab PRL
  • FAUTo the central FAU website
Suche öffnen
  • Campo
  • StudOn
  • FAUdir
  • Jobs
  • Map
  • Help
Friedrich-Alexander-Universität Pattern Recognition Lab PRL
Navigation Navigation close
  • Lab
    • News
    • Cooperations
    • Join the Pattern Recognition Lab
    • Ph.D. Gallery
    • Contact
    • Directions
  • Team
    • Our Team
    • Former PRL members
  • Research
    • Research Groups
    • Research Projects
    • Publications
    • Competitions
    • Datasets
    • Research Demo Videos
    • Pattern Recognition Blog
    • Beyond the Patterns
  • Teaching
    • Curriculum / Courses
    • Lecture Notes
    • Lecture Videos
    • LME Videos
    • Thesis / Projects
  1. Home
  2. Computational Two-Illuminant Datasets

Computational Two-Illuminant Datasets

Computational Two-Illuminant Datasets

Symbolic picture for the article. The link opens the image in a large view.
November 27, 2019

Obtaining quantitative ground truth for color constancy under multiple light sources is difficult. We provide two datasets of 58 and 20 images that are exposed to two illuminants. The ground truth is obtained from an algorithm that operates on multiple aligned input images.

Read more & download

Recent Posts

  • New PhD student: Karan Pahlajani joins the PRL
  • PhD Student of the Pattern Recognition Lab Featured by FOCUS
  • Pattern Recognition Lab Researchers Again Among World’s Top 2% Most-Cited Academics
  • DFG funds new project at the Pattern Recognition Lab on deep learning–based CBCT reconstruction
  • “(Dis)Honest Communication”: Tomás Arias Receives ISF-DFG Grant for Research on the Vocalizations of Rock Hyraxes

Categories

  • Competitions
  • Datasets
  • Lecture Notes
    • Lecture Notes in Deep Learning
    • Lecture Notes in Medical Engineering
    • Lecture Notes in Pattern Recognition
  • Lecture Videos
    • Deep Learning WS 20/21
    • Pattern Recognition WS 20/21
  • News
  • Pattern Recognition Blog
  • Ph.D. Gallery
  • Research Demo Videos
  • Uncategorized
Friedrich-Alexander-Universität Erlangen-Nürnberg
Lehrstuhl für Mustererkennung (Informatik 5)

Martensstr. 3
91058 Erlangen
  • Contact
  • Login
  • Intranet
  • Imprint
  • Privacy
  • Accessibility
  • RSS Feed
  • Instagram
  • TikTok
  • Mastodon
  • BlueSky
  • YouTube
  • Facebook
  • Xing
  • LinkedIn
  • Community
  • Threads
Up