Visual Quality Assessment Databases, MMSP Konstanz
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  • VQA Databases
    • KonViD-150k Database
    • KonViD-1k Database
    • KonIQ-10k Database
    • KonIQ++ Database
    • KADID-10k Database
    • IQA-Experts-300
    • KonPatch-30k Database
    • KoSMo-1k Database
    • StudyMB 2.0 Database
    • Picturewise JND Data
    • KonJND-1k database
    • KonFiG-IQA Database
    • GFIQA-20k Database
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Our group

The team 

Vlad Hosu
Mohsen Jenadeleh
Dietmar Saupe
Oliver Wiedemann
​github | project | uni-kn
uni-kn
uni-kn
github | personal | uni-kn

Previous members

Franz Hahn
Hanhe Lin
Hui Men
uni-kn
uni-kn
uni-kn
Picture

Goals

We design prediction algorithms for the visual quality of images and videos, with respect to technical and perceptual aspects e.g. quality of experience (QoE).
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​The tools of our trade include crowdsourcing, machine learning i.e. deep networks, eye-tracking. Consequently, we are creating massive multimedia databases that are suitable for training generic and accurate VQA models.
More details
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Copyright "VQA Group at Universität Konstanz" © 2019-2022
  • Home
  • VQA Databases
    • KonViD-150k Database
    • KonViD-1k Database
    • KonIQ-10k Database
    • KonIQ++ Database
    • KADID-10k Database
    • IQA-Experts-300
    • KonPatch-30k Database
    • KoSMo-1k Database
    • StudyMB 2.0 Database
    • Picturewise JND Data
    • KonJND-1k database
    • KonFiG-IQA Database
    • GFIQA-20k Database
  • About
  • Contact