690 citations · 1.5k across the 15 of their papers we have counts for
4 papers · 1 filter
KonVid-150k: A Dataset for No-Reference Video Quality Assessment of Videos in-the-Wild
Franz Götz-Hahn, Vlad Hosu, Hanhe Lin +1
Video quality assessment (VQA) methods focus on particular degradation types, usually artificially induced on a small set of reference videos. Hence, most traditional VQA methods u…
KonIQ-10k: An ecologically valid database for deep learning of blind image quality assessment
Vlad Hosu, Hanhe Lin, Tamas Sziranyi +1
Deep learning methods for image quality assessment (IQA) are limited due to the small size of existing datasets. Extensive datasets require substantial resources both for generatin…
Effective Aesthetics Prediction with Multi-level Spatially Pooled Features
Vlad Hosu, Bastian Goldlucke, Dietmar Saupe
We propose an effective deep learning approach to aesthetics quality assessment that relies on a new type of pre-trained features, and apply it to the AVA data set, the currently l…
Technical Report on Visual Quality Assessment for Frame Interpolation
Hui Men, Hanhe Lin, Vlad Hosu +3
Current benchmarks for optical flow algorithms evaluate the estimation quality by comparing their predicted flow field with the ground truth, and additionally may compare interpola…