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  • Prefiltering YFCC100M dataset.
  • Computing different attributes on the filtered dataset, uniform sampling 10,000 images using those attributes. 
  • Subjective study on the 10,000 images by crowdsouring.
  • Collect existing IQA algorithms and compare their performance on the database.


  • Basic math skills are required.
  • Basic programming skills, e.g., Matlab, C/C++, or Python.
  • Some statistical knowledge is a plus.


  1. Winkler, Stefan. "Analysis of public image and video databases for quality assessment." IEEE Journal of Selected Topics in Signal Processing 6.6 (2012): 616-625.
  2. Ghadiyaram, Deepti, and Alan C. Bovik. "Massive online crowdsourced study of subjective and objective picture quality." IEEE Transactions on Image Processing 25.1 (2016): 372-387.