Performance results of various VQA algorithms on KoNViD-1k.

The data is taken from the references listed in the second column. In the upper half, the first column gives the abbreviated name of the algorithm. The lower half denotes the base architecture used to extract features (column ‘base’) and the model used to predict the overall quality (column ‘pred’). The last two columns designate whether fine-tuning (column ‘ft’) was performed correctly (green checkmark), or with data leakage (red cross), and whether the test set (column ‘test’) was independent (green checkmark) or tainted (red cross). The two approaches indicated by * were published after the referenced publication and are current state-of-the-art. –.–– indicates unreported values. The numbers in bold font in lines 15 and 20 give the true performance of CNN-SVR and CNN-LSTM, much below the claimed performance.