TADAC:Text Annotated Distortion, Appearance and Content

In order to train the joint contrastive representation learning module, we constructe a large Text Annotated Distortion, Appearance and Content (TADAC) image database. We collect images with both synthetic distortions and authentic distortions from multiple image databases.Each image in TADAC is annotated with three types of textual descriptions indicating the semantic contents, the distortion characteristics and the appearance properties respectively.For image content description text,we adpot the textual template format of A photo of a(n) {s},where {s} is given by the scene label or object label of the image.For synthetic distorction images,we design a list of phrases describing distortion types and another list of adjectives, adverbs, and quantifiers describing the degree of distortions.For authentic distorction, we design appearance characteristics based on 4 quality relevant aspects:brightness,contrast,sharpness and colorfulness.We constructe a database containing images of diverse contents, a variety of distortions and rich appearances.Importantly, these images are annotated with texts describing their semantic contents, distortion charactistics and appearance propertities.These texts can represent quality relevant high level knowledge.The database can be used in other contexts and will be particularly useful for developing IQA applications