Automatic assessment of aesthetic-related subjective ratings.
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Automatically learned quality assessment for images has recently become a hot topic due to its usefulness in a wide variety of applications such as evaluating image capture pipelines, storage techniques and sharing media.
#4 best model for Aesthetics Quality Assessment on AVA
In this work, we propose to learn a deep convolutional neural network to rank photo aesthetics in which the relative ranking of photo aesthetics are directly modeled in the loss function.
#7 best model for Aesthetics Quality Assessment on AVA
Aggregation structures with explicit information, such as image attributes and scene semantics, are effective and popular for intelligent systems for assessing aesthetics of visual data.
SOTA for Aesthetics Quality Assessment on AVA
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 largest aesthetics database.
#3 best model for Aesthetics Quality Assessment on AVA