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Behaviour of Recent Aesthetics Assessment Models with Professional Photography

Abstract : Aesthetic quality assessment for photographs is an important research topic since it can be used by a number of applications, such as image database management or image browsing. In 2012, the Aesthetic Visual Analysis (AVA) dataset has been proposed. Those 255,000 aesthetically annotated images are a key ingredient for training and for testing new models for aesthetics prediction. As AVA dataset is mainly composed of competitive photographs, we evaluate whether or not those computational models of aesthetics generalize well and perform well over professional photographs. We notice that the different models we test behave quite differently. Besides, we fine-tune the model using professional photographs and the results show that this process is effective.
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Contributor : Mathieu Chambe Connect in order to contact the contributor
Submitted on : Thursday, November 21, 2019 - 3:09:33 PM
Last modification on : Friday, April 8, 2022 - 4:08:03 PM


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  • HAL Id : hal-02374494, version 1


Mathieu Chambe, Rémi Cozot, Olivier Le Meur. Behaviour of Recent Aesthetics Assessment Models with Professional Photography. 2019. ⟨hal-02374494⟩



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