NIMA: Neural image assessment
H Talebi, P Milanfar - IEEE transactions on image processing, 2018 - ieeexplore.ieee.org
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 …
its usefulness in a wide variety of applications, such as evaluating image capture pipelines …
A reference-free underwater image quality assessment metric in frequency domain
Owing to the complexity of the underwater environment and the limitations of imaging
devices, the quality of underwater images varies differently, which may affect the practical …
devices, the quality of underwater images varies differently, which may affect the practical …
Personality-assisted multi-task learning for generic and personalized image aesthetics assessment
Traditional image aesthetics assessment (IAA) approaches mainly predict the average
aesthetic score of an image. However, people tend to have different tastes on image …
aesthetic score of an image. However, people tend to have different tastes on image …
A unified probabilistic formulation of image aesthetic assessment
Image aesthetic assessment (IAA) has been attracting considerable attention in recent years
due to the explosive growth of digital photography in Internet and social networks. The IAA …
due to the explosive growth of digital photography in Internet and social networks. The IAA …
Advances and challenges in computational image aesthetics
Computational image aesthetics aims at designing algorithmic approaches to perform
aesthetic decisions, in a similar fashion as humans. In the past fifteen years, computational …
aesthetic decisions, in a similar fashion as humans. In the past fifteen years, computational …
A gated peripheral-foveal convolutional neural network for unified image aesthetic prediction
Learning fine-grained details is a key issue in image aesthetic assessment. Most of the
previous methods extract the fine-grained details via random cropping strategy, which may …
previous methods extract the fine-grained details via random cropping strategy, which may …
Learned perceptual image enhancement
H Talebi, P Milanfar - 2018 IEEE international conference on …, 2018 - ieeexplore.ieee.org
Learning a typical image enhancement pipeline involves minimization of a loss function
between enhanced and reference images. While L 1 and L 2 losses are perhaps the most …
between enhanced and reference images. While L 1 and L 2 losses are perhaps the most …
A comprehensive survey on image aesthetic quality assessment
H Yang, P Shi, S He, D Pan, Z Ying… - 2019 IEEE/ACIS 18th …, 2019 - ieeexplore.ieee.org
Image aesthetic quality assessment has demonstrated tremendous success in variety of
application domains in recent years. This field has been growing so rapidly that various …
application domains in recent years. This field has been growing so rapidly that various …
Beyond vision: A multimodal recurrent attention convolutional neural network for unified image aesthetic prediction tasks
Over the past few years, image aesthetic prediction has attracted increasing attention
because of its wide applications, such as image retrieval, photo album management and …
because of its wide applications, such as image retrieval, photo album management and …
User-guided personalized image aesthetic assessment based on deep reinforcement learning
Personalized image aesthetic assessment (PIAA) has recently become a hot topic due to its
wide applications, such as photography, film, television, e-commerce, fashion design, and …
wide applications, such as photography, film, television, e-commerce, fashion design, and …