A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Filters
Survey: Deep Learning for Video Aesthetics
2019
International Journal for Research in Applied Science and Engineering Technology
Preserved Fulltext
Aesthetics is defined by the properties of arts and beauty. In our day to day lives with the increase of multimedia requirements the aesthetic sense of images and videos has gained much importance. ...
In this paper, we review the deep learning techniques which effectively automate the video and image aesthetics analysis. ...
And the high level properties are the photographic rules, mainly comprising of the Rules Of Thirds (RoT), Visual Balance (VB), Diagonal Dominance (DD), Simplicity and the Depth of Field (DoF) [3] . ...
doi:10.22214/ijraset.2019.2021
fatcat:yyxhlh6jcnaiba3k233etf42ly
RAPID
2014
Proceedings of the ACM International Conference on Multimedia - MM '14
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2015; you can also visit the original URL.
The file type is application/pdf.
deep convolutional neural network. ...
We present the RAPID (RAting PIctorial aesthetics using Deep learning) system, which adopts a novel deep neural network approach to enable automatic feature learning. ...
photographic rules such as the rule of thirds. ...
doi:10.1145/2647868.2654927
dblp:conf/mm/LuLJYW14
fatcat:3auap2hjazgetj2pqsdlxkkwja
A Survey on Image Aesthetic Assessment
[article]
2022
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Other Versions
This article presents a review of the contemporary automatic image aesthetics assessment techniques. ...
The categorization is usually done by analyzing an input image and computing some measure of the degree to which the image adheres to the fundamental principles of photography such as balance, rhythm, ...
fields, and rule of thirds. ...
arXiv:2103.11616v2
fatcat:4zwjch6vajetrnfd65hnjehegi
Composition-Preserving Deep Photo Aesthetics Assessment
2016
2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2016; you can also visit the original URL.
The file type is application/pdf.
Photo aesthetics assessment is challenging. Deep convolutional neural network (ConvNet) methods have recently shown promising results for aesthetics assessment. ...
The performance of these deep ConvNet methods, however, is often compromised by the constraint that the neural network only takes the fixed-size input. ...
This work was supported by NSF IIS-1321119 and CNS-1218589. ...
doi:10.1109/cvpr.2016.60
dblp:conf/cvpr/MaiJL16
fatcat:hmuvxwqfcfdozmdbql7bm4nf24
A-Lamp: Adaptive Layout-Aware Multi-Patch Deep Convolutional Neural Network for Photo Aesthetic Assessment
[article]
2017
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Deep convolutional neural networks (CNN) have recently been shown to generate promising results for aesthetics assessment. ...
Thus the aesthetics of the original images is impaired because of potential loss of fine grained details and holistic image layout. ...
photography composition guidelines, such as visual balance, rule of thirds, golden ratio, and diagonal dominance. ...
arXiv:1704.00248v1
fatcat:vnigeoizkfcmxfqxc4dk72zl3i
A-Lamp: Adaptive Layout-Aware Multi-patch Deep Convolutional Neural Network for Photo Aesthetic Assessment
2017
2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Deep convolutional neural networks (CNN) have recently been shown to generate promising results for aesthetics assessment. ...
Thus the aesthetics of the original images is impaired because of potential loss of fine grained details and holistic image layout. ...
photography composition guidelines, such as visual balance, rule of thirds, golden ratio, and diagonal dominance. ...
doi:10.1109/cvpr.2017.84
dblp:conf/cvpr/MaLC17
fatcat:brvylnil7zd6xogxycbiuq7zrq
Deep image aesthetics classification using inception modules and fine-tuning connected layer
2016
2016 8th International Conference on Wireless Communications & Signal Processing (WCSP)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2016; you can also visit the original URL.
The file type is application/pdf.
Deep convolutional neural network (DCNN) methods have recently shown promising results for image aesthetics assessment. ...
Besides, we use a pre-trained image classification CNN called GoogLeNet on the ImageNet dataset and fine tune our connected local and global layer on the large scale aesthetics assessment AVA dataset [ ...
rule of third, visual balance, rule of simplicity [3] , [4] , [5] , [6] , [7] , [8] , [9] , [10] , [11] , [12] , [13] , [14] , [15] , [16] , [17] , [18] , [19] , [20] . ...
doi:10.1109/wcsp.2016.7752571
dblp:conf/wcsp/JinCPTYL16
fatcat:x3wudxw6cffonem5c4fl5aty4i
A Gated Peripheral-Foveal Convolutional Neural Network for Unified Image Aesthetic Prediction
[article]
2019
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
Note that this fulltext copy is not of the "primary" version of this work. The version it corresponds to is:
2018 pre-print arXiv:1812.07989v1 fatcat:3rrs346axnhqfioufwossi5gr4
The peripheral vision is used for perceiving the broad spatial scene and selecting the attended regions for the fovea. ...
It is a dedicated double-subnet neural network, i.e. a peripheral subnet and a foveal subnet. ...
Early attempts in this area focus on handcrafted features which are based on the known aesthetic principles such as the rule-of-thirds, simplicity or diagonal rules [5] - [9] . ...
arXiv:1812.07989v2
fatcat:6qvnf6ex6nd4fesdiccndf43jq
A Novel Feature Fusion Method for Computing Image Aesthetic Quality
2020
IEEE Access
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
INDEX TERMS Deep convolutional neural networks, feature fusion, handcrafted aesthetic features, image aesthetics quality assessment. ...
The lower stream of the network consists of the proposed algorithms for handcrafted extracting aesthetic features and multiple convolution layers to extract the aesthetic features. ...
Aes_Stage_1, Aes_Stage_2 and Aes_Stage_3 are used to extract deep aesthetic features. The extraction of deep features makes up for the lack of handcrafted algorithms. ...
doi:10.1109/access.2020.2983725
fatcat:emz5q4sajve3lpeo2okcdvzlti
Analysis and Importance of Deep Learning for Video Aesthetic Assessments
2019
International Journal of Scientific Research in Computer Science Engineering and Information Technology
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Visual aesthetic typically: Remember what they see, understand and learn rather than what they hear. This paper principally emphasizes deep learning on basics of automatic video aesthetic assessments. ...
Deep Learning is one of the active analysis topic obtaining a great deal of analysis attention recently. ...
And the
high level properties are the photographic rules,
mainly comprising of the Rules of Thirds (RoT),
Visual Balance (VB), Diagonal Dominance (DD),
Simplicity and the Depth of Field (DoF) [7 ...
doi:10.32628/cseit1951100
fatcat:otq2ucutdfgk3hiigsb3ffszzy
A Comprehensive Survey on Computational Aesthetic Evaluation of Visual Art Images: Metrics and Challenges
2021
IEEE Access
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Besides, we systematically evaluate recent deep learning techniques that are useful for developing robust models for aesthetic prediction tasks in scoring, distribution, attribute, and description. ...
Computational image aesthetic evaluation is a computable human aesthetic perception and judgment realized by machines, which has a significant impact on a variety of applications such as image advanced ...
INTERPRETABILITY OF DEEP AESTHETIC ASSESSMENT MODELS At present, the mainstream technique used in image aesthetic evaluation is the deep neural network, which shows outperformed performance than the previous ...
doi:10.1109/access.2021.3083075
fatcat:zukn4uhlinejjdubdezsdghh5i
Image Aesthetic Assessment Assisted by Attributes through Adversarial Learning
2019
PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
The inherent connections among aesthetic attributes and aesthetics are crucial for image aesthetic assessment, but have not been thoroughly explored yet. ...
The multi-task deep network wants to output aesthetic score and attributes as close to the ground truth labels as possible. Thus the deep network and the discriminator compete with each other. ...
Acknowledgments This work was supported in part by the Project from Anhui Science and Technology Agency under Grant 1508085SMF223, and the National Nature Science Foundation of China under Grant 61473270 ...
doi:10.1609/aaai.v33i01.3301679
fatcat:k5nahkv2snbpjfgcgma75t47fu
Image aesthetic assessment via deep semantic aggregation
2016
2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Aesthetic quality estimation of an image is a challenging task. In this paper, we introduce a deep CNN approach to tackle this problem. ...
The networks capable of dealing with these high-level concepts are then fused by a learned logical connector for predicting the aesthetic rating. ...
Most of the researches focus on designing aesthetic features, e.g., the rule of thirds, sky illumination, simplicity, etc. ...
doi:10.1109/globalsip.2016.7905838
dblp:conf/globalsip/LuCC16
fatcat:enfrfslhwfbt5njxxwkkxen5iu
Measuring Photography Aesthetics with Deep CNNs
2020
IET Image Processing
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
The proposed aesthetic features outperform the state-of-art methods especially for Rule of Thirds attribute. ...
We propose a multi-task deep CNN, that collectively learns aesthetic attributes alongwith a general aesthetic score for the photograph. ...
Acknowledgment The authors wish to thank NVIDIA for providing a Titan × GPU as a research grant, which is used in this research for experimentations. ...
doi:10.1049/iet-ipr.2019.1300
fatcat:qlhufps36rbopdx7kn3gmwqqoi
Inkthetics: A Comprehensive Computational Model for Aesthetic Evaluation of Chinese Ink Paintings
2020
IEEE Access
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Basic composition rules and examples. (a) Rule of thirds. ...
On this basis, we quantize the following several composition rules commonly-used in Chinese ink painting. Rule of thirds. ...
For more information, see https://creativecommons.org/licenses/by/4.0/ Area proportion of brush strokes in the whole image frame composition ...
doi:10.1109/access.2020.3044573
fatcat:f5pzql6yjnbaloorsguo5j5cxq
« Previous
Showing results 1 — 15 out of 1,803 results