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awesome-image-aesthetic-assessment's Introduction

Awesome Machine Learning for Image Aesthetic Assessment Resources

Awesome

We would like to maintain a list of resources that utilize machine learning technologies to solve image aesthetic assessment.

Maintained by members from UIBE: Lian Liu, Xiangyi Zhang, Yanghao Xing, Yufei Deng, Yifan Yang and Guolong Wang. We also thank all the advisers!

Thank you for the support of Thinklab.

1. Survey
2. Problems
2.1 General Image Aesthetic Assessment 2.2 Personalized Image Aesthetic Assessment
2.3 Aesthetic Critique 2.4 Dataset
2.5 Aesthetic Assessment in Downstream Tasks
  1. Image Aesthetic Assessment: An Experimental Survey. IEEE Signal Processing Magazine, 2017. journal

    Deng, Yubin and Loy, Chen Change and Tang, Xiaoou.

  2. Image Aesthetic Quality Assessment: A survey. (in chinese) 科技导报, 2018. journal

    Jin, Xin and Zhou, Bin and Zou, Dongqing, Li, Xiaodong, Sun, Hongbo and Wu, Le

  3. A Comprehensive Survey on Image Aesthetic Quality Assessment. IEEE/ACIS 18th International Conference on Computer and Information Science, 2019. paper

    Yang, Hongtao and Shi, Ping and He, Saike and Pan, Da and Ying, Zefeng and Lei, Ling.

  4. Survey of Application of Deep Convolution Neural Network in Image Aesthetic Evaluation. (in chinese) 计算机工程与应用, 2019. journal

    Wen, Kunzhe and Wei, Yuke and Dong, Xiaohua.

  5. Perceptual Image Quality Assessment: A Survey. Science China Information Sciences., 2020. paper

    Zhai, Guangtao and Min, Xiongkuo.

  6. Computational Aesthetics:Visual Aesthetics Measurement and Generation Driven by Computational Science. (in chinese) 包装工程, 2021. journal

    Guo, Bin and Zhang, Qiu-yun and Fang, Yu-yang and Ding, Ya-san and Zhang ying and Yu, Zhi-wen

  7. A Survey on Image Aesthetic Assessment. arXiv, 2021. journal

    Anwar, Abbas and Kanwal, Saira and Tahir, Muhammad and Saqib, Muhammad and Uzair, Muhammad and Rahmani, Mohammad Khalid Imam and Ullah, Habib

  1. Computational Media Aesthetics: Finding Meaning Beautiful. IEEE multimedia, 2001. journal

    Nack, Frank and Dorai, Chitra and Venkatesh, Svetha

  2. Defining Computational Aesthetics. Computational aesthetics in graphics, visualization and imaging, 2005. journal

    Neumann, L and Sbert, M and Gooch, B and Purgathofer, W and others

  3. Algorithmic Inferencing of Aesthetics and Emotion in Natural Images: An Exposition. ICIP, 2008. paper

    Datta, Ritendra and Li, Jia and Wang, James Z.

  4. Saliency-Enhanced Image Aesthetics Class Prediction. ICIP, 2009. paper

    Wong, Lai-Kuan and Low, Kok-Lim

  5. The Good, the Bad, and the Ugly: Predicting Aesthetic Image Labels. ICPR, 2010. paper

    Wu, Yaowen and Bauckhage, Christian and Thurau, Christian

  6. A Framework for Photo-Quality Assessment and Enhancement Based on Visual Aesthetics. ACM Multimedia, 2010. paper

    Bhattacharya, Subhabrata and Sukthankar, Rahul and Shah, Mubarak

  7. Affective Image Classification Using Features Inspired By Psychology and Art Theory. ACM Multimedia, 2010. paper, code

    Machajdik, Jana and Hanbury, Allan

  8. Aesthetics and Emotions in Images. IEEE Signal Processing Magazine, 2011. journal

    Joshi, Dhiraj and Datta, Ritendra and Fedorovskaya, Elena and Luong, Quang-Tuan and Wang, James Z and Li, Jia and Luo, Jiebo

  9. Aesthetic Quality Classification of Photographs Based on Color Harmony. CVPR, 2011. paper

    Nishiyama, Masashi and Okabe, Takahiro and Sato, Imari and Sato, Yoichi

  10. A Holistic Approach to Aesthetic Enhancement of Photographs. ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), 2011. journal

    Bhattacharya, Subhabrata and Sukthankar, Rahul and Shah, Mubarak

  11. High Level Describable Attributes for Predicting Aesthetics and Interestingness. CVPR, 2011. paper

    Dhar, Sagnik and Ordonez, Vicente and Berg, Tamara L

  12. Scenic Photo Quality Assessment with Bag of Aesthetics-Preserving Features. ACM Multimedia, 2011. paper

    Su, Hsiao-Hang and Chen, Tse-Wei and Kao, Chieh-Chi and Hsu, Winston H. and Chien, Shao-Yi

  13. Assessing the Aesthetic Quality of Photographs Using Generic Image Descriptors. ICCV, 2011. paper

    Marchesotti, Luca and Perronnin, Florent and Larlus, Diane and Csurka, Gabriela

  14. Assessment of Photo Aesthetics with Efficiency. ICPR, 2012. paper

    Lo, Kuo-Yen and Liu, Keng-Hao and Chen, Chu-Song

  15. AVA: A Large-Scale Database for Aesthetic Visual Analysis. CVPR, 2012. paper, code

    Murray, Naila and Marchesotti, Luca and Perronnin, Florent

  16. Automated Aesthetic Analysis of Photographic Images. IEEE Transactions on Visualization and Computer Graphics, 2014. journal, code

    Aydın, Tunç Ozan and Smolic, Aljoscha and Gross, Markus

  17. Fusion of Multichannel Local and Global Structural Cues for Photo Aesthetics Evaluation. IEEE Transactions on Image Processing, 2014. journal

    Zhang, Luming and Gao, Yue and Zimmermann, Roger and Tian, Qi and Li, Xuelong

  18. Rapid: Rating Pictorial Aesthetics Using Deep Learning. ACM Multimedia, 2014. paper, code

    Lu, Xin and Lin, Zhe and Jin, Hailin and Yang, Jianchao and Wang, James Z.

  19. Deep Multi-Patch Aggregation Network for Image Style, Aesthetics, and Quality Estimation. ICCV, 2015. paper

    Lu, Xin and Lin, Zhe and Shen, Xiaohui and Mech, Radomir and Wang, James Z.

  20. Query-Dependent Aesthetic Model with Deep Learning for Photo Quality Assessment. IEEE Transactions on Multimedia, 2015. journal

    Tian, Xinmei and Dong, Zhe and Yang, Kuiyuan and Mei, Tao

  21. Rating Image Aesthetics Using Deep Learning. IEEE Transactions on Multimedia, 2015. journal, code

    Lu, Xin and Lin, Zhe and Jin, Hailin and Yang, Jianchao and Wang, James Z.

  22. Brain-Inspired Deep Networks for Image Aesthetics Assessment. arXiv, 2016. journal, code

    Wang, Zhangyang and Chang, Shiyu and Dolcos, Florin and Beck, Diane and Liu, Ding and Huang, Thomas S.

  23. A Multi-Scene Deep Learning Model for Image Aesthetic Evaluation. Signal Processing: Image Communication, 2016. journal

    Wang, Weining and Zhao, Mingquan and Wang, Li and Huang, Jiexiong and Cai, Chengjia and Xu, Xiangmin

  24. Hierarchical Aesthetic Quality Assessment Using Deep Convolutional Neural Networks. Signal Processing: Image Communication, 2016. journal

    Kao, Yueying and Huang, Kaiqi and Maybank, Steve

  25. Visual Aesthetic Quality Assessment with Multi-Task Deep Learning. arXiv, 2016. journal

    Kao, Yueying and He, Ran and Huang, Kaiqi

  26. Photo Aesthetics Ranking Network with Attributes and Content Adaptation. ECCV, 2016. paper, code

    Kong, Shu and Shen, Xiaohui and Lin, Zhe and Mech, Radomir and Fowlkes, Charless

  27. Composition-Preserving Deep Photo Aesthetics Assessment. CVPR, 2016. paper

    Mai, Long and Jin, Hailin and Liu, Feng

  28. Joint Image and Text Representation for Aesthetics Analysis. ACM Multimedia, 2016. paper

    Zhou, Ye and Lu, Xin and Zhang, Junping and Wang, James Z.

  29. Aesthetic Critiques Generation for Photos. ICCV, 2017. paper, code

    Chang, Kuang-Yu and Lu, Kung-Hung and Chen, Chu-Song

  30. Deep Aesthetic Quality Assessment with Semantic Information. IEEE Transactions on Image Processing, 2017. journal

    Kao, Yueying and He, Ran and Huang, Kaiqi

  31. Photo Aesthetics Analysis via DCNN Feature Encoding. IEEE Transactions on Multimedia, 2017. journal

    Lee, Hui-Jin and Hong, Ki-Sang and Kang, Henry and Lee, Seungyong

  32. Engineering Deep Representations for Modeling Aesthetic Perception. IEEE Transactions on Cybernetics, 2017. journal

    Chen, Yanxiang and Hu, Yuxing and Zhang, Luming and Li, Ping and Zhang, Chao

  33. A Flexible Fuzzy Regression Method for Addressing Nonlinear Uncertainty on Aesthetic Quality Assessments. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2017. journal

    Chan, Kit Yan and Lam, Hak-Keung and Yiu, Cedric Ka Fai and Dillon, Tharam S.

  34. POI Summarization By Aesthetics Evaluation from Crowd Source Social Media. IEEE Transactions on Image Processing, 2017. journal

    Qian, Xueming and Li, Cheng and Lan, Ke and Hou, Xingsong and Li, Zhetao and Han, Junwei

  35. A-Lamp: Adaptive Layout-Aware Multi-Patch Deep Convolutional Neural Network for Photo Aesthetic Assessment. CVPR, 2017. paper, code

    Ma, Shuang and Liu, Jing and Wen Chen, Chang

  36. Deep Cropping via Attention Box Prediction and Aesthetics Assessment. ICCV, 2017. paper

    Wang, Wenguan and Shen, Jianbing

  37. Using CNN Features to Better Understand What Makes Visual Artworks Special. Frontiers in psychology, 2017. journal

    Brachmann, Anselm and Barth, Erhardt and Redies, Christoph

  38. Computational and Experimental Approaches to Visual Aesthetics. Frontiers in computational neuroscience, 2017. journal

    Brachmann, Anselm and Redies, Christoph

  39. Putting the Art in Artificial: Aesthetic Responses to Computer-Generated Art. Psychology of Aesthetics, Creativity, and the Arts, 2018. journal

    Chamberlain, Rebecca and Mullin, Caitlin and Scheerlinck, Bram and Wagemans, Johan

  40. Usar: An Interactive User-Specific Aesthetic Ranking Framework for Images. ACM Multimedia, 2018. paper

    Lv, Pei and Wang, Meng and Xu, Yongbo and Peng, Ze and Sun, Junyi and Su, Shimei and Zhou, Bing and Xu, Mingliang

  41. Predicting Aesthetic Score Distribution Through Cumulative Jensen-Shannon Divergence. AAAI, 2018. paper, code

    Jin, Xin and Wu, Le and Li, Xiaodong and Chen, Siyu and Peng, Siwei and Chi, Jingying and Ge, Shiming and Song, Chenggen and Zhao, Geng

  42. Objectivity and Subjectivity in Aesthetic Quality Assessment of Digital Photographs. IEEE Transactions on Affective Computing, 2018. journal

    Kim, Won-Hee and Choi, Jun-Ho and Lee, Jong-Seok

  43. Deep Active Learning with Contaminated Tags for Image Aesthetics Assessment. IEEE Transactions on Image Processing, 2018. journal

    Liu, Zhenguang and Wang, Zepeng and Yao, Yiyang and Zhang, Luming and Shao, Ling

  44. Bio-Inspired Deep Attribute Learning towards Facial Aesthetic Prediction. IEEE Transactions on Affective Computing, 2018. journal

    Xu, Mingliang and Chen, Fuhai and Li, Lu and Shen, Chen and Lv, Pei and Zhou, Bing and Ji, Rongrong

  45. Leveraging Expert Feature Knowledge for Predicting Image Aesthetics. IEEE Transactions on Image Processing, 2018. journal

    Kucer, Michal and Loui, Alexander C. and Messinger, David W.

  46. Distribution-Oriented Aesthetics Assessment with Semantic-Aware Hybrid Network. IEEE transactions on multimedia, 2018. journal

    Cui, Chaoran and Liu, Huihui and Lian, Tao and Nie, Liqiang and Zhu, Lei and Yin, Yilong

  47. Image Aesthetics Assessment Using Composite Features from Off-the-Shelf Deep Models. ICIP, 2018. paper

    Fu, Xin and Yan, Jia and Fan, Cien

  48. NIMA: Neural Image Assessment. IEEE Transactions on Image Processing, 2018. journal, code

    Talebi, Hossein and Milanfar, Peyman

  49. Will People Like Your Image? Learning the Aesthetic Space. WACV, 2018. paper, code

    Schwarz, Katharina and Wieschollek, Patrick and Lensch, Hendrik PA

  50. Learning to Detect Multiple Photographic Defects. WACV, 2018. paper, code

    Yu, Ning and Shen, Xiaohui and Lin, Zhe and Mech, Radomir and Barnes, Connelly

  51. PAC-Net: Pairwise Aesthetic Comparison Network for Image Aesthetic Assessment. ICIP, 2018. paper

    Ko, Keunsoo and Lee, Jun-Tae and Kim, Chang-Su

  52. Instagram Likes for Architectural Photos Can Be Predicted By Quantitative Balance Measures and Curvature. Frontiers in Psychology, 2018. journal

    Thömmes, Katja and Hübner, Ronald

  53. Photographic Composition Classification and Dominant Geometric Element Detection for Outdoor Scenes. Journal of Visual Communication and Image Representation, 2018. journal, code

    Lee, Jun-Tae and Kim, Han-Ul and Lee, Chul and Kim, Chang-Su

  54. Image Aesthetic Assessment based on Pairwise Comparison - A Unified Approach to Score Regression, Binary Classification, and Personalization. ICCV, 2019. paper

    Lee, Jun-Tae and Kim, Chang-Su

  55. Personality Driven Multi-Task Learning for Image Aesthetic Assessment. ICME, 2019. paper

    Li, Leida and Zhu, Hancheng and Zhao, Sicheng and Ding, Guiguang and Jiang, Hongyan and Tan, Allen

  56. Aesthetic Attributes Assessment of Images. ACM Multimedia, 2019. paper, code

    Jin, Xin and Wu, Le and Zhao, Geng and Li, Xiaodong and Zhang, Xiaokun and Ge, Shiming and Zou, Dongqing and Zhou, Bin and Zhou, Xinghui

  57. Towards Unified Aesthetics and Emotion Prediction in Images. ICIP, 2019. paper, code

    Yu, Jun and Cui, Chaoran and Geng, LeiLei and Ma, Yuling and Yin, Yilong

  58. Aesthetic Image Captioning from Weakly-Labelled Photographs. ICCV Workshops, 2019. paper, code

    Ghosal, Koustav and Rana, Aakanksha and Smolic, Aljosa

  59. A Unified Probabilistic Formulation of Image Aesthetic Assessment. IEEE Transactions on Image Processing, 2019. journal, code

    Zeng, Hui and Cao, Zisheng and Zhang, Lei and Bovik, Alan C

  60. A Gated Peripheral-Foveal Convolutional Neural Network for Unified Image Aesthetic Prediction. IEEE Transactions on Multimedia, 2019. journal

    Zhang, Xiaodan and Gao, Xinbo and Lu, Wen and He, Lihuo

  61. Deep Multimodality Learning for Uav Video Aesthetic Quality Assessment. IEEE Transactions on Multimedia, 2019. journal

    Kuang, Qi and Jin, Xin and Zhao, Qinping and Zhou, Bin

  62. Color Theme–based Aesthetic Enhancement Algorithm to Emulate the Human Perception of Beauty in Photos. ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), 2019. journal

    Panetta, Karen and Bao, Long and Agaian, Sos and Oludare, Victor

  63. Beauty Is in the Eye of the Beholder: Demographically Oriented Analysis of Aesthetics in Photographs. ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), 2019. journal

    Kairanbay, Magzhan and See, John and Wong, Lai-Kuan

  64. Aesthetics-Guided Graph Clustering with Absent Modalities Imputation. IEEE Transactions on Image Processing, 2019. journal

    Zhang, Luming and Yao, Yiyang and Lu, Zhenguang and Shao, Ling

  65. Image Aesthetic Assessment Assisted By Attributes Through Adversarial Learning. AAAI, 2019. paper

    Pan, Bowen and Wang, Shangfei and Jiang, Qisheng

  66. Aspect-Ratio-Preserving Multi-Patch Image Aesthetics Score Prediction. CVPR Workshops, 2019. paper

    Wang, Lijie and Wang, Xueting and Yamasaki, Toshihiko and Aizawa, Kiyoharu

  67. Modeling Image Composition for Visual Aesthetic Assessment. CVPR Workshops, 2019. paper

    Liu, Dong and Puri, Rohit and Kamath, Nagendra and Bhattacharya, Subhabrata

  68. Effective Aesthetics Prediction with Multi-Level Spatially Pooled Features. CVPR, 2019. paper, code

    Hosu, Vlad and Goldlucke, Bastian and Saupe, Dietmar

  69. An Universal Image Attractiveness Ranking Framework. WACV, 2019. paper

    Ma, Ning and Volkov, Alexey and Livshits, Aleksandr and Pietrusinski, Pawel and Hu, Houdong and Bolin, Mark

  70. Modeling Human Perception for Image Aesthetic Assessme. ICIP, 2019. paper

    Wang, Weining and Deng, Rui

  71. Personality-Assisted Multi-Task Learning for Generic and Personalized Image Aesthetics Assessment. IEEE Transactions on Image Processing, 2020. journal

    Li, Leida and Zhu, Hancheng and Zhao, Sicheng and Ding, Guiguang, and Lin, Weisi

  72. Beyond Vision: A Multimodal Recurrent Attention Convolutional Neural Network for Unified Image Aesthetic Prediction Tasks. IEEE Transactions on Multimedia, 2020. journal

    Zhang, Xiaodan and Gao, Xinbo and Lu, Wen and He, Lihuo and Li, Jie

  73. Social-Sensed Image Aesthetics Assessment. ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), 2020. journal

    Cui, Chaoran and Lin, Peiguang and Nie, Xiushan and Jian, Muwei and Yin, Yilong

  74. Revisiting Image Aesthetic Assessment via Self-Supervised Feature Learning. AAAI, 2020. paper

    Sheng, Kekai and Dong, Weiming and Chai, Menglei and Wang, Guohui and Zhou, Peng and Huang, Feiyue and Hu, Bao-Gang and Ji, Rongrong and Ma, Chongyang

  75. Adaptive Fractional Dilated Convolution Network for Image Aesthetics Assessment. CVPR, 2020. paper

    Chen, Qiuyu and Zhang, Wei and Zhou, Ning and Lei, Peng and Xu, Yi and Zheng, Yu and Fan, Jianping

  76. Composition-Aware Image Aesthetics Assessment. WACV, 2020. paper

    Liu, Dong and Puri, Rohit and Kamath, Nagendra and Bhattacharya, Subhabrata

  77. Learning with Privileged Information for Photo Aesthetic Assessment. Neurocomputing, 2020. journal

    Shu, Yangyang and Li, Qian and Liu, Shaowu and Xu, Guandong

  78. EVA: An Explainable Visual Aesthetics Dataset. Joint Workshop on Aesthetic and Technical Quality Assessment of Multimedia and Media Analytics for Societal Trends, 2020. journal, code

    Kang, Chen and Valenzise, Giuseppe and Dufaux, Frédéric

  79. Object-Level Attention for Aesthetic Rating Distribution Prediction. ACM Multimedia, 2020. paper

    Hou, Jingwen and Yang, Sheng and Lin, Weisi

  80. Representation Learning of Image Composition for Aesthetic Prediction. Computer Vision and Image Understanding, 2020. journal, code

    Zhao, Lin and Shang, Meimei and Gao, Fei and Li, Rongsheng and Huang, Fei and Yu, Jun

  81. A Hypothesis for the Aesthetic Appreciation in Neural Networks. arXiv, 2021. journal

    Cheng, Xu and Wang, Xin and Xue, Haotian and Liang, Zhengyang and Zhang, Quanshi

  82. Semi-Supervised Adversarial Learning for Attribute-Aware Photo Aesthetic Assessment. IEEE Transactions on Multimedia, 2021. journal

    Shu, Yangyang and Li, Qian and Liu, Lingqiao and Xu, Guandong

  83. Hierarchical Layout-Aware Graph Convolutional Network for Unified Aesthetics Assessment. CVPR, 2021. paper, code

    She, Dongyu and Lai, Yu-Kun and Yi, Gaoxiong and Xu, Kun

  84. Self-Supervised Multi-Task Pretraining Improves Image Aesthetic Assessment. CVPR, 2021. paper, code

    Pfister, Jan and Kobs, Konstantin and Hotho, Andreas

  85. Learning Image Aesthetic Assessment from Object-Level Visual Components. arXiv, 2021. journal

    Hou, Jingwen and Yang, Sheng and Lin, Weisi and Zhao, Baoquan and Fang, Yuming

  86. Aesthetic Evaluation and Guidance for Mobile Photography. ACM Multimedia, 2021. paper

    Lou, Hao and Huang, Heng and Xiao, Chaoen and Jin, Xin

  87. Rethinking Image Aesthetics Assessment: Models, Datasets and Benchmarks. IJCAI, 2022. paper, code

    He, Shuai and Zhang, Yongchang and Xie, Rui and Jiang, Dongxiang and Ming, Anlong

  88. Understanding Aesthetics with Language: A Photo Critique Dataset for Aesthetic Assessment. arXiv, 2022. journal, code

    Nieto, Daniel Vera and Celona, Luigi and Fernandez-Labrador, Clara

  89. Exploring Metrics to Establish an Optimal Model for Image Aesthetic Assessment and Analysis. Journal of Imaging, 2022. journal

    Dai, Ying

  90. Composition and Style Attributes Guided Image Aesthetic Assessment. IEEE Transactions on Image Processing, 2022. journal

    Celona, Luigi and Leonardi, Marco and Napoletano, Paolo and Rozza, Alessandro

  91. Learning Image Aesthetic Subjectivity from Attribute-Aware Relational Reasoning Network. Pattern Recognition Letters, 2022. journal

    Zhu, Hancheng and Zhou, Yong and Yao, Rui and Wang, Guangcheng and Yang, Yuzhe

  92. Theme-Aware Semi-Supervised Image Aesthetic Quality Assessment. Mathematics, 2022. journal

    Zhang, Xiaodan and Zhang, Xun and Xiao, Yuan and Liu, Gang

  93. Privileged Multi-Task Learning for Attribute-Aware Aesthetic Assessment. Pattern Recognition, 2022. journal

    Shu, Yangyang and Li, Qian and Liu, Lingqiao and Xu, Guandong

  94. A Deep Drift-Diffusion Model for Image Aesthetic Score Distribution Prediction. ICME Workshops, 2022. paper

    Jin, Xin and Li, Xinning and Huang, Heng and Li, Xiaodong and Xiao, Chaoen and Li, Xiqiao

  95. Pseudo-Labeling and Meta Reweighting Learning for Image Aesthetic Quality Assessment. IEEE Transactions on Intelligent Transportation Systems, 2022. journal

    Jin, Xin and Lou, Hao and Huang, Heng and Li, Xinning and Li, Xiaodong and Cui, Shuai and Zhang, Xiaokun and Li, Xiqiao

  96. Computational Analysis of Correlations Between Image Aesthetic and Image Naturalness in the Relation with Image Quality. Journal of Imaging, 2022. journal

    Le, Quyet-Tien and Ladret, Patricia and Nguyen, Huu-Tuan and Caplier, Alice

  97. Metamp: Metalearning-Based Multipatch Image Aesthetics Assessment. IEEE Transactions on Cybernetics, 2022. journal

    Yang, Jiachen and Zhou, Yanshuang and Zhao, Yang and Lu, Wen and Gao, Xinbo

  98. Interpretable Aesthetic Analysis Model for Intelligent Photography Guidance Systems. ACM IUI, 2022. paper

    Wu, Xiaoran

  99. Distilling Knowledge from Object Classification to Aesthetics Assessment. IEEE Transactions on Circuits and Systems for Video Technology, 2022. journal

    Hou, Jingwen and Ding, Henghui and Lin, Weisi and Liu, Weide and Fang, Yuming

  100. Theme-Aware Aesthetic Distribution Prediction with Full-Resolution Photographs. IEEE Transactions on Neural Networks and Learning Systems, 2022. journal

    Jia, Gengyun and Li, Peipei and He, Ran

  101. BeauVis: A Validated Scale for Measuring the Aesthetic Pleasure of Visual Representations. IEEE Transactions on Visualization and Computer Graphics, 2022. journal

    He, Tingying and Isenberg, Petra and Dachselt, Raimund and Isenberg, Tobias

  102. Compression Ensembles Quantify Aesthetic Complexity and the Evolution of Visual Art. arXiv, 2022. journal

    Karjus, Andres and Solà, Mar Canet and Ohm, Tillmann and Ahnert, Sebastian E and Schich, Maximilian

  103. Clip Knows Image Aesthetics. Frontiers in Artificial Intelligence, 2022. journal

    Hentschel, Simon and Kobs, Konstantin and Hotho, Andreas

  104. Aesthetic Attribute Assessment of Images Numerically on Mixed Multi-attribute Datasets. ACM Transactions on Multimedia Computing, Communications, and Applications, 2022. journal, code

    Jin, Xin; Li, Xinning; Lou, Hao; Fan, Chenyu; Deng, Qiang; Xiao, Chaoen; Cui, Shuai; Singh, Amit Kumar

  105. MaxViT: Multi-Axis Vision Transformer. ECCV, 2022. paper, code

    Tu, Zhengzhong and Talebi, Hossein and Zhang, Han and Yang, Feng and Milanfar, Peyman and Bovik, Alan and Li, Yinxiao

  106. Aesthetically Relevant Image Captioning. AAAI, 2023. paper, code

    Zhong, Zhipeng and Zhou, Fei and Qiu, Guoping

  107. Neural Mechanisms Underlying the Hierarchical Construction of Perceived Aesthetic Value. Nature Communications, 2023. journal

    Iigaya, Kiyohito and Yi, Sanghyun and Wahle, Iman A and Tanwisuth, Sandy and Cross, Logan and Logan and O’Doherty, John P

  108. VILA: Learning Image Aesthetics from User Comments with Vision-Language Pretraining. , 2023. journal

    Ke, Junjie and Ye, Keren and Yu, Jiahui and Wu, Yonghui and Milanfar, Peyman and Yang, Feng

  109. Towards Artistic Image Aesthetics Assessment: a Large-Scale Dataset and a New Method. CVPR, 2023. paper, code

    Yi, Ran and Tian, Haoyuan and Gu, Zhihao and Lai, Yu-Kun and Rosin, Paul L

  110. AesPA-Net: Aesthetic Pattern-Aware Style Transfer Networks. ICCV, 2023. paper

    Hong, Kibeom and Jeon, Seogkyu and Lee, Junsoo and Ahn, Namhyuk and Kim, Kunhee and Lee, Pilhyeon and Kim, Daesik and Uh, Youngjung and Byun, Hyeran

  111. GAIT: Generating Aesthetic Indoor Tours with Deep Reinforcement Learning. ICCV, 2023. paper,code

    Xie, Desai and Hu, Ping and Sun, Xin and Pirk, Soren and Zhang, Jianming and Mech, Radomir and Kaufman, E.Arie

  112. Exploring Video Quality Assessment on User Generated Contents from Aesthetic and Technical Perspectives. ICCV, 2023. paper

    Wu, Haoning and Zhang, Erli and Liao, Liang and Chen, Chaofeng and Hou, Jingwen and Wang, Annan and Sun, Wenxiu and Yan, Qiong and Lin, Weisi

  113. Thinking Image Color Aesthetics Assessment: Models, Datasets and Benchmarks. ICCV, 2023. paper

    He, Shuai and Ming, Anlong and Li, Yaqi and Sun, Jinyuan and Zeng, huntian and Ma, Huadong

  114. A Brain-inspired Multimodal Interaction Network for Image Aesthetic Assessment. ACM International Conference on Multimedia, 2023. paper

    Nie, Xixi and Hu, Bo and Gao, Xinbo and Li, Leida and Zhang, Xiaodan and Xiao, Bin

  115. Personalized Image Aesthetics Assessment with Attribute-guided Fine-grained Feature Representation. ACM International Conference on Multimedia, 2023. paper

    Zhu, Hancheng and Shao, Zhiwen and Zhou, Yong and Wang, Guangcheng and Chen, Pengfei and Li, Leida

  116. AesCLIP: Multi-Attribute Contrastive Learning for Image Aesthetics Assessment. ACM International Conference on Multimedia, 2023. paper

    Sheng, Xiangfei and Li, Leida and Chen, Pengfei and Wu, Jinjian and Dong, Weisheng and Yang, Yuzhe and Xu, Liwu and Li, Yanqian and Shi, Guangming

  1. Personalized Image Aesthetic Quality Assessment By Joint Regression and Ranking. WACV, 2017. paper

    Park, Kayoung and Hong, Seunghoon and Baek, Mooyeol and Han, Bohyung

  2. Personalized Image Aesthetics. ICCV, 2017. paper, code

    Ren, Jian and Shen, Xiaohui and Lin, Zhe and Mech, Radomir and Foran, David J

  3. Collaborative and Attentive Learning for Personalized Image Aesthetic Assessment. IJCAI, 2018. paper, code

    Wang, Guolong and Yan, Junchi and Qin, Zheng

  4. Image Aesthetic Assessment based on Pairwise Comparison - A Unified Approach to Score Regression, Binary Classification, and Personalization. ICCV, 2019. paper

    Lee, Jun-Tae and Kim, Chang-Su

  5. Personality Driven Multi-Task Learning for Image Aesthetic Assessment. ICME, 2019. paper

    Li, Leida and Zhu, Hancheng and Zhao, Sicheng and Ding, Guiguang and Jiang, Hongyan and Tan, Allen

  6. Meta-Learning Perspective for Personalized Image Aesthetics Assessment. ICIP, 2019. paper

    Wang, Weining and Su, Junjie and Li, Lemin and Xu, Xiangmin and Luo, Jiebo

  7. Personalized Image Aesthetics Assessment via Meta-Learning with Bilevel Gradient Optimization. IEEE Transactions on Image Processing, 2020. journal, code

    Zhu, Hancheng and Li, Leida and Wu, Jinjian and Zhao, Sicheng and Ding, Guiguang and Shi, Guangming

  8. Personality-Assisted Multi-Task Learning for Generic and Personalized Image Aesthetics Assessment. IEEE Transactions on Image Processing, 2020. journal

    Li, Leida and Zhu, Hancheng and Zhao, Sicheng and Ding, Guiguang, and Lin, Weisi

  9. Personalized Image Quality Assessment with Social-Sensed Aesthetic Preference. Information Sciences, 2020. journal

    Cui, Chaoran and Yang, Wenya and Shi, Cheng and Wang, Meng and Nie, Xiushan and Yin, Yilong

  10. Learning Personalized Image Aesthetics from Subjective and Objective Attributes. IEEE Transactions on Multimedia, 2021. journal

    Zhu, Hancheng and Zhou, Yong and Li, Leida and Li, Yaqian and Guo, Yandong

  11. User-Guided Personalized Image Aesthetic Assessment Based on Deep Reinforcement Learning. IEEE Transactions on Multimedia, 2021. journal

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    Yi, Ran and Tian, Haoyuan and Gu, Zhihao and Lai, Yu-Kun and Rosin, Paul L

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    Zong, Hai

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  5. Computational Aesthetic Evaluation of Logos. ACM Transactions on Applied Perception, 2017. journal

    Zhang, Jiajing and Yu, Jinhui and Zhang, Kang and Zheng, Xianjun Sam and Zhang, Junsong

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  7. RA Code: A Robust and Aesthetic Code for Resolution-Constrained Applications. IEEE Transactions on Circuits and Systems for Video Technology, 2017. journal

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