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https://github.com/bcmi/Awesome-Aesthetic-Evaluation-and-Cropping

List: Awesome-Aesthetic-Evaluation-and-Cropping
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URL: https://github.com/bcmi/Awesome-Aesthetic-Evaluation-and-Cropping
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- Readme: README.md
Awesome Lists containing this project

Awesome-Image-Quality-Assessment - Awesome Image Aesthetic Assessment and Cropping
README

        # Awesome Image Aesthetic Assessment and Cropping [![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)](https://github.com/sindresorhus/awesome)

A curated list of resources including papers, datasets, and relevant links pertaining to aesthetic evaluation and cropping.

## Contributing

Contributions are welcome.  If you wish to contribute, feel free to send a pull request. If you have suggestions for new sections to be included, please raise an issue and discuss before sending a pull request.

## Table of Contents

+ [Papers](#Papers)

+ [Datasets](#Datasets)

+ [Other Resources](#Other-resources)

## Papers

#### Image Aesthetic Assessment

+ Shuai He, Anlong Ming, Yaqi Li, Jinyuan Sun, ShunTian Zheng, Huadong Ma: "*Thinking Image Color Aesthetics Assessment: Models, Datasets and Benchmarks*" ICCV (2023) [[paper]](https://github.com/woshidandan/Image-Color-Aesthetics-Assessment/blob/main/Paper-PDF-Thinking%20Image%20Color%20Aesthetics%20Assessment%20Models%2C%20Datasets%20and%20Benchmarks.pdf) [[homepage]](https://github.com/woshidandan/Image-Color-Aesthetics-Assessment)

+ Shuai He, Anlong Ming, Shuntian Zheng, Haobin Zhong, Huadong Ma: "*EAT: An Enhancer for Aesthetics-Oriented Transformers.*" ACM MM (2023) [[pdf]](https://github.com/woshidandan/Image-Aesthetics-Assessment/blob/main/Paper-PDF-EAT%20An%20Enhancer%20for%20Aesthetics-Oriented%20Transformers.pdf) [[homepage]](https://github.com/woshidandan/Image-Aesthetics-Assessment/tree/main#eat-an-enhancer-for-aesthetics-oriented-transformers)

+ Yaohui Li, Yuzhe Yang, Huaxiong Li,Haoxing Chen, Liwu Xu, Leida Li, Yaqian Li, Yandong Guo: "*Transductive Aesthetic Preference Propagation for Personalized Image Aesthetics Assessment*" ACM MM (2023) [[pdf]](https://dl.acm.org/doi/10.1145/3503161.3548244)

+ Ran Yi, Haoyuan Tian, Zhihao Gu, Yu-Kun Lai, Paul L. Rosin: "*Towards Artistic Image Aesthetics Assessment: a Large-scale Dataset and a New Method*" CVPR (2023) [[pdf]](https://arxiv.org/abs/2303.15166) [[dataset]](https://github.com/Dreemurr-T/BAID)

+ Junjie Ke, Keren Ye, Jiahui Yu, Yonghui Wu, Peyman Milanfar, Feng Yang: "*VILA: Learning Image Aesthetics from User Comments with Vision-Language Pretraining*" CVPR (2023) [[pdf]](https://arxiv.org/abs/2303.14302)

+ Shuai He, Yongchang Zhang, Rui Xie, Dongxiang Jiang, Anlong Ming: "*Rethinking Image Aesthetics Assessment: Models, Datasets and Benchmarks*" IJCAI (2022) [[pdf]](https://www.ijcai.org/proceedings/2022/0132.pdf) [[code]](https://github.com/woshidandan/TANet)

+ Yuzhe Yang, Liwu Xu, Leida Li, Nan Qie, Yaqian Li, Peng Zhang, Yandong Guo: "*Personalized Image Aesthetics Assessment with Rich Attributes*" CVPR (2022) [[pdf]](https://arxiv.org/pdf/2203.16754.pdf) [[homepage]](https://web.xidian.edu.cn/ldli/en/dataset.html)

+ Dongyu She, Yu-Kun Lai, Gaoxiong Yi, Kun Xu: "*Hierarchical layout-aware graph convolutional network for unified aesthetics assessment.*" CVPR (2021) [[pdf]](https://openaccess.thecvf.com/content/CVPR2021/papers/She_Hierarchical_Layout-Aware_Graph_Convolutional_Network_for_Unified_Aesthetics_Assessment_CVPR_2021_paper.pdf)

+ Hao Lou, Heng Huang, Chaoen Xiao, Xin Jin: "*Aesthetic Evaluation and Guidance for Mobile Photography.*" ACM MM(2021) [[pdf]](https://dl.acm.org/doi/abs/10.1145/3474085.3478557)

+ Pei Lv, Jianqi Fan, Xixi Nie, Weiming Dong, Xiaoheng Jiang, Bing Zhou, Mingliang Xu, Changsheng Xu: "*User-Guided Personalized Image Aesthetic Assessment based on Deep Reinforcement Learning.*" TMM (2021) [[pdf]](https://arxiv.org/pdf/2106.07488.pdf)

+ Jingwen Hou, Sheng Yang, Weisi Lin, Baoquan Zhao, Yuming Fang: "*Learning Image Aesthetic Assessment from Object-level Visual Components.*" TIP (2021) [[pdf]](https://arxiv.org/pdf/2104.01548.pdf)

+ Lin Zhao, Meimei Shang, Fei Gao, Rongsheng Li, Fei Huang, Jun Yu: "*Representation learning of image composition for aesthetic prediction.*" CVIU (2020) [[pdf]](https://linkinghub.elsevier.com/retrieve/pii/S1077314220300801) [[code]](https://github.com/fei-hdu/ReLIC)  

+ Jingwen Hou, Sheng Yang, Weisi Lin: "*Object-level attention for aesthetic rating distribution prediction.*" ACM MM (2020) [[pdf]](https://dr.ntu.edu.sg/bitstream/10356/144332/2/Object-level%20attention%20for%20aesthetic%20rating%20distribution%20prediction.pdf)

+ Kekai Sheng, Weiming Dong, Menglei Chai, Guohui Wang, Peng Zhou, Feiyue Huang, Bao-Gang Hu, Rongrong Ji, Chongyang Ma: "*Revisiting image aesthetic assessment via self-supervised feature learning.*" AAAI (2020) [[pdf]](https://arxiv.org/pdf/1911.11419.pdf)

+ Qiuyu Chen, Wei Zhang, Ning Zhou, Peng Lei, Yi Xu, Yu Zheng, Jianping Fan: "*Adaptive fractional dilated convolution network for image aesthetics assessment.*" CVPR (2020) [[pdf]](https://openaccess.thecvf.com/content_CVPR_2020/papers/Chen_Adaptive_Fractional_Dilated_Convolution_Network_for_Image_Aesthetics_Assessment_CVPR_2020_paper.pdf)

+ Hui Zeng, Zisheng Cao, Lei Zhang, Alan C. Bovik: "*A unified probabilistic formulation of image aesthetic assessment.*" TIP (2020) [[pdf]](https://ieeexplore.ieee.org/abstract/document/8846580) [[code]](https://github.com/HuiZeng/Unified_IAA)

+ Dong Liu, Rohit Puri, Nagendra Kamath, Subhabrata Bhattacharya: "*Composition-aware image aesthetics assessment.*" WACV(2020) [[pdf]](https://openaccess.thecvf.com/content_WACV_2020/papers/Liu_Composition-Aware_Image_Aesthetics_Assessment_WACV_2020_paper.pdf)

+ Hancheng Zhu, Leida Li, Jinjian Wu, Sicheng Zhao, Guiguang Ding, Guangming Shi: "*Personalized Image Aesthetics Assessment via Meta-Learning With Bilevel Gradient Optimization.*" IEEE Trans. Cybern. (2020) [[pdf]](https://ieeexplore.ieee.org/abstract/document/9115059) [[code]](https://github.com/zhuhancheng/BLG-PIAA)

+ Weining Wang, Rui Deng: "*Modeling human perception for image aesthetic assessme.*" ICIP (2019) [[pdf]](https://ieeexplore.ieee.org/document/8803749)

+ Vlad Hosu, Bastian Goldlucke, Dietmar Saupe: "*Effective aesthetics prediction with multi-level spatially pooled features.*" CVPR (2019) [[pdf]](https://openaccess.thecvf.com/content_CVPR_2019/papers/Hosu_Effective_Aesthetics_Prediction_With_Multi-Level_Spatially_Pooled_Features_CVPR_2019_paper.pdf) [[code]](https://github.com/subpic/ava-mlsp)

+ Xin Jin, Le Wu, Geng Zhao, Xiaodong Li, Xiaokun Zhang, Shiming Ge, Dongqing Zou, Bin Zhou, Xinghui Zhou: "*Aesthetic attributes assessment of images.*" ACM MM (2019) [[pdf]](https://arxiv.org/pdf/1907.04983.pdf) [[project]](https://github.com/BestiVictory/DPC-Captions)

+ Leida Li, Hancheng Zhu, Sicheng Zhao, Guiguang Ding, Hongyan Jiang, Allen Tan: "*Personality driven multi-task learning for image aesthetic assessment.*" ICME (2019) [[pdf]](https://ieeexplore.ieee.org/abstract/document/8784759)

+ Ning Ma, Alexey Volkov, Aleksandr Livshits, Pawel Pietrusinski, Houdong Hu, Mark Bolin: "*An universal image attractiveness ranking framework.*" WACV (2019) [[pdf]](https://arxiv.org/pdf/1805.00309.pdf)

+ Jun-Tae Lee, Han-Ul Kim, Chul Lee, Chang-Su Kim: "*Photographic composition classification and dominant geometric element detection for outdoor scenes.*" JVCIR (2018) [[pdf]](https://www.sciencedirect.com/science/article/abs/pii/S1047320318301147) [[code]](http://mcl.korea.ac.kr/research/Submitted/jtlee_JVCIR2018/code.zip)

+ Katja Thömmes and Ronald Hübner: "*Instagram likes for architectural photos can be predicted by quantitative balance measures and curvature.*" Front Psychol (2018) [[pdf]](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6024014/)

+ Kekai Sheng, Weiming Dong, Chongyang Ma, Xing Mei, Feiyue Huang, Bao-Gang Hu: "*Attention-based multi-patch aggregation for image aesthetic assessment.*" ACM MM (2018) [[pdf]](https://openreview.net/pdf/1cc851d9d7bfc5ec17eedc6498b1601fcb84a40b.pdf) [[code]](https://github.com/Openning07/MPADA)

+ Ning Yu, Xiaohui Shen, Zhe Lin, Radomir Mech, Connelly Barnes: "*Learning to detect multiple photographic defects.*" WACV (2018) [[pdf]](https://arxiv.org/pdf/1612.01635.pdf)

+ Keunsoo Ko, Jun Tae Lee, Chang-Su Kim: "*PAC-Net: Pairwise aesthetic comparison network for image aesthetic assessment.*" ICIP (2018) [[pdf]](https://ieeexplore.ieee.org/abstract/document/8451621)

+ Hossein Talebi and Peyman Milanfar: "*NIMA: Neural image assessment.*" TIP (2018) [[pdf]](https://ieeexplore.ieee.org/abstract/document/8352823) [[code]](https://paperswithcode.com/paper/nima-neural-image-assessment#code)

+ Katharina Schwarz, Patrick Wieschollek, Hendrik P. A. Lensch: "*Will people like your image? Learning the aesthetic space.*" WACV (2018) [[pdf]](https://arxiv.org/pdf/1611.05203.pdf) [[code]](https://github.com/cgtuebingen/will-people-like-your-image)

+ Guolong Wang, Junchi Yan, Zheng Qin: "*Collaborative and attentive learning for personalized image aesthetic assessment.*" IJCAI (2018) [[pdf]](https://www.ijcai.org/Proceedings/2018/0133.pdf)

+ Shuang Ma, Jing Liu, Chang Wen Chen: "*A-Lamp: Adaptive layout-aware multi-patch deep convolutional neural network for photo aesthetic assessment.*" CVPR (2017) [[pdf]](https://openaccess.thecvf.com/content_cvpr_2017/papers/Ma_A-Lamp_Adaptive_Layout-Aware_CVPR_2017_paper.pdf) [[code]](https://github.com/GuillaumeBalezo/A-Lamp) 

+ Jian Ren, Xiaohui Shen, Zhe Lin, Radomir Mech, David J. Foran: "*Personalized image aesthetics.*" ICCV (2017) [[pdf]](https://openaccess.thecvf.com/content_ICCV_2017/papers/Ren_Personalized_Image_Aesthetics_ICCV_2017_paper.pdf) [[code]](https://github.com/alanspike/personalizedImageAesthetics)

+ Anselm Brachmann and Christoph Redies: "*Computational and experimental approaches to visual aesthetics.*"  Front Hum Neurosci (2017) [[pdf]](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5694465/)

+ Anselm Brachmann, Erhardt Barth, Christoph Redies: "*Using CNN features to better understand what makes visual artworks special.*" Front Psychol (2017) [[pdf]](https://pubmed.ncbi.nlm.nih.gov/28588537/)

+ Deng Yubin, Chen Change Loy, Xiaoou Tang: "*Image aesthetic assessment: An experimental survey.*" IEEE Signal Processing Magazine (2017) [[pdf]](https://arxiv.org/pdf/1610.00838.pdf) 

+ Long Mai, Hailin Jin, Feng Liu: "*Composition-preserving deep photo aesthetics assessment.*" CVPR (2016) [[pdf]](https://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Mai_Composition-Preserving_Deep_Photo_CVPR_2016_paper.pdf)

+ Shu Kong, Xiaohui Shen, Zhe L. Lin, Radomír Mech, Charless C. Fowlkes: "*Photo aesthetics ranking network with attributes and content adaptation.*" ECCV (2016) [[pdf]](https://arxiv.org/pdf/1606.01621.pdf) [[code]](https://github.com/aimerykong/deepImageAestheticsAnalysis)

+ Xin Lu, Zhe Lin, Xiaohui Shen, Radomir Mech, James Z. Wang: "*Deep multi-patch aggregation network for image style, aesthetics, and quality estimation.*" ICCV (2015) [[pdf]](https://www.cv-foundation.org/openaccess/content_iccv_2015/papers/Lu_Deep_Multi-Patch_Aggregation_ICCV_2015_paper.pdf)

+ Xin Lu, Zhe Lin, Hailin Jin, Jianchao Yang, James Z. Wang: "*Rapid: Rating pictorial aesthetics using deep learning.*" ACM MM (2014) [[pdf]](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.710.1251&rep=rep1&type=pdf) [[code]](https://github.com/paramoecium/RAPID)

+ Naila Murray, Luca Marchesotti, Florent Perronnin: "*AVA: A large-scale database for aesthetic visual analysis.*" CVPR (2012) [[pdf]](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6247954)

+ Luca Marchesotti, Florent Perronnin, Diane Larlus, Gabriela Csurka: "*Assessing the aesthetic quality of photographs using generic image descriptors.*" ICCV (2011) [[pdf]](https://ieeexplore.ieee.org/document/6126444)

+ Sagnik Dhar, Vicente Ordonez, Tamara L Berg: "*High level describable attributes for predicting aesthetics and interestingness.*" CVPR (2011) [[pdf]](https://bvisionweb1.cs.unc.edu/home/publications/aesthetics_cvpr11.pdf)

+ Ritendra Datta, Jia Li, and James Z. Wang: "*Algorithmic inferencing of aesthetics and emotion in natural images: An exposition.*" ICIP (2008) [[pdf]](https://www.ri.cmu.edu/pub_files/pub4/datta_ritendra_2008_2/datta_ritendra_2008_2.pdf)

#### Image Cropping

+ Zhiyu Pan, Jiahao Cui, Kewei Wang, Yizheng Wu, and Zhiguo Cao. “Pseudo Label Fusion with Uncertainty Estimation for Semi-Supervised Cropping Box Regression.” TMM (2024) [[pdf]](https://ieeexplore.ieee.org/document/10472083)

+ Yukun Su, Yiwen Cao, Jingliang Deng, Fengyun Rao, and Qingyao Wu. “Spatial-Semantic Collaborative Cropping for User Generated Content.” AAAI (2024) [[pdf]](https://ojs.aaai.org/index.php/AAAI/article/view/28303/28596) [[code]](https://github.com/suyukun666/S2CNet/tree/main)

+ Quan Yuan, Leida Li, and Pengfei Chen. “Aesthetic Image Cropping Meets Vlp: Enhancing Good While Reducing Bad.” SSRN (2024) [[pdf]](https://doi.org/10.2139/ssrn.4879045)

+ James Hong, Lu Yuan, Michaël Gharbi, Matthew Fisher, and Kayvon Fatahalian. “Learning Subject-Aware Cropping by Outpainting Professional Photos.” AAAI (2024) [[pdf]](https://ojs.aaai.org/index.php/AAAI/article/view/28303/28596) [[code]](https://github.com/jhong93/gencrop)

+ Zhiyu Pan, Yinpeng Chen, Jiale Zhang, Hao Lu, Zhiguo Cao, and Weicai Zhong. “Find Beauty in the Rare: Contrastive Composition Feature Clustering for Nontrivial Cropping Box Regression.” AAAI (2023) [[pdf]](https://ojs.aaai.org/index.php/AAAI/article/view/25293)

+ GuoYe Yang, WenYang Zhou, Yun Cai, SongHai Zhang, and FangLue Zhang. “Focusing on Your Subject: Deep Subject-Aware Image Composition Recommendation Networks.” Computational Visual Media (2023) [[pdf]](https://link.springer.com/article/10.1007/s41095-021-0263-3) [[dataset]](https://cg.cs.tsinghua.edu.cn/SACD/)

+ Takumi Nishiyasu, Wataru Shimoda, and Yoichi Sato. “Image Cropping under Design Constraints.” ACMMM Asia (2023) [[pdf]](https://arxiv.org/abs/2310.08892) [[code]](https://github.com/CyberAgentAILab/cropping-design-constraints)

+ Tengfei Shi, Chenglizhao Chen, Yuanbo He, Wenfeng Song, and Aimin Hao. “Joint Probability Distribution Regression for Image Cropping.” ICIP (2023) [[pdf]](https://ieeexplore.ieee.org/document/10222223)

+ Xiaoyu Liu, Ming Liu, Junyi Li, Shuai Liu, Xiaotao Wang, Lei Lei, Wangmeng Zuo: "*Beyond Image Borders: Learning Feature Extrapolation for Unbounded Image Composition.*" ICCV (2023) [[pdf]](https://openaccess.thecvf.com/content/ICCV2023/html/Liu_Beyond_Image_Borders_Learning_Feature_Extrapolation_for_Unbounded_Image_Composition_ICCV_2023_paper.html) [[code]](https://github.com/liuxiaoyu1104/UNIC) 

+ Zhihang Zhong, Mingxi Cheng, Zhirong Wu, Yuhui Yuan, Yinqiang Zheng, Ji Li, Han Hu, Stephen Lin, Yoichi Sato, Imari Sato: "*ClipCrop: Conditioned Cropping Driven by Vision-Language Model.*" ICCV Workshops (2023) [[pdf]](https://arxiv.org/pdf/2211.11492.pdf)

+ Wang Chao, Li Niu, Bo Zhang, Liqing Zhang: "*Image Cropping with Spatial-aware Feature and Rank Consistency.*" CVPR (2023) [[pdf]](https://openaccess.thecvf.com/content/CVPR2023/html/Wang_Image_Cropping_With_Spatial-Aware_Feature_and_Rank_Consistency_CVPR_2023_paper.html)

+ Gengyun Jia, Huaibo Huang, Chaoyou Fu, Ran He: "*Rethinking Image Cropping: Exploring Diverse Compositions From Global Views.*" CVPR (2022) [[pdf]](https://openaccess.thecvf.com/content/CVPR2022/papers/Jia_Rethinking_Image_Cropping_Exploring_Diverse_Compositions_From_Global_Views_CVPR_2022_paper.pdf)

+ Yang Cheng, Qian Lin, Jan P. Allebach: "*Re-Compose the Image by Evaluating the Crop on More Than Just a Score.*" WACV (2022) [[pdf]](https://openaccess.thecvf.com/content/WACV2022/papers/Cheng_Re-Compose_the_Image_by_Evaluating_the_Crop_on_More_Than_WACV_2022_paper.pdf)

+ Zhiyu Pan, Zhiguo Cao, Kewei Wang, Hao Lu, Weicai Zhong: "*TransView: Inside, Outside, and Across the Cropping View Boundaries.*" ICCV (2021) [[pdf]](https://openaccess.thecvf.com/content/ICCV2021/papers/Pan_TransView_Inside_Outside_and_Across_the_Cropping_View_Boundaries_ICCV_2021_paper.pdf)

+ Lei Zhong, Feng-Heng Li, Hao-Zhi Huang, Yong Zhang, Shao-Ping Lu, Jue Wang: "*Aesthetic-guided outward image cropping.*" TOG (2021) [[pdf]](https://www.shaopinglu.net/publications_files/tog21.pdf)

+ Chaoyi Hong, Shuaiyuan Du, Ke Xian, Hao Lu, Zhiguo Cao, Weicai Zhong: "*Composing photos like a photographer.*" CVPR (2021) [[pdf]](https://openaccess.thecvf.com/content/CVPR2021/papers/Hong_Composing_Photos_Like_a_Photographer_CVPR_2021_paper.pdf) [[code]](https://github.com/bo-zhang-cs/CACNet-Pytorch)

+ Debang Li, Junge Zhang, Kaiqi Huang: "*Learning to learn cropping models for different aspect ratio requirements.*" CVPR (2020) [[pdf]](https://openaccess.thecvf.com/content_CVPR_2020/papers/Li_Learning_to_Learn_Cropping_Models_for_Different_Aspect_Ratio_Requirements_CVPR_2020_paper.pdf) 

+ Debang Li, Junge Zhang, Kaiqi Huang, Ming-Hsuan Yang: "*Composing good shots by exploiting mutual relations.*" CVPR (2020) [[pdf]](https://openaccess.thecvf.com/content_CVPR_2020/papers/Li_Composing_Good_Shots_by_Exploiting_Mutual_Relations_CVPR_2020_paper.pdf) [[code]](https://github.com/bo-zhang-cs/CGS-Pytorch)

+ Yi Tu, Li Niu, Weijie Zhao, Dawei Cheng, Liqing Zhang: "*Image cropping with composition and saliency aware aesthetic score map.*" AAAI (2020) [[pdf]](https://arxiv.org/pdf/1911.10492.pdf)

+ Hui Zeng, Lida Li, Zisheng Cao, Lei Zhang: "*Grid anchor based image cropping: a new benchmark and an efficient model.*" TPAMI (2020) [[pdf]](https://www4.comp.polyu.edu.hk/~cslzhang/paper/GAIC-PAMI.pdf) [[code]](https://github.com/HuiZeng/Grid-Anchor-based-Image-Cropping-Pytorch)

+ Hui Zeng, Lida Li, Zisheng Cao, Lei Zhang: "*Reliable and efficient image cropping: a grid anchor based approach.*" CVPR (2019)  [[pdf]](https://arxiv.org/pdf/1909.08989.pdf)  [[code]](https://github.com/HuiZeng/Grid-Anchor-based-Image-Cropping)

+ Weirui Lu, Xiaofen Xing, Bolun Cai, Xiangmin Xu: "*Listwise view ranking for image cropping.*" IEEE Access (2019) [[pdf]](https://arxiv.org/pdf/1905.05352.pdf) [[code]](https://github.com/luwr1022/listwise-view-ranking)

+ Zijun Wei, Jianming Zhang, Xiaohui Shen, Zhe Lin, Radomír Mech, Minh Hoai, Dimitris Samaras: "*Good view hunting: learning photo composition from dense view pairs.*" CVPR (2018) [[pdf]](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wei_Good_View_Hunting_CVPR_2018_paper.pdf) [[VEN code]](https://github.com/zijunwei/ViewEvaluationNet) [[VPN code]](https://github.com/zijunwei/ViewProposalNet)

+ Debang Li, Huikai Wu, Junge Zhang, Kaiqi Huang: "*A2-RL: aesthetics aware reinforcement learning for image cropping.*" [[pdf]](https://openaccess.thecvf.com/content_cvpr_2018/papers/Li_A2-RL_Aesthetics_Aware_CVPR_2018_paper.pdf) [[code]](https://github.com/wuhuikai/TF-A2RL)

+ Seyed A. Esmaeili, Bharat Singh, Larry S. Davis: "*Fast-At: Fast automatic thumbnail generation using deep neural networks.*" CVPR (2017) [[pdf]](https://arxiv.org/pdf/1612.04811.pdf)

+ Wenguan Wang, Jianbing Shen: "*Deep cropping via attention box prediction and aesthetics assessment.*" ICCV (2017) [[pdf]](http://openaccess.thecvf.com/content_ICCV_2017/papers/Wang_Deep_Cropping_via_ICCV_2017_paper.pdf)

+ Yi-Ling Chen, Jan Klopp, Min Sun, Shao-Yi Chien, Kwan-Liu Ma: "*Learning to compose with professional photographs on the web.*" ACM MM (2017) [[pdf]](https://arxiv.org/pdf/1702.00503.pdf) [[code]](https://github.com/yiling-chen/view-finding-network)

+ Yi-Ling Chen, Tzu-Wei Huang, Kai-Han Chang, Yu-Chen Tsai, Hwann-Tzong Chen, Bing-Yu Chen: "*Quantitative analysis of automatic image cropping algorithms: a dataset and comparative study.*" WACV (2017) [[pdf]](https://arxiv.org/pdf/1701.01480.pdf)

+ Jiansheng Chen, Gaocheng Bai, Shaoheng Liang, Zhengqin Li: "*Automatic image cropping: a computational complexity study."* CVPR (2016) [[pdf]](https://www.cv-foundation.org/openaccess/content_cvpr_2016/app/S03-33.pdf)

+ Jonas Abeln, Leonie Fresz, Seyed Ali Amirshahi, Chris McManus, Michael Koch, Helene Kreysa, Christoph Redies: "*Preference for well-balanced saliency in details cropped from photographs.*" Front Hum Neurosci (2016) [[pdf]](https://pubmed.ncbi.nlm.nih.gov/26793086/)

+ Chen Fang, Zhe Lin, Radomír Mech, Xiaohui Shen: "*Automatic image Cropping using visual composition, boundary simplicity and content preservation models.*" ACM MM (2014) [[pdf]](http://fangchen.org/paper_pdf/FLMS_mm14.pdf)

+ Jianzhou Yan, Stephen Lin, Sing Bing Kang, Xiaoou Tang: "*Learning the change for automatic image cropping.*" CVPR (2013) [[pdf]](https://www.cv-foundation.org/openaccess/content_cvpr_2013/papers/Yan_Learning_the_Change_2013_CVPR_paper.pdf)

+ Bongwon Suh, Haibin Ling, Benjamin B. Bederson, David W. Jacobs: "*Automatic thumbnail cropping and its effectiveness.*" UIST (2003) [[pdf]](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.12.2949&rep=rep1&type=pdf)

#### Aesthetic Captioning

+ Junjie Ke, Keren Ye, Jiahui Yu, Yonghui Wu, Peyman Milanfar, Feng Yang: "*VILA: Learning Image Aesthetics from User Comments with Vision-Language Pretraining.*" CVPR (2023) [[pdf]](https://arxiv.org/abs/2303.14302)

+ Koustav Ghosal, Aakanksha Rana, Aljosa Smolic: "*Aesthetic Image Captioning From Weakly-Labelled Photographs.*" ICCVW (2019) [[pdf]](https://arxiv.org/pdf/1908.11310.pdf) [[homepage]](https://github.com/V-Sense/Aesthetic-Image-Captioning-ICCVW-2019)

+ Xin Jin, Le Wu, Geng Zhao, Xiaodong Li, Xiaokun Zhang, Shiming Ge, Dongqing Zou, Bin Zhou, Xinghui Zhou: "*Aesthetic Attributes Assessment of Images.*" ACM MM (2019) [[pdf]](https://arxiv.org/pdf/1907.04983.pdf) [[code]](https://github.com/BestiVictory/DPC-Captions)

+ Wenshan Wang, Su Yang, Weishan Zhang, Jiulong Zhang: "*Neural aesthetic image reviewer.*" IET Computer Vision (2019) [[pdf]](https://arxiv.org/pdf/1802.10240.pdf)

+ Kuang-Yu Chang, Kung-Hung Lu, Chu-Song Chen: "*Aesthetic Critiques Generation for Photos.*" ICCV (2017) [[pdf]](http://openaccess.thecvf.com/content_ICCV_2017/papers/Chang_Aesthetic_Critiques_Generation_ICCV_2017_paper.pdf) [[code]](https://github.com/kunghunglu/DeepPhotoCritic-ICCV17) 

+ Ye Zhou, Xin Lu, Junping Zhang, James Z. Wang: "*Joint image and text representation for aesthetics analysis.*" ACM MM (2016) [[pdf]](https://dl.acm.org/doi/pdf/10.1145/2964284.2967223)

## Datasets

### Aesthetic Assessment Datasets

images with aesthetic score/attribute

+ Photo.net (2006) [[homepage]](https://ritendra.weebly.com/aesthetics-datasets.html)

+ DPChallenge (2008) [[homepage]](https://ritendra.weebly.com/aesthetics-datasets.html)

+ CUHK-PQ (2011) [[homepage]](http://mmlab.ie.cuhk.edu.hk/archive/CUHKPQ/Dataset.htm)

+ AVA (2012) [[download]](https://github.com/imfing/ava_downloader)

+ AADB (2016) [[homepage]](https://github.com/aimerykong/deepImageAestheticsAnalysis)

+ FLICKER-AES and REAL-CUR (2017) [[homepage]](https://github.com/alanspike/personalizedImageAesthetics)

+ PCCD (2017) [[homepage]](https://github.com/kunghunglu/DeepPhotoCritic-ICCV17)

+ AROD (2018) [[homepage]](https://github.com/cgtuebingen/will-people-like-your-image)

+ EVA (2020) [[homepage]](https://github.com/kang-gnak/eva-dataset)

+ TAD66K (2022) [[homepage]](https://github.com/woshidandan/TANet)

+ PARA (2022) [[homepage]](https://web.xidian.edu.cn/ldli/en/dataset.html)

+ Boldbrush Artistic Image Dataset (BAID) (2023) [[homepage]](https://github.com/Dreemurr-T/BAID)

+ Largest Color-oriented Dataset: ICAA17K (2023) [[homepage]](https://github.com/woshidandan/Image-Color-Aesthetics-Assessment)

images with aesthetic caption

+ PCCD (2017) [[download]](https://drive.google.com/file/d/1hap2UGI9XV5XmxKOo54wZW30OXbqNyo8/view?usp=sharing) 

+ DPC-Captions (2019) [[homepage]](https://github.com/BestiVictory/DPC-Captions)

+ AVA-Captions (2019) [[homepage]](https://github.com/V-Sense/Aesthetic-Image-Captioning-ICCVW-2019)

image with composition score/label

+ KU-PCP (2018) [[homepage]](http://mcl.korea.ac.kr/jtlee_jvcir2018/)

+ CADB (2021) [[homepage]](https://github.com/bcmi/Image-Composition-Assessment-Dataset-CADB)

### Image Cropping Datasets

densely annotated (multiple crops in each image are annotated)

+ CPC (2018) [[homepage]](https://www3.cs.stonybrook.edu/~cvl/projects/wei2018goods/VPN_CVPR2018s.html)

+ GAICD (2019) [[homepage]](https://github.com/HuiZeng/Grid-Anchor-based-Image-Cropping)

+ SACD (2023) [[homepage]](https://cg.cs.tsinghua.edu.cn/SACD)

+ SID (2024) [[homepage]](https://github.com/jhong93/gencrop)

+ UGCrop5K (2024) [[homepage]](https://github.com/suyukun666/S2CNet)

sparsely annotated (only the best crop in each image is annotated)

+ ICDB/MSR-ICD (2013) [[homepage]](https://personal.ie.cuhk.edu.hk/~ccloy/downloads_cuhk_crop_dataset.html)

+ FLMS/HCDB (2014) [[download images]](http://fangchen.org/proj_page/FLMS_mm14/data/radomir500_image/image.tar) [[download crops]](http://fangchen.org/proj_page/FLMS_mm14/data/radomir500_gt/release_data.tar)

+ FCDB (2017) [[homepage]](https://github.com/yiling-chen/flickr-cropping-dataset)

+ GNMC (2022) [[homepage]](https://github.com/aneeshvartakavi/GNMC)