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Measuring the perception of visual content is a long-standing problem in computer vision.
The statistics of natural images
Ruderman, D. L. 1994 · 1994
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Final report from the video quality experts group on the validation of objective models of video quality assessment
Group, V. Q. E.; et al. 2000 · 2000
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Multiscale structural similarity for image quality assessment
Wang, Z.; Simoncelli, E. P.; and Bovik, A. C. 2003 · 2003
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Gaze patterns when looking at emotional pictures: Motivationally biased attention
Calvo, M. G.; and Lang, P. J. 2004 · 2004
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Image quality assessment: from error visibility to structural similarity
Wang, Z.; Bovik, A. C.; Sheikh, H. R.; and Simoncelli, E. P. 2004 · 2004
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Artifact reduction with diffusion preprocessing for image compression
Kopilovic, I.; and Sziranyi, T. 2005 · 2005
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Image information and visual quality
Sheikh, H. R.; and Bovik, A. C. 2006 · 2006
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A statistical evaluation of recent full reference image quality assessment algorithms
Sheikh, H. R.; Sabir, M. F.; and Bovik, A. C. 2006 · 2006
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Most apparent distortion: full-reference image quality assessment and the role of strategy
Larson, E. C.; and Chandler, D. M. 2010 · 2010
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A two-step framework for constructing blind image quality indices
Moorthy, A. K.; and Bovik, A. C. 2010 · 2010
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Learning Photographic Global Tonal Adjustment with a Database of Input / Output Image Pairs
Bychkovsky, V.; Paris, S.; Chan, E.; and Durand, F. 2011 · 2011
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Applications of objective image quality assessment methods [applications corner]
Wang, Z. 2011 · 2011
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FSIM: A feature similarity index for image quality assessment
Zhang, L.; Zhang, L.; Mou, X.; and Zhang, D. 2011 · 2011
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No-reference image quality assessment in the spatial domain
Mittal, A.; Moorthy, A. K.; and Bovik, A. C. 2012 · 2012
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Making a “completely blind” image quality analyzer
Mittal, A.; Soundararajan, R.; and Bovik, A. C. 2012 · 2012
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AVA: A large-scale database for aesthetic visual analysis
Murray, N.; Marchesotti, L.; and Perronnin, F. 2012 · 2012
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Blind image quality assessment: A natural scene statistics approach in the DCT domain
Saad, M. A.; Bovik, A. C.; and Charrier, C. 2012 · 2012
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Unsupervised feature learning framework for no-reference image quality assessment
Ye, P.; Kumar, J.; Kang, L.; and Doermann, D. 2012 · 2012
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Gradient magnitude similarity deviation: A highly efficient perceptual image quality index
Xue, W.; Zhang, L.; Mou, X.; and Bovik, A. C. 2013 · 2013
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Affective abstract image classification and retrieval using multiple kernel learning
Zhang, H.; Yang, Z.; Gönen, M.; Koskela, M.; Laaksonen, J.; Honkela, T.; and Oja, E. 2013 · 2013
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Convolutional neural networks for no-reference image quality assessment
Kang, L.; Ye, P.; Li, Y.; and Doermann, D. 2014 · 2014
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VSI: A visual saliency-induced index for perceptual image quality assessment
Zhang, L.; Shen, Y.; and Li, H. 2014 · 2014
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Massive online crowdsourced study of subjective and objective picture quality
Ghadiyaram, D.; and Bovik, A. C. 2015 · 2015
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Image color transfer to evoke different emotions based on color combinations
He, L.; Qi, H.; and Zaretzki, R. 2015 · 2015
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Image database TID2013: Peculiarities, results and perspectives
Ponomarenko, N.; Jin, L.; Ieremeiev, O.; Lukin, V.; Egiazarian, K.; Astola, J.; Vozel, B.; Chehdi, K.; Carli, M.; Battisti, F.; et al. 2015 · 2015
Cited alongside, same era.
A feature-enriched completely blind image quality evaluator
Zhang, L.; Zhang, L.; and Bovik, A. C. 2015 · 2015
Cited alongside, same era.
Photo Aesthetics Ranking Network with Attributes and Content Adaptation
Kong, S.; Shen, X.; Lin, Z.; Mech, R.; and Fowlkes, C. 2016 · 2016
Cited alongside, same era.
Deep neural networks for no-reference and full-reference image quality assessment
Bosse, S.; Maniry, D.; Müller, K.-R.; Wiegand, T.; and Samek, W. 2017 · 2017
Cited alongside, same era.
Natural language processing: State of the art, current trends and challenges
Khurana, D.; Koli, A.; Khatter, K.; and Singh, S. 2017 · 2017
Cited alongside, same era.
Perceptual image quality assessment with transformers
Cheon, M.; Yoon, S.-J.; Kang, B.; and Lee, J. 2021 · 2021
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Comparison of full-reference image quality models for optimization of image processing systems
Ding, K.; Ma, K.; Wang, S.; and Simoncelli, E. P. 2021 · 2021
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An image is worth more than a thousand words: Towards disentanglement in the wild
Gabbay, A.; Cohen, N.; and Hoshen, Y. 2021 · 2021
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CLIPScore: A reference-free evaluation metric for image captioning
Hessel, J.; Holtzman, A.; Forbes, M.; Bras, R. L.; and Choi, Y. 2021 · 2021
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Learning the Non-differentiable Optimization for Blind Super-Resolution
Hui, Z.; Li, J.; Wang, X.; and Gao, X. 2021 · 2021
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Putting nerf on a diet: Semantically consistent few-shot view synthesis
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The perception-distortion tradeoff
Blau, Y.; and Michaeli, T. 2018 · 2018
Cited alongside, same era.
Building emotional machines: Recognizing image emotions through deep neural networks
Kim, H.-R.; Kim, Y.-S.; Kim, S. J.; and Lee, I.-K. 2018 · 2018
Cited alongside, same era.
Contemplating visual emotions: Understanding and overcoming dataset bias
Panda, R.; Zhang, J.; Li, H.; Lee, J.-Y.; Lu, X.; and Roy-Chowdhury, A. K. 2018 · 2018
Cited alongside, same era.
Pieapp: Perceptual image-error assessment through pairwise preference
Prashnani, E.; Cai, H.; Mostofi, Y.; and Sen, P. 2018 · 2018
Cited alongside, same era.
Attention-based multi-patch aggregation for image aesthetic assessment
Sheng, K.; Dong, W.; Ma, C.; Mei, X.; Huang, F.; and Hu, B.-G. 2018 · 2018
Cited alongside, same era.
Deep Retinex Decomposition for Low-Light Enhancement
Wei, C.; Wang, W.; Yang, W.; and Liu, J. 2018 · 2018
Cited alongside, same era.
Real-world noisy image denoising: A new benchmark
Xu, J.; Li, H.; Liang, Z.; Zhang, D.; and Zhang, L. 2018 · 2018
Cited alongside, same era.
Jain, A.; Tancik, M.; and Abbeel, P. 2021 · 2021
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Musiq: Multi-scale image quality transformer
Ke, J.; Wang, Q.; Wang, Y.; Milanfar, P.; and Yang, F. 2021 · 2021
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Clipcap: Clip prefix for image captioning
Mokady, R.; Hertz, A.; and Bermano, A. H. 2021 · 2021
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Styleclip: Text-driven manipulation of stylegan imagery
Patashnik, O.; Wu, Z.; Shechtman, E.; Cohen-Or, D.; and Lischinski, D. 2021 · 2021
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Learning transferable visual models from natural language supervision
Radford, A.; Kim, J. W.; Hallacy, C.; Ramesh, A.; Goh, G.; Agarwal, S.; Sastry, G.; Askell, A.; Mishkin, P.; Clark, J.; et al. 2021 · 2021
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Semi-supervised Adversarial Learning for Attribute-Aware Photo Aesthetic Assessment
Shu, Y.; Li, Q.; Liu, L.; and Xu, G. 2021 · 2021
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Ranksrgan: Generative adversarial networks with ranker for image super-resolution
Wenlong, Z.; Yihao, L.; Dong, C.; and Qiao, Y. 2021 · 2021
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Positional encoding as spatial inductive bias in gans
Xu, R.; Wang, X.; Chen, K.; Zhou, B.; and Loy, C. C. 2021 · 2021
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Tip-Adapter: Training-free CLIP-Adapter for Better Vision-Language Modeling
Zhang, R.; Fang, R.; Gao, P.; Zhang, W.; Li, K.; Dai, J.; Qiao, Y.; and Li, H. 2021 · 2021
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Open-vocabulary Object Detection via Vision and Language Knowledge Distillation
Gu, X.; Lin, T.-Y.; Kuo, W.; and Cui, Y. 2022 · 2022
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Pseudo-labelling and Meta Reweighting Learning for Image Aesthetic Quality Assessment
Jin, X.; Lou, H.; Heng, H.; Li, X.; Cui, S.; Zhang, X.; and Li, X. 2022 · 2022
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VCRNet: Visual Compensation Restoration Network for No-Reference Image Quality Assessment
Pan, Z.; Yuan, F.; Lei, J.; Fang, Y.; Shao, X.; and Kwong, S. 2022 · 2022
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DenseCLIP: Language-Guided Dense Prediction with Context-Aware Prompting
Rao, Y.; Zhao, W.; Chen, G.; Tang, Y.; Zhu, Z.; Huang, G.; Zhou, J.; and Lu, J. 2022 · 2022
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ProposalCLIP: Unsupervised Open-Category Object Proposal Generation via Exploiting CLIP Cues
Shi, H.; Hayat, M.; Wu, Y.; and Cai, J. 2022 · 2022
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Predict, Prevent, and Evaluate: Disentangled Text-Driven Image Manipulation Empowered by Pre-Trained Vision-Language Model
Xu, Z.; Lin, T.; Tang, H.; Li, F.; He, D.; Sebe, N.; Timofte, R.; Van Gool, L.; and Ding, E. 2022 · 2022
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RegionCLIP: Region-based Language-Image Pretraining
Zhong, Y.; Yang, J.; Zhang, P.; Li, C.; Codella, N.; Li, L. H.; Zhou, L.; Dai, X.; Yuan, L.; Li, Y.; et al. 2022 · 2022
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DenseCLIP: Extract Free Dense Labels from CLIP
Zhou, C.; Loy, C. C.; and Dai, B. 2022 · 2022
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Learning to prompt for vision-language models
Zhou, K.; Yang, J.; Loy, C. C.; and Liu, Z. 2022 · 2022
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