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As the quality of optical sensors improves, there is a need for processing large-scale images.
A multiscale retinex for bridging the gap between color images and the human observation of scenes
Jobson, D. J.; Rahman, Z.-u.; and Woodell, G. A. 1997 · 1997
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Contrast enhancement using brightness preserving bi-histogram equalization
Kim, Y.-T. 1997 · 1997
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Adaptive image contrast enhancement using generalizations of histogram equalization
Stark, J. A. 2000 · 2000
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A variational framework for retinex
Kimmel, R.; Elad, M.; Shaked, D.; Keshet, R.; and Sobel, I. 2003 · 2003
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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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Fast efficient algorithm for enhancement of low lighting video
Dong, X.; Wang, G.; Pang, Y.; Li, W.; Wen, J.; Meng, W.; and Lu, Y. 2011 · 2011
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Contrast enhancement based on layered difference representation
Lee, C.; Lee, C.; and Kim, C.-S. 2012 · 2012
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A biologically inspired scale-space for illumination invariant feature detection
Vonikakis, V.; Chrysostomou, D.; Kouskouridas, R.; and Gasteratos, A. 2013 · 2013
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Naturalness preserved enhancement algorithm for non-uniform illumination images
Wang, S.; Zheng, J.; Hu, H.-M.; and Li, B. 2013 · 2013
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Generalized equalization model for image enhancement
Xu, H.; Zhai, G.; Wu, X.; and Yang, X. 2013 · 2013
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Spatial entropy-based global and local image contrast enhancement
Celik, T. 2014 · 2014
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Variational Bayesian method for retinex
Wang, L.; Xiao, L.; Liu, H.; and Wei, Z. 2014 · 2014
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Fast r-cnn
Girshick, R. 2015 · 2015
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A low-light image enhancement method for both denoising and contrast enlarging
Li, L.; Wang, R.; Wang, W.; and Gao, W. 2015 · 2015
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Ba, J. L.; Kiros, J. R.; and Hinton, G. E. 2016 · 2016
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LIME: Low-light image enhancement via illumination map estimation
Guo, X.; Li, Y.; and Ling, H. 2016 · 2016
Cited alongside, same era.
Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network
Shi, W.; Caballero, J.; Huszár, F.; Totz, J.; Aitken, A. P.; Bishop, R.; Rueckert, D.; and Wang, Z. 2016 · 2016
Cited alongside, same era.
Enhanced deep residual networks for single image super-resolution
Lim, B.; Son, S.; Kim, H.; Nah, S.; and Mu Lee, K. 2017 · 2017
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LLNet: A deep autoencoder approach to natural low-light image enhancement
Lore, K. G.; Akintayo, A.; and Sarkar, S. 2017 · 2017
Cited alongside, same era.
Msr-net: Low-light image enhancement using deep convolutional network
Shen, L.; Yue, Z.; Feng, F.; Chen, Q.; Liu, S.; and Ma, J. 2017 · 2017
Cited alongside, same era.
Advancing image understanding in poor visibility environments: A collective benchmark study
Yang, W.; Yuan, Y.; Ren, W.; Liu, J.; Scheirer, W. J.; Wang, Z.; Zhang, T.; Zhong, Q.; Xie, D.; Pu, S.; et al. 2020 · 2020
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Learning enriched features for real image restoration and enhancement
Zamir, S. W.; Arora, A.; Khan, S.; Hayat, M.; Khan, F. S.; Yang, M.-H.; and Shao, L. 2020 · 2020
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Deblurring by realistic blurring
Zhang, K.; Luo, W.; Zhong, Y.; Ma, L.; Stenger, B.; Liu, W.; and Li, H. 2020 · 2020
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An image is worth 16x16 words: Transformers for image recognition at scale
Dosovitskiy, A.; Beyer, L.; Kolesnikov, A.; Weissenborn, D.; Zhai, X.; Unterthiner, T.; Dehghani, M.; Minderer, M.; Heigold, G.; Gelly, S.; et al. 2021 · 2021
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Enlightengan: Deep light enhancement without paired supervision
Jiang, Y.; Gong, X.; Liu, D.; Cheng, Y.; Fang, C.; Shen, X.; Yang, J.; Zhou, P.; and Wang, Z. 2021 · 2021
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Attention is all you need
Vaswani, A.; Shazeer, N.; Parmar, N.; Uszkoreit, J.; Jones, L.; Gomez, A. N.; Kaiser, Ł.; and Polosukhin, I. 2017 · 2017
Cited alongside, same era.
A bio-inspired multi-exposure fusion framework for low-light image enhancement
Ying, Z.; Li, G.; and Gao, W. 2017 · 2017
Cited alongside, same era.
Learning to see in the dark
Chen, C.; Chen, Q.; Xu, J.; and Koltun, V. 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.
Kindling the darkness: A practical low-light image enhancer
Zhang, Y.; Zhang, J.; and Guo, X. 2019 · 2019
Cited alongside, same era.
Retinaface: Single-shot multi-level face localisation in the wild
Deng, J.; Guo, J.; Ververas, E.; Kotsia, I.; and Zafeiriou, S. 2020 · 2020
Cited alongside, same era.
Zero-reference deep curve estimation for low-light image enhancement
Guo, C.; Li, C.; Guo, J.; Loy, C. C.; Hou, J.; Kwong, S.; and Cong, R. 2020 · 2020
Cited alongside, same era.
Learning to Enhance Low-Light Image via Zero-Reference Deep Curve Estimation
Li, C.; Guo, C. G.; and Loy, C. C. 2021 · 2021
Later among the works it cites.
Video deblurring via spatiotemporal pyramid network and adversarial gradient prior
Wang, T.; Zhang, X.; Jiang, R.; Zhao, L.; Chen, H.; and Luo, W. 2021 · 2021
Later among the works it cites.
Low-light image and video enhancement using deep learning: A survey
Li, C.; Guo, C.; Han, L.-H.; Jiang, J.; Cheng, M.-M.; Gu, J.; and Loy, C. C. 2022 · 2022
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AdaInt: Learning Adaptive Intervals for 3D Lookup Tables on Real-time Image Enhancement
Yang, C.; Jin, M.; Jia, X.; Xu, Y.; and Chen, Y. 2022 · 2022
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Restormer: Efficient Transformer for High-Resolution Image Restoration
Zamir, S. W.; Arora, A.; Khan, S.; Hayat, M.; Khan, F. S.; and Yang, M.-H. 2022 · 2022
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Deep image deblurring: A survey
Zhang, K.; Ren, W.; Luo, W.; Lai, W.-S.; Stenger, B.; Yang, M.-H.; and Li, H. 2022 · 2022
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Enhancement and noise reduction of very low light level images
Zhang, X.; Shen, P.; Luo, L.; Zhang, L.; and Song, J. 2012 · 2037
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Learning a deep single image contrast enhancer from multi-exposure images
Cai, J.; Gu, S.; and Zhang, L. 2018 · 2062
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Learning image-adaptive 3d lookup tables for high performance photo enhancement in real-time
Zeng, H.; Cai, J.; Li, L.; Cao, Z.; and Zhang, L. 2020 · 2073
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