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A Switched View of Retinex: Deep Self-Regularized Low-Light Image Enhancement

Zhuqing Jiang, Haotian Li, Liangjie Liu, Aidong Men, Haiying Wang
2021 Neurocomputing  
Our code is available at eep-Self-Regularized-Low-Light-Image-Enhancement.  ...  A B S T R A C T Self-regularized low-light image enhancement does not require any normal-light image in training, thereby freeing from the chains of paired or unpaired training data that are time-consuming  ...  In this paper, we propose a novel self-regularized method for low-light image enhancement.  ... 
doi:10.1016/j.neucom.2021.05.025 fatcat:qfwoaf3r3fgrfg6gsjkqjeue2y

Self-supervised Low Light Image Enhancement and Denoising [article]

Yu Zhang and Xiaoguang Di and Bin Zhang and Qingyan Li and Shiyu Yan and Chunhui Wang
2021 arXiv   pre-print
This paper proposes a self-supervised low light image enhancement method based on deep learning, which can improve the image contrast and reduce noise at the same time to avoid the blur caused by pre-/  ...  The ICE-Net takes the low light image as input and produces a contrast enhanced image.  ...  Inspired by [41] which introduce a Conditional Re-Enhancement Network(CRE-Net) to denoise for low light image enhancement tasks, we further propose a self-supervised RED-Net to re-enhance the low light  ... 
arXiv:2103.00832v1 fatcat:ll5puz3ndjh7jjw44f4ty3egqu

Unsupervised Low-Light Image Enhancement via Histogram Equalization Prior [article]

Feng Zhang, Yuanjie Shao, Yishi Sun, Kai Zhu, Changxin Gao, Nong Sang
2021 arXiv   pre-print
Deep learning-based methods for low-light image enhancement typically require enormous paired training data, which are impractical to capture in real-world scenarios.  ...  Embedded into a Light Up Module (LUM), it helps to decompose the low-light images into illumination and reflectance maps, and the reflectance maps can be regarded as restored images.  ...  Deep learning based Methods Deep learning-based methods have dominated the research of low-light image enhancement. Lore et al.  ... 
arXiv:2112.01766v1 fatcat:k3oslkc5k5birhlkpu4b6eamh4

Learning with Nested Scene Modeling and Cooperative Architecture Search for Low-Light Vision [article]

Risheng Liu and Long Ma and Tengyu Ma and Xin Fan and Zhongxuan Luo
2021 arXiv   pre-print
A variety of deep learning methods have been proposed to enhance the visual quality of low-light images.  ...  To partially address above issues, we establish Retinex-inspired Unrolling with Architecture Search (RUAS), a general learning framework, which not only can address low-light enhancement task, but also  ...  ACKNOWLEDGMENTS This work is partially supported by the National Key R&D Program of China (2020YFB1313503), the National Natural Science Foundation of China (No. 61922019), and the Fundamental Research  ... 
arXiv:2112.04719v1 fatcat:h2nxuzalvngenerod7vxgacu6m

2020 Index IEEE Transactions on Image Processing Vol. 29

2020 IEEE Transactions on Image Processing  
., +, TIP 2020 3091 Multi-View Video Synopsis via Simultaneous Object-Shifting and View-Switching Optimization.  ...  ., +, Self-Enhanced Convolutional Network for Facial Video Hallucination. Fang, C., +, TIP 2020 3078-3090 Self-Supervised Learning of Detailed 3D Face Reconstruction.  ... 
doi:10.1109/tip.2020.3046056 fatcat:24m6k2elprf2nfmucbjzhvzk3m

Seeing Pedestrian in the Dark via Multi-Task Feature Fusing-Sharing Learning for Imaging Sensors

Yuanzhi Wang, Tao Lu, Tao Zhang, Yuntao Wu
2020 Sensors  
Experimental results show that the proposed approach consistently and significantly improves the performance of pedestrian detection on low-light images obtained by visible light imaging sensor.  ...  The image relighting subnetwork adjusts the low-light image quality for detection, the pedestrian detection subnetwork learns enhanced features for prediction, and the feature-level multi-task fusion learning  ...  Conflicts of Interest: The authors declare no conflicts of interest.  ... 
doi:10.3390/s20205852 pmid:33081153 pmcid:PMC7588961 fatcat:6ccaruvf5fgbjblwcbinb7ure4

Real-world Person Re-Identification via Degradation Invariance Learning [article]

Yukun Huang, Zheng-Jun Zha, Xueyang Fu, Richang Hong, Liang Li
2020 arXiv   pre-print
We use low-resolution images as the main demonstration, and experiments show that our approach is able to achieve state-of-the-art performance on several Re-ID benchmarks.  ...  An intuitive solution to this problem is to utilize low-level image restoration methods to improve the image quality.  ...  Low-level variations tend to have global consistency and can be alleviated by image restoration methods, such as super-resolution or low-light enhancement.  ... 
arXiv:2004.04933v1 fatcat:hrldgxr2hzarpl3g3ye3drbste

2019 Index IEEE Photonics Journal Vol. 11

2019 IEEE Photonics Journal  
., JPHOT Feb. 2019 7901115 Remote Sensing Image Enhancement Via Edge-Preserving Multiscale Retinex.  ...  ., +, JPHOT Dec. 2019 7801718 Remote Sensing Image Enhancement Via Edge-Preserving Multiscale Retinex.  ... 
doi:10.1109/jphot.2020.2969544 fatcat:i2xladbx5fff7fhlgng2n4nc3e

Perceiving light versus material

Frederick A.A. Kingdom
2008 Vision Research  
On the basis of an examination of the cues together with the behavioural evidence that they are used by vision, I propose a set of heuristics that may guide vision in the task of distinguishing between  ...  This review explores the cues, or regularities in the visual world that evidence suggests vision exploits to discriminate light from material.  ...  Acknowledgements This review was supported by Canadian Institute of Health Research Grant #11554 given to the author.  ... 
doi:10.1016/j.visres.2008.03.020 pmid:18479723 fatcat:kbopisaqijddhdcyjgwnjtctxi

Person Re-identification: A Retrospective on Domain Specific Open Challenges and Future Trends [article]

Asmat Zahra, Nazia Perwaiz, Muhammad Shahzad, Muhammad Moazam Fraz
2022 arXiv   pre-print
It aims to automatically identify/search persons in a multi-camera network having non-overlapping field-of-views.  ...  Owing to its potential in various applications and research significance, a plethora of deep learning based re-Id approaches have been proposed in the recent years.  ...  Lighting conditions significantly affects the performance of low level features such as texture and color.  ... 
arXiv:2202.13121v1 fatcat:luwwbcwspndqpauj4dosmmojee

Deep Learning meets Liveness Detection: Recent Advancements and Challenges [article]

Arian Sabaghi, Marzieh Oghbaie, Kooshan Hashemifard, Mohammad Akbari
2021 arXiv   pre-print
To shed light on this topic, a semantic taxonomy based on various features and learning methodologies is represented.  ...  Deep feature learning and techniques, as opposed to hand-crafted features, have promised a dramatic increase in the FAS systems' accuracy, tackling the key challenges of materializing the real-world application  ...  lights in the room are switched on) and light-off (electric lights are turned off).  ... 
arXiv:2112.14796v1 fatcat:axar6akifnh3lgc4mbuqc5nc2i

Empowering Things with Intelligence: A Survey of the Progress, Challenges, and Opportunities in Artificial Intelligence of Things [article]

Jing Zhang, Dacheng Tao
2020 arXiv   pre-print
Artificial intelligence (AI), especially deep learning, is now a proven success in various areas including computer vision, speech recognition, and natural language processing.  ...  However, transmitting massive amounts of heterogeneous data, perceiving complex environments from these data, and then making smart decisions in a timely manner are difficult.  ...  Images captured in a low-light environment are in low visibility and difficult to see details due to insufficient incident light or underexposure.  ... 
arXiv:2011.08612v1 fatcat:dflut2wdrjb4xojll34c7daol4

Autonomous Driving in Adverse Weather Conditions: A Survey [article]

Yuxiao Zhang, Alexander Carballo, Hanting Yang, Kazuya Takeda
2021 arXiv   pre-print
State-of-the-art techniques on perception enhancement with regard to each kind of weather are thoroughly reported.  ...  a holistic overview on the obstacles and directions of ADS development in terms of adverse weather driving conditions.  ...  The Retinex algorithm can also be ify the network to a new DirtyGAN. Furthermore, they used for image enhancement in low-light conditions [203].  ... 
arXiv:2112.08936v1 fatcat:hmgjhywy7rgx3fgrk6yxnu56ie

Improving Shadow Suppression for Illumination Robust Face Recognition

Wuming ZHANG, Xi ZHAO, Jean-Marie Morvan, Liming Chen
2018 IEEE Transactions on Pattern Analysis and Machine Intelligence  
Moreover, as an advantage over most prevailing methods, a photo-realistic color face image is subsequently reconstructed which eliminates a wide variety of shadows whilst retaining the color information  ...  Specifically, the proposed illumination processing pipeline enables the generation of Chromaticity Intrinsic Image (CII) in a log chromaticity space which is robust to illumination variations.  ...  [9] in the Self Quotient Image (SQI) which replaced the prototype images by a smoothed version of test image itself.  ... 
doi:10.1109/tpami.2018.2803179 pmid:29994507 fatcat:qqdzwzajbfecrktm6eev55gfia

The M2DC Project: Modular Microserver DataCentre

Mariano Cecowski, Giovanni Agosta, Ariel Oleksiak, Michal Kierzynka, Micha vor dem Berge, Wolfgang Christmann, Stefan Krupop, Mario Porrmann, Jens Hagemeyer, Rene Griessl, Meysam Peykanu, Lennart Tigges (+13 others)
2016 2016 Euromicro Conference on Digital System Design (DSD)  
This paper provides an overview of the different topics FPGAs have been used for in the last 15 years of research and why they have been chosen over other processing units like e.g. CPUs.  ...  Since their introduction, FPGAs can be seen in more and more different fields of applications.  ...  A more detailed view on the topic is given in [3] .  ... 
doi:10.1109/dsd.2016.76 dblp:conf/dsd/CecowskiAOKBCKP16 fatcat:bu4nbkqaejebjafrotibui6mkq
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