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Deep Learning-based Single Image Face Depth Data Enhancement
[article]
2021
arXiv
pre-print
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All tested enhancer types exclusively use depth data as input, which differs from methods that enhance depth based on additional input data such as visible light color images. ...
The proposed deep learning enhancers yield noticeably better results than the tested preexisting enhancers, without overly falsifying depth data when non-face input is provided, and are shown to reduce ...
Deep Learning-based Depth Enhancer The deep learning depth enhancer network is created using Keras [69] . ...
arXiv:2006.11091v3
fatcat:56rg6myuxzc25m7ymucb6lvose
2021 Index IEEE Transactions on Image Processing Vol. 30
2021
IEEE Transactions on Image Processing
Preserved Fulltext
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Gao, Y., +, TIP 2021 9321-9331 Weakly Supervised Learning for Single Depth-Based Hand Shape Recovery. ...
., +, TIP 2021 5944-5955 Deep Spectral Representation Learning From Multi-View Data. Huang, Z., +, TIP 2021 5352-5362 Deep Learning-Based Forgery Attack on Document Images. ...
doi:10.1109/tip.2022.3142569
fatcat:z26yhwuecbgrnb2czhwjlf73qu
A Novel Face Recognition Algorithm based on the Deep Convolution Neural Network and Key Points Detection Jointed Local Binary Pattern Methodology
2017
Journal of Electrical Engineering and Technology
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This paper presents a novel face recognition algorithm based on the deep convolution neural network and key point detection jointed local binary pattern methodology to enhance the accuracy of face recognition ...
Furthermore, we modify the local binary pattern texture description operator and combine it with the neural network to overcome drawbacks that deep neural network could not learn to face image and the ...
Face recognition application field expands unceasingly in recent years and many occasions require the identification based on a single face image. ...
doi:10.5370/jeet.2017.12.1.363
fatcat:xrgzmayk3vgsrovcnucjjhngau
2019 Index IEEE Transactions on Circuits and Systems for Video Technology Vol. 29
2019
IEEE transactions on circuits and systems for video technology (Print)
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., +, TCSVT Dec. 2019 3568-3582 Fast Single-Image Super-Resolution via Deep Network With Component Learning. ...
Shen, C., +, TCSVT Oct. 2019 3016-3027 Single Image Depth Estimation With Normal Guided Scale Invariant Deep Convolutional Fields. ...
doi:10.1109/tcsvt.2019.2959179
fatcat:2bdmsygnonfjnmnvmb72c63tja
Trade-off Between Spatial and Angular Resolution in Facial Recognition
[article]
2024
arXiv
pre-print
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State-of-the-art methods often incorporate additional information, such as depth, thermal, or angular data, to enhance performance. ...
However, light field-based face recognition approaches that leverage angular information face computational limitations. ...
Deep learning-based face recognition techniques, like other computer vision tasks, are becoming state-of-the-art. ...
arXiv:2402.07263v1
fatcat:7tqf376ppbg77evygl3tc7a5ky
VCIP 2020 Index
2020
2020 IEEE International Conference on Visual Communications and Image Processing (VCIP)
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Guided Self-Supervised Depth
Completion from LiDAR and Monocular Camer
Wu, Feng
Deep Learning-Based Nonlinear Transform for
HEVC Intra Coding
Wu, Feng
Chain Code-Based Occupancy Map Coding fo ...
Coding Zhou, Yanlin Spatiotemporal Guided Self-Supervised Depth Completion from LiDAR and Monocular Camer Zhou, Yudong A night-time outdoor data set for low-light enhancement Theory of Occlusion for Improving ...
doi:10.1109/vcip49819.2020.9301896
fatcat:bdh7cuvstzgrbaztnahjdp5s5y
Cross-modal Deep Face Normals with Deactivable Skip Connections
[article]
2020
arXiv
pre-print
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While data-driven strategies have been proposed for single face images, limited available ground truth data makes this problem difficult. ...
To alleviate this issue, we propose a method that can leverage all available image and normal data, whether paired or not, thanks to a novel cross-modal learning architecture. ...
Geometry Enhancement using Deep Networks Methods have been proposed that directly enhance face models using deep neural networks. Richardson et al. ...
arXiv:2003.09691v2
fatcat:66ianwrqqvf6phcws77nnzya6m
2020 Index IEEE Transactions on Circuits and Systems for Video Technology Vol. 30
2020
IEEE transactions on circuits and systems for video technology (Print)
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., +, TCSVT June 2020 1569-1582
Adversarial Learning for Depth and Viewpoint Estimation From a Single
Image. ...
., +, TCSVT Oct. 2020 3843-3855
CAD
Adversarial Learning for Depth and Viewpoint Estimation From a Single
Image. ...
doi:10.1109/tcsvt.2020.3043861
fatcat:s6z4wzp45vfflphgfcxh6x7npu
2020 Index IEEE Transactions on Image Processing Vol. 29
2020
IEEE Transactions on Image Processing
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., +, TIP 2020 6800-6812 Deep Cascade Model-Based Face Recognition: When Deep-Layered Learning Meets Small Data. ...
., +, TIP
2020 2380-2394
Deep Cascade Model-Based Face Recognition: When Deep-Layered Learn-
ing Meets Small Data. ...
doi:10.1109/tip.2020.3046056
fatcat:24m6k2elprf2nfmucbjzhvzk3m
Facial Expression Recognition from a Single Face Image Based on Deep Learning and Broad Learning
2022
Wireless Communications and Mobile Computing
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Most single face image datasets are based on the psychological classification of the six basic human expressions used for network training. ...
By outlining the problem of facial recognition by comparing traditional methods, deep learning, and broad learning techniques, this review highlights the remaining challenges and future directions of deep ...
The impacts of traditional and deep learning technology on different data sets are compared, and facial expression recognition technology based on deep learning is thoroughly examined from the perspectives ...
doi:10.1155/2022/7094539
fatcat:z7um4uzymzeadinnpffcmoiowe
Deep Learning for Face Anti-Spoofing: A Survey
[article]
2022
arXiv
pre-print
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In this paper, to stimulate future research, we present the first comprehensive review of recent advances in deep learning based FAS. ...
RGB camera, we summarize the deep learning applications under multi-modal (e.g., depth and infrared) or specialized (e.g., light field and flash) sensors. ...
Privacy-Preserved Training Leveraging large-scale live/spoof face data, deep learning based FAS has achieved huge breakthroughs. ...
arXiv:2106.14948v3
fatcat:jqlcgrte3faoxmn4pucnys4kbm
Recent trends in image processing and pattern recognition
2020
Multimedia tools and applications
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In "Super Resolution of Single Depth Image based on Multi-dictionary Learning with Edge Feature Regularization," authors focused on super resolution based on multi-dictionary learning with edge regularization ...
In "Image Fuzzy Enhancement Algorithm based on Contourlet Transform Domain," authors focused on enhancing globally the texture and edge of the image. ...
doi:10.1007/s11042-020-10093-3
fatcat:z2wzbhk4qbd3vpsyuzm4pdlque
Contrast-enhanced serial optical coherence scanner with deep learning network reveals vasculature and white matter organization of mouse brain
2019
Neurophotonics
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The segmentation and reconstruction of the vasculature are presented by using a deep learning algorithm. ...
We present contrast enhancement to visualize the vasculature by perfusing titanium dioxide particles transcardially into the mouse vascular system. ...
From the imaging data, a 4 mm × 4 mm × 2.7 mm volume was selected for the analysis. Deep learning-based vessel segmentation was performed on 2-D images. ...
doi:10.1117/1.nph.6.3.035004
pmid:31338386
pmcid:PMC6646884
fatcat:2jtfd3knizf6jdjiw36ttmv2v4
2021 Index IEEE Transactions on Multimedia Vol. 23
2021
IEEE transactions on multimedia
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Zhang, W., +, TMM 2021 4483-4490 Learning (artificial intelligence) 3D Face Reconstruction From A Single Image Assisted by 2D Face Images in the Wild. ...
., +, TMM 2021 611-623 Deep Battery Saver: End-to-End Learning for Power Constrained Contrast Enhancement. Yin, J., +, TMM 2021 1049-1059 Deep Single Image Deraining via Modeling Haze-Like Effect. ...
Liao, J., and Kwong, S., Semantic Example Guided Image-to-Image Translation; TMM 2021 1654-1665 Huang, J., see Gong, X., TMM 2021 2820-2832 Huang, J., see Zhong, H., TMM 2021 1264 -1273 Huang, K., see ...
doi:10.1109/tmm.2022.3141947
fatcat:lil2nf3vd5ehbfgtslulu7y3lq
CISP-BMEI 2020 TOC
2020
2020 13th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)
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......................................................................................................110 Depth Image Inpainting via Single Depth Features Learning Junbo Mao, Jupeng Li, Feng Li, Chengkai ...
Graphics and Animation
Multi-face recognition
.....281 Gait Recognition Based on GFHI and Combined Hidden Markov Model Kai Chen, Shiyu Wu, Zhihua Li ...
.....287 Deep learning-based fully automated ...
doi:10.1109/cisp-bmei51763.2020.9263536
fatcat:7ulpvhnt35d2lg5dwzu4kexley
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