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Identity-Aware Deep Face Hallucination via Adversarial Face Verification [article]

Hadi Kazemi, Fariborz Taherkhani, Nasser M. Nasrabadi
<span title="2019-09-17">2019</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
In this paper, we address the problem of face hallucination by proposing a novel multi-scale generative adversarial network (GAN) architecture optimized for face verification.  ...  Second, we incorporate a face verifier with the original GAN discriminator and propose a novel discriminator which learns to discriminate different identities while distinguishing fake generated HR face  ...  In summary, our framework has three major contributions: • We propose a novel identity-aware GAN for face super resolution which enable us to hallucinate photorealistic HR faces while preserving the face  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1909.08130v1">arXiv:1909.08130v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/k4xkuinqj5g4zd4s5huplebfyy">fatcat:k4xkuinqj5g4zd4s5huplebfyy</a> </span>
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Cross-spectral Face Completion for NIR-VIS Heterogeneous Face Recognition [article]

Ran He, Jie Cao, Lingxiao Song, Zhenan Sun, Tieniu Tan
<span title="2019-02-10">2019</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
One UV loss, two adversarial losses and one pixel loss are imposed to ensure synthesis results.  ...  A warping procedure is developed to integrate the two components into an end-to-end deep network.  ...  The performance of face verification is evaluated by 'recognition via generation': NIR faces are first processed by our NIR-VIS face completion method and then fed to the Light CNN for matching.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1902.03565v1">arXiv:1902.03565v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/3u4ihwcotvcy7bfrktqxwdt554">fatcat:3u4ihwcotvcy7bfrktqxwdt554</a> </span>
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Pose-Guided Photorealistic Face Rotation

Yibo Hu, Xiang Wu, Bing Yu, Ran He, Zhenan Sun
<span title="">2018</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ilwxppn4d5hizekyd3ndvy2mii" style="color: black;">2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition</a> </i> &nbsp;
Besides the generator and conditional adversarial loss, CAPG-GAN further employs identity preserving loss and total variation regularization to preserve identity information and refine local textures respectively  ...  We propose a novel Couple-Agent Pose-Guided Generative Adversarial Network (CAPG-GAN) to generate both neutral and profile head pose face images.  ...  [26] introduce adversarial learning into a cross-spectral face hallucination, facilitating heterogeneous face recognition via generation.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/cvpr.2018.00876">doi:10.1109/cvpr.2018.00876</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/cvpr/HuWYHS18.html">dblp:conf/cvpr/HuWYHS18</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/trl5znmxznfg7fcyvdvspbauee">fatcat:trl5znmxznfg7fcyvdvspbauee</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200318230150/http://openaccess.thecvf.com/content_cvpr_2018/papers/Hu_Pose-Guided_Photorealistic_Face_CVPR_2018_paper.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/39/ed/39ed31ced75e6151dde41944a47b4bdf324f922b.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/cvpr.2018.00876"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Face Hallucination with Finishing Touches [article]

Yang Zhang, Ivor W.Tsang, Jun Li, Ping Liu, Xiaobo Lu, Xin Yu
<span title="2020-10-28">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
In this paper, we present a novel Vivid Face Hallucination Generative Adversarial Network (VividGAN) for simultaneously super-resolving and frontalizing tiny non-frontal face images.  ...  The Coarse-D enforces the coarsely hallucinated faces to be upright and complete while the Fine-D focuses on the fine hallucinated ones for sharper details.  ...  High-quality face images are one of the most discriminative biometric cues to provide identity verification.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2002.03308v2">arXiv:2002.03308v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/dm6lmpkvtnfdnoi2byk5qrb6ve">fatcat:dm6lmpkvtnfdnoi2byk5qrb6ve</a> </span>
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2021 Index IEEE Transactions on Image Processing Vol. 30

<span title="">2021</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/dhlhr4jqkbcmdbua2ca45o7kru" style="color: black;">IEEE Transactions on Image Processing</a> </i> &nbsp;
Chen, X., +, TIP 2021 3041-3055 Multitask Identity-Aware Image Steganography via Minimax Optimization.  ...  ., +, TIP 2021 4610-4621 F 3 A-GAN: Facial Flow for Face Animation With Generative Adversarial Networks. Wu, X., +, TIP 2021 8658-8670 Face Hallucination With Finishing Touches.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tip.2022.3142569">doi:10.1109/tip.2022.3142569</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/z26yhwuecbgrnb2czhwjlf73qu">fatcat:z26yhwuecbgrnb2czhwjlf73qu</a> </span>
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Pro-UIGAN: Progressive Face Hallucination from Occluded Thumbnails [article]

Yang Zhang, Xin Yu, Xiaobo Lu, Ping Liu
<span title="2022-04-01">2022</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
In this paper, we study the task of hallucinating an authentic high-resolution (HR) face from an occluded thumbnail.  ...  Our multi-stage hallucination network super-resolves and inpaints occluded LR faces in a coarse-to-fine manner, thus reducing unwanted blurriness and artifacts significantly.  ...  INTRODUCTION With the increasing demand for social security, nonintrusive identity verification has become indispensable in daily life.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2108.00602v6">arXiv:2108.00602v6</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/o7pkr3vbxnbqlis5cqucoy2hlq">fatcat:o7pkr3vbxnbqlis5cqucoy2hlq</a> </span>
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Joint Face Hallucination and Deblurring via Structure Generation and Detail Enhancement [article]

Yibing Song, Jiawei Zhang, Lijun Gong, Shengfeng He, Linchao Bao, Jinshan Pan, Qingxiong Yang, Ming-Hsuan Yang
<span title="2018-11-22">2018</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
We first propose a facial component guided deep Convolutional Neural Network (CNN) to restore a coarse face image, which is denoted as the base image where the facial component is automatically generated  ...  We further develop a novel exemplar-based detail enhancement algorithm via facial component matching.  ...  It predicts face images via extremely low-resolution inputs where the facial identity is hard to identify.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1811.09019v1">arXiv:1811.09019v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/zhaokqukyjfl5ocamyz67cbd4i">fatcat:zhaokqukyjfl5ocamyz67cbd4i</a> </span>
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2021 International Joint Conference on Biometrics (IJCB 2021) - Event schedule [Table of Contents]

<span title="">2021</span> <i title="IEEE"> 2021 IEEE International Joint Conference on Biometrics (IJCB) </i> &nbsp;
Specifically, the audience should know basic concepts in facial analysis, deep learning, and optimization. We think almost all participants of IJCB have the prerequisite knowledge.  ...  To name a few, facial recognition and analysis methods may be subject to bias and uncertainty, biometrics systems can be failed under adversarial attacks, imagery of people can maliciously tamper, and  ...  Learning and Data Augmentation for Kinship Verification  4:00pm -4:10pm, Aug 5  Online  (S) Face Sketch Synthesis via Semantic-Driven Generative Adversarial Network  4:10pm -4:20pm, Aug 5  Online  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/ijcb52358.2021.9521653">doi:10.1109/ijcb52358.2021.9521653</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/cywo2fo27rauvbpxdj5qx7ykui">fatcat:cywo2fo27rauvbpxdj5qx7ykui</a> </span>
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Deep Face Recognition: A Survey [article]

Mei Wang, Weihong Deng
<span title="2020-08-01">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Since then, deep learning technique, characterized by the hierarchical architecture to stitch together pixels into invariant face representation, has dramatically improved the state-of-the-art performance  ...  Second, the related face processing methods are categorized into two classes: "one-to-many augmentation" and "many-to-one normalization".  ...  [240] embedded cross-spectral face hallucination and discriminative feature learning into an end-to-end adversarial network.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1804.06655v9">arXiv:1804.06655v9</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/i2yxh7bf45attlfjd3akyc65me">fatcat:i2yxh7bf45attlfjd3akyc65me</a> </span>
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Recent Advances in Deep Learning Techniques for Face Recognition

Md. Tahmid Hasan Fuad, Awal Ahmed Fime, Delowar Sikder, Md. Akil Raihan Iftee, Jakaria Rabbi, Mabrook S. Al-Rakhami, Abdu Gumae, Ovishake Sen, Mohtasim Fuad, Md. Nazrul Islam
<span title="">2021</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/q7qi7j4ckfac7ehf3mjbso4hne" style="color: black;">IEEE Access</a> </i> &nbsp;
INDEX TERMS Deep learning, face recognition, artificial neural network, convolutional neural network, auto encoder, generative adversarial network, deep belief network, reinforcement learning. 99112 This  ...  Deep FR systems benefit from the hierarchical architecture of the DL methods to learn discriminative face representation.  ...  For video face recognition, an attention-aware deep reinforcement learning (ADRL) [119] was proposed.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2021.3096136">doi:10.1109/access.2021.3096136</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/g5sftnugunbczppu56dbymlhra">fatcat:g5sftnugunbczppu56dbymlhra</a> </span>
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Recent Advances in Deep Learning Techniques for Face Recognition [article]

Md. Tahmid Hasan Fuad, Awal Ahmed Fime, Delowar Sikder, Md. Akil Raihan Iftee, Jakaria Rabbi, Mabrook S. Al-rakhami, Abdu Gumae, Ovishake Sen, Mohtasim Fuad, Md. Nazrul Islam
<span title="2021-03-18">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Deep FR systems benefit from the hierarchical architecture of the DL methods to learn discriminative face representation.  ...  In recent years, researchers have proposed many deep learning (DL) methods for various tasks, and particularly face recognition (FR) made an enormous leap using these techniques.  ...  the article was to recover the identity-aware information for LRFR. LR faces increase the angle and magnitude gap of the features.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2103.10492v1">arXiv:2103.10492v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/h526swzntjgmlcjmwnuidqg44u">fatcat:h526swzntjgmlcjmwnuidqg44u</a> </span>
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2020 Index IEEE Transactions on Image Processing Vol. 29

<span title="">2020</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/dhlhr4jqkbcmdbua2ca45o7kru" style="color: black;">IEEE Transactions on Image Processing</a> </i> &nbsp;
., +, TIP 2020 3270-3281 Face Hallucination Using Cascaded Super-Resolution and Identity Priors.  ...  ., +, TIP 2020 3270-3281 Face Hallucination Using Cascaded Super-Resolution and Identity Priors. Grm, K., +, TIP 2020 2150-2165 Facial Expression Recognition in Videos Using Dynamic Kernels.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tip.2020.3046056">doi:10.1109/tip.2020.3046056</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/24m6k2elprf2nfmucbjzhvzk3m">fatcat:24m6k2elprf2nfmucbjzhvzk3m</a> </span>
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Table of contents

<span title="">2020</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/dhlhr4jqkbcmdbua2ca45o7kru" style="color: black;">IEEE Transactions on Image Processing</a> </i> &nbsp;
Nie 2139 Face Hallucination Using Cascaded Super-Resolution and Identity Priors ....... K. Grm, W. J. Scheirer, and V.  ...  Smolic 1285 Deep Heterogeneous Hashing for Face Video Retrieval ....................... S. Qiao, R. Wang, S. Shan, and X.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tip.2019.2940372">doi:10.1109/tip.2019.2940372</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/h23ul2rqazbstcho46uv3lunku">fatcat:h23ul2rqazbstcho46uv3lunku</a> </span>
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Omni-supervised Facial Expression Recognition via Distilled Data [article]

Ping Liu, Yunchao Wei, Zibo Meng, Weihong Deng, Joey Tianyi Zhou, Yi Yang
<span title="2021-12-09">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Most recently, deep learning based methods have shown promising for facial expression recognition.  ...  Particularly, a new dataset is firstly constructed using a primitive model trained on a small number of labeled samples to select samples with high confidence scores from a face dataset, i.e., MS-Celeb  ...  Since CK+ does not provide official train- face verification.  ... 
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Facial Attribute Capsules for Noise Face Super Resolution [article]

Jingwei Xin, Nannan Wang, Xinrui Jiang, Jie Li, Xinbo Gao, Zhifeng Li
<span title="2020-02-16">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Extensive benchmark experiments show that our method achieves superior hallucination results and outperforms state-of-the-art for very low resolution (LR) noise face image super resolution.  ...  The diverse FACs could better combine the face prior information to generate the face images with fine-grained semantic attributes.  ...  In order to corroborate the real benefit of the proposal, we further perform the face verification experiments via the Arcface [41] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2002.06518v1">arXiv:2002.06518v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/zs6355bui5aqpfric55kmv5rry">fatcat:zs6355bui5aqpfric55kmv5rry</a> </span>
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