Computer Engineering and Applications ›› 2022, Vol. 58 ›› Issue (23): 56-66.DOI: 10.3778/j.issn.1002-8331.2206-0028
• Research Hotspots and Reviews • Previous Articles Next Articles
TANG Yumin, FAN Jing, QU Jinshuai
Online:
2022-12-01
Published:
2022-12-01
唐玉敏,范菁,曲金帅
TANG Yumin, FAN Jing, QU Jinshuai. Overview of Deepfake Generation and Detection[J]. Computer Engineering and Applications, 2022, 58(23): 56-66.
唐玉敏, 范菁, 曲金帅. 深度伪造生成与检测研究综述[J]. 计算机工程与应用, 2022, 58(23): 56-66.
Add to citation manager EndNote|Ris|BibTeX
URL: http://cea.ceaj.org/EN/10.3778/j.issn.1002-8331.2206-0028
[1] MALIK A,KURIBAYASHI M,ABDULLAHI S M,et al.DeepFake detection for human face images and videos:a survey[J].IEEE Access,2022,10:18757-18775. [2] 曹秀莲,汤益华.深度伪造检测技术发展现状研究[J].网络安全技术与应用,2022(5):49-51. CAO Xiulian,TANG Yihua.Research on the development status of deep forgery detection technology[J].Network Security Technology & Application,2022(5):49-51. [3] 刘国柱.深度伪造与国家安全:基于总体国家安全观的视角[J].国际安全研究,2022,40(3):3-31. LIU Guozhu.Deep forgery and national security:from the perspective of overall national security view[J].Journal of International Security Studies,2022,40(3):3-31. [4] MASOOD M,NAWAZ M,MALIK K M,et al.Deepfakes generation and detection:state-of-the-art,open challenges,countermeasures,and way forward[J].Applied Intelligence,2022:1-53. [5] RAMESH A,DHARIWAL P,NICHOL A,et al.Hierarchical text-conditional image generation with clip latents[J].arXiv:2204.06125,2022. [6] ZHOU Y,ZHANG R,CHEN C,et al.Towards language-free training for text-to-image generation[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition,2022:17907-17917. [7] HO J,SAHARIA C,CHAN W,et al.Cascaded diffusion models for high fidelity image generation[J].arXiv:2106. 15282,2021. [8] PARK S,SHIN Y G.Generative convolution layer for image generation[J].Neural Networks,2022,152:370-379. [9] ROMBACH R,BLATTMANN A,LORENZ D,et al.High-resolution image synthesis with latent diffusion models[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition,2022:10684-10695. [10] DENG Y,YANG J,CHEN D,et al.Disentangled and controllable face image generation via 3D imitative-contrastive learning[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition,2020:5154-5163. [11] KIM H,GARRIDO P,TEWARI A,et al.Deep video portraits[J].ACM Transactions on Graphics,2018,37(4):1-14. [12] PRAJWAL K R,MUKHOPADHYAY R,NAMBOODIRI V P,et al.A lip sync expert is all you need for speech to lip generation in the wild[C]//Proceedings of the 28th ACM International Conference on Multimedia,2020:484-492. [13] ZHOU Y,LIM S N.Joint audio-visual deepfake detec-tion[C]//Proceedings of the IEEE/CVF International Conference on Computer Vision,2021:14800-14809. [14] 任延珍,刘晨雨,刘武洋,等.语音伪造及检测技术研究综述[J].信号处理,2021,37(12):2412-2439. REN Yanzhen,LIU Chenyu,LIU Wuyang,et al.A survey on speech forgery and detection[J].Journal of Signal Processing,2021,37(12):2412-2439. [15] 李旭嵘,纪守领,吴春明,等.深度伪造与检测技术综述[J].软件学报,2021,32(2):496-518. LI Xurong,JI Shouling,WU Chunming,et al.Survey on deepfakes and detection techniques[J].Journal of Software,2021,32(2):496-518. [16] 杨帅,乔凯,陈健,等.语音合成及伪造、鉴伪技术综述[J].计算机系统应用,2022,31(7):12-22. YANG Shuai,QIAO Kai,CHEN Jian,et al.Overview on speech synthesis,forgery and detection technology[J].Computer System & Applications,2022,31(7):12-22. [17] ZHANG Y,JIANG F,DUAN Z.One-class learning towards synthetic voice spoofing detection[J].IEEE Signal Processing Letters,2021,28:937-941. [18] 苗晓孔,孙蒙,张雄伟,等.基于参数转换的语音深度伪造及其对声纹认证的威胁评估[J].信息安全学报,2020,5(6):53-59. MIAO Xiaokong,SUN Meng,ZHANG Xiongwei,et al.Deep speech forgery based on parameter transformation and threat assessment to voiceprint authentication[J].Journal of Cyber Security,2020,5(6):53-59. [19] QURESHI A,MEGíAS D,KURIBAYASHI M.Detecting deepfake videos using digital watermarking[C]//2021 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference(APSIPA ASC),2021:1786-1793. [20] SONG L,LIU B,YIN G,et al.TACR-Net:editing on deep video and voice portraits[C]//Proceedings of the 29th ACM International Conference on Multimedia,2021:478-486. [21] CHADHA A,KUMAR V,KASHYAP S,et al.Deepfake:an overview[C]//Proceedings of Second International Conference on Computing,Communications,and Cyber-Security.Singapore:Springer,2021:557-566. [22] ZAKHAROV E,SHYSHEYA A,BURKOV E,et al.Few-shot adversarial learning of realistic neural talking head models[C]//Proceedings of the IEEE/CVF International Conference on Computer Vision,2019:9459-9468. [23] SAMUEL S.A guy made a deepfake app to turn photos of women into nudes.It didn’t go well[EB/OL].[2021-02-18].https://www.vox.com/2019/6/27/18761639/ai?deepfake-deepnude-app-nude-women-porn. [24] THIES J,ZOLLHOFER M,STAMMINGER M,et al.Face2face:real-time face capture and reenactment of RGB videos[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition,2016:2387-2395. [25] HWANG T.Deepfakes:a grounded threat assessment[Z].Georgetown University.Centre for Security and Emerging Technologies,2020. [26] ZOBAED S,RABBY F,HOSSAIN I,et al.DeepFakes:detecting forged and synthetic media content using machine learning[M]//Artificial intelligence in cyber security:impact and implications.Cham:Springer,2021:177-201. [27] LIN C H,CHANG C C,CHEN Y S,et al.Coco-GAN:generation by parts via conditional coordinating[C]//Proceedings of the IEEE/CVF International Conference on Computer Vision,2019:4512-4521. [28] KARRAS T,LAINE S,AITTALA M,et al.Analyzing and improving the image quality of StyleGAN[C]//2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition(CVPR),2020. [29] GANDHI A,JAIN S.Adversarial perturbations fool deepfake detectors[C]//2020 International Joint Conference on Neural Networks(IJCNN),2020:1-8. [30] GENG Z,CAO C,TULYAKOV S.3D guided fine-grained face manipulation[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition,2019:9821-9830. [31] HUANG Y,JUEFEI-XU F,WANG R,et al.FakePolisher:making deepfakes more detection-evasive by shallow reconstruction[C]//Proceedings of the 28th ACM International Conference on Multimedia,2020:1217-1226. [32] ZHANG Y,ZHANG S,HE Y,et al.One-shot face reenact-ment[J].arXiv:1908.03251,2019. [33] KAUR G,SINGH N,KUMAR M.Image forgery techniques:a review[J].Artificial Intelligence Review,2022:1-49. [34] ROSSLER A,COZZOLINO D,VERDOLIVA L,et al.FaceForensics++:learning to detect manipulated facial images[C]//Proceedings of the IEEE/CVF International Conference on Computer Vision,2019:1-11. [35] NAGRANI A,CHUNG J S,ZISSERMAN A.VoxCeleb:a large-scale speaker identification dataset[J].arXiv:1706. 08612,2017. [36] CHUNG J S,NAGRANI A,ZISSERMAN A.VoxCeleb2:deep speaker recognition[J].arXiv:1806.05622,2018. [37] WU Z,KHODABAKHSH A,DEMIROGLU C,et al.SAS:a speaker verification spoofing database containing diverse attacks[C]//2015 IEEE International Conference on Acoustics,Speech and Signal Processing(ICASSP),2015:4440-4444. [38] PANAYOTOV V,CHEN G,POVEY D,et al.LibriSpeech:an ASR corpus based on public domain audio books[C]//2015 IEEE International Conference on Acoustics,Speech and Signal Processing(ICASSP),2015:5206-5210. [39] LORENZO-TRUEBA J,YAMAGISHI J,TODA T,et al.The voice conversion challenge 2018:promoting development of parallel and nonparallel methods[J].arXiv:1804.04262,2018. [40] MYSORE G J.Can we automatically transform speech recorded on common consumer devices in real-world environments into professional production quality speech?—a dataset,insights,and challenges[J].IEEE Signal Processing Letters,2014,22(8):1006-1010. [41] MAZE B,ADAMS J,DUNCAN J A,et al.IARPA Janus Benchmark-C:face dataset and protocol[C]//2018 International Conference on Biometrics(ICB),2018:158-165. [42] R?SSLER A,COZZOLINO D,VERDOLIVA L,et al.Face-Forensics:a large-scale video dataset for forgery detection in human faces[J].arXiv:1803.09179,2018. [43] WU W,ZHANG Y,LI C,et al.ReenactGAN:learning to Reenact faces via boundary transfer[J].arXiv:1807. 11079,2018. [44] SANDERSON C,LOVELL B C.Multi-region probabilistic histograms for robust and scalable identity inference[C]//International Conference on Biometrics.Berlin,Heidelberg:Springer,2009:199-208. [45] PETRIDIS S,STAFYLAKIS T,MA P,et al.Audio-visual speech recognition with a hybrid CTC/attention architecture[C]//2018 IEEE Spoken Language Technology Workshop(SLT),2018:513-520. [46] STERPU G,SAAM C,HARTE N.Attention-based audio-visual fusion for robust automatic speech recognition[C]//Proceedings of the 20th ACM International Conference on Multimodal Interaction,2018:111-115. [47] KARRAS T,LAINE S,AILA T.A style-based generator architecture for generative adversarial networks[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition,2019:4401-4410. [48] LI S,DENG W,DU J P.Reliable crowdsourcing and deep locality-preserving learning for expression recognition in the wild[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition,2017:2852-2861. [49] CAO Q,SHEN L,XIE W,et al.VGGFace2:a dataset for recognising faces across pose and age[C]//2018 13th IEEE International Conference on Automatic Face & Gesture Recognition(FG 2018),2018:67-74. [50] DU S,WARD R.Wavelet-based illumination normalization for face recognition[C]//IEEE International Conference on Image Processing,2005. [51] LE V,BRANDT J,LIN Z,et al.Interactive facial feature localization[C]//European Conference on Computer Vision.Berlin,Heidelberg:Springer,2012:679-692. [52] WANG X,HUANG J,MA S,et al.DeepFake disrupter:the detector of deepfake is my friend[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition,2022:14920-14929. [53] WANG J,WU Z,OUYANG W,et al.M2tr:multi-modal multi-scale transformers for deepfake detection[C]//Proceedings of the 2022 International Conference on Multimedia Retrieval,2022:615-623. [54] NARAYAN K,AGARWAL H,MITTAL S,et al.DeSI:deep-fake source identifier for social media[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition,2022:2858-2867. [55] CHEN L,ZHANG Y,SONG Y,et al.Self-supervised learning of adversarial example:towards good generali-zations for deepfake detection[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition,2022:18710-18719. [56] GUARNERA L,GIUDICE O,NIE?NER M,et al.On the exploitation of deepfake model recognition[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition,2022:61-70. [57] COCCOMINI D A,MESSINA N,GENNARO C,et al.Combining efficientnet and vision transformers for video deepfake detection[C]//International Conference on Image Analysis and Processing.Cham:Springer,2022:219-229. [58] USTUBIOGLU A,USTUBIOGLU B,ULUTAS G.Mel spectrogram based audio forgery detection using CNN[EB/OL].[2022-05-10].https://doi.org/10.21203/rs.3.rs-1828771/v1. [59] CHETTRI B,STOLLER D,MORFI V,et al.Ensemble models for spoofing detection in automatic speaker veri-fication[C]//Proc Interspeech,2019:1033-1037. [60] MOUSSA D,HIRSCH G,RIESS C.Towards unconstrained audio splicing detection and localization with neural networks[J].arXiv:2207.14682,2022. [61] AKHTAR N,SADDIQUE M,ASGHAR K,et al.Digital video tampering detection and localization:review,representations,challenges and algorithm[J].Mathematics,2022,10(2):168. [62] YANG X,LI Y,LYU S.Exposing deep fakes using incon-sistent head poses[C]//ICASSP 2019-2019 IEEE International Conference on Acoustics,Speech and Signal Processing(ICASSP),2019:8261-8265. [63] TEMMERMANS F,BHOWMIK D,PEREIRA F,et al.JPEG fake media:a provenance-based sustainable approach to secure and trustworthy media annotation[C]//Applications of Digital Image Processing XLIV,2021. [64] DEMIR I,CIFTCI U A.Where do deep fakes look? synthetic face detection via gaze tracking[C]//ACM Symposium on Eye Tracking Research and Applications,2021:1-11. [65] QAZI E U H,ZIA T,ALMORJAN A.Deep learning-based digital image forgery detection system[J].Applied Sciences,2022,12(6):2851. [66] JEONG Y,KIM D,MIN S,et al.BiHPF:bilateral highpass filters for robust deepfake detection[C]//Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision,2022:48-57. [67] LIU S,LIAN Z,GU S,et al.Block shuffling learning for deepfake detection[J].arXiv:2202.02819,2022. [68] GUARNERA L,GIUDICE O,BATTIATO S.Deepfake detection by analyzing convolutional traces[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops,2020:666-667. [69] HOODA A,MANGAOKAR N,FENG R,et al.Towards adversarially robust deepfake detection:an ensemble approach[J].arXiv:2202.05687,2022. [70] 裘昊轩,杜彦辉,芦天亮.针对深度伪造的对抗攻击算法动态APGD设计[J/OL].计算机工程与应用:1-11[2022-05-10].http://kns.cnki.net/kcms/detail/11.2127.TP.20220126.1536. 005.html. QIU Haoxuan,DU Yanhui,LU Tianliang.Design of DAPGD,an adversarial attack algorithm against deepfake[J/OL].Computer Engineering and Applications:1-11[2022-05-10].http://kns.cnki.net/kcms/detail/11.2127.TP.20220126.1536. 005.html. [71] 耿鹏志,唐云祁,樊红兴,等.数据增强对深度伪造检测模型的影响研究[J].计算机工程与应用,2021,57(17):10-16. GENG Pengzhi,TANG Yunqi,FAN Hongxing,et al.Research on influence of data enhancement on deepfake detection model[J].Computer Engineering and Applications,2021,57(17):10-16. [72] YAMAGISHI J,TODISCO M,SAHIDULLAH M,et al.Asvspoof 2019:automatic speaker verification spoofing and countermeasures challenge evaluation plan[EB/OL].[2022-05-10].http://www.asvspoof.org/asvspoof2019/asvspoof2019evaluationplan.pdf. [73] DOLHANSKY B,BITTON J,PFLAUM B,et al.The deepfake detection challenge(DFDC) dataset[J].arXiv:2006.07397,2020. [74] LI Y,YANG X,SUN P,et al.Celeb-DF:a large-scale challenging dataset for deepfake forensics[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition,2020:3207-3216. [75] LI Y,CHANG M C,LYU S.In ictu oculi:exposing AI gener-ated fake face videos by detecting eye blinking[J].arXiv:1806.02877,2018. [76] CIFTCI U A,DEMIR I,YIN L.FakeCatcher:detection of synthetic portrait videos using biological signals[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2020:32750816. [77] JIANG L,LI R,WU W,et al.DeeperForensics-1.0:a large-scale dataset for real-world face forgery detection[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition,2020:2889-2898. [78] YU F,SEFF A,ZHANG Y,et al.LSUN:construction of a large-scale image dataset using deep learning with humans in the loop[J].arXiv:1506.03365,2015. [79] LIN T Y,MAIRE M,BELONGIE S,et al.Microsoft COCO:common objects in context[C]//European Conference on Computer Vision.Cham:Springer,2014:740-755. [80] LIU Z,LUO P,WANG X,et al.Deep learning face attributes in the wild[C]//Proceedings of the IEEE International Conference on Computer Vision,2015:3730-3738. |
[1] | LUO Xianglong, GUO Huang, LIAO Cong, HAN Jing, WANG Lixin. Spatiotemporal Short-Term Traffic Flow Prediction Based on Broad Learning System [J]. Computer Engineering and Applications, 2022, 58(9): 181-186. |
[2] | Alim Samat, Sirajahmat Ruzmamat, Maihefureti, Aishan Wumaier, Wushuer Silamu, Turgun Ebrayim. Research on Sentence Length Sensitivity in Neural Network Machine Translation [J]. Computer Engineering and Applications, 2022, 58(9): 195-200. |
[3] | CHEN Yixiao, Alifu·Kuerban, LIN Wenlong, YUAN Xu. CA-YOLOv5 for Crowded Pedestrian Detection [J]. Computer Engineering and Applications, 2022, 58(9): 238-245. |
[4] | FANG Yiqiu, LU Zhuang, GE Junwei. Forecasting Stock Prices with Combined RMSE Loss LSTM-CNN Model [J]. Computer Engineering and Applications, 2022, 58(9): 294-302. |
[5] | GAO Guangshang. Survey on Attention Mechanisms in Deep Learning Recommendation Models [J]. Computer Engineering and Applications, 2022, 58(9): 9-18. |
[6] | JI Meng, HE Qinglong. AdaSVRG: Accelerating SVRG by Adaptive Learning Rate [J]. Computer Engineering and Applications, 2022, 58(9): 83-90. |
[7] | SHI Jie, YUAN Chenxiang, DING Fei, KONG Weixiang. Survey of Building Target Detection in SAR Images [J]. Computer Engineering and Applications, 2022, 58(8): 58-66. |
[8] | XIONG Fengguang, ZHANG Xin, HAN Xie, KUANG Liqun, LIU Huanle, JIA Jionghao. Research on Improved Semantic Segmentation of Remote Sensing [J]. Computer Engineering and Applications, 2022, 58(8): 185-190. |
[9] | YANG Jinfan, WANG Xiaoqiang, LIN Hao, LI Leixiao, YANG Yanyan, LI Kecen, GAO Jing. Review of One-Stage Vehicle Detection Algorithms Based on Deep Learning [J]. Computer Engineering and Applications, 2022, 58(7): 55-67. |
[10] | WANG Bin, LI Xin. Research on Multi-Source Domain Adaptive Algorithm Integrating Dynamic Residuals [J]. Computer Engineering and Applications, 2022, 58(7): 162-166. |
[11] | TAN Shuqiu, TANG Guofang, TU Yuanya, ZHANG Jianxun, GE Panjie. Classroom Monitoring Students Abnormal Behavior Detection System [J]. Computer Engineering and Applications, 2022, 58(7): 176-184. |
[12] | ZHANG Meiyu, LIU Yuehui, HOU Xianghui, QIN Xujia. Automatic Coloring Method for Gray Image Based on Convolutional Network [J]. Computer Engineering and Applications, 2022, 58(7): 229-236. |
[13] | ZHANG Zhuangzhuang, QU Licheng, LI Xiang, ZHANG Minghao, LI Zhaolu. Traffic Flow Prediction with Missing Data Based on Spatial-Temporal Convolutional Neural Networks [J]. Computer Engineering and Applications, 2022, 58(7): 259-265. |
[14] | XU Jie, ZHU Yukun, XING Chunxiao. Research on Financial Trading Algorithm Based on Deep Reinforcement Learning [J]. Computer Engineering and Applications, 2022, 58(7): 276-285. |
[15] | ZHANG Hao, ZHANG Xiaoyu, ZHANG Zhenyou, LI Wei. Summary of Intrusion Detection Models Based on Deep Learning [J]. Computer Engineering and Applications, 2022, 58(6): 17-28. |
Viewed | ||||||
Full text |
|
|||||
Abstract |
|
|||||