Cybenko, A.K.,
Cybenko, G.,
AI and Fake News,
IEEE_Int_Sys(33), No. 5, Sep. 2018, pp. 1-5.
IEEE DOI
1901
Cultural differences, Intelligent systems,
Social network services, Psychology, Economics, Software
BibRef
de Rezende, E.R.S.[Edmar R.S.],
Ruppert, G.C.S.[Guilherme C.S.],
Theóphilo, A.[Antônio],
Tokuda, E.K.[Eric K.],
Carvalho, T.[Tiago],
Exposing computer generated images by using deep convolutional neural
networks,
SP:IC(66), 2018, pp. 113-126.
Elsevier DOI
1806
Digital forensics, CG detection, Deep learning,
Transfer learning, Fake news
BibRef
Reis, J.C.S.,
Correia, A.,
Murai, F.,
Veloso, A.,
Benevenuto, F.,
Cambria, E.,
Supervised Learning for Fake News Detection,
IEEE_Int_Sys(34), No. 2, March 2019, pp. 76-81.
IEEE DOI
1906
Feature extraction, Facebook, Data mining, IP networks,
Radio frequency, Affective computing
BibRef
Greengard, S.[Samuel],
Will Deepfakes Do Deep Damage?,
CACM(63), No. 1, January 2020, pp. 17-19.
DOI Link
1912
News item.
BibRef
Strickland, E.,
Facebook takes on deepfakes,
Spectrum(57), No. 01, January 2020, pp. 40-57.
IEEE DOI
2001
They are everywhere, they are high quality.
BibRef
Babaguchi, N.[Noboru],
Echizen, I.[Isao],
Yamagishi, J.[Junichi],
Nitta, N.[Naoko],
Nakashima, Y.[Yuta],
Nakamura, K.[Kazuaki],
Kono, K.[Kazuhiro],
Fang, F.M.[Fu-Ming],
Myojin, S.[Seiko],
Kuang, Z.Z.[Zhen-Zhong],
Nguyen, H.H.[Huy H.],
Tieu, N.D.T.[Ngoc-Dung T.],
Preventing Fake Information Generation Against Media Clone Attacks,
IEICE(E104-D), No. 1, January 2021, pp. 2-11.
WWW Link.
2101
BibRef
de Oliveira, N.R.,
Medeiros, D.S.V.,
Mattos, D.M.F.,
A Sensitive Stylistic Approach to Identify Fake News on Social
Networking,
SPLetters(27), 2020, pp. 1250-1254.
IEEE DOI
2007
Fake news detection, one-class SVM
BibRef
Johnson, D.G.[Deborah G.],
Diakopoulos, N.[Nicholas],
What To Do About Deepfakes,
CACM(64), No. 1, January 2021, pp. 33-35.
DOI Link
2103
Seeking to reap the positive uses of synthetic media while minimizing
or preventing negative societal impact.
BibRef
Kamboj, M.,
Hessler, C.,
Asnani, P.,
Riani, K.,
Abouelenien, M.,
Multimodal Political Deception Detection,
MultMedMag(28), No. 1, January 2021, pp. 94-102.
IEEE DOI
2104
Feature extraction, Videos, Linguistics, Visualization, Psychology,
Task analysis
BibRef
Caldelli, R.[Roberto],
Galteri, L.[Leonardo],
Amerini, I.[Irene],
del Bimbo, A.[Alberto],
Optical Flow based CNN for detection of unlearnt deepfake
manipulations,
PRL(146), 2021, pp. 31-37.
Elsevier DOI
2105
BibRef
Earlier: A3, A2, A1, A4:
Deepfake Video Detection through Optical Flow Based CNN,
HBU19(1205-1207)
IEEE DOI
2004
Deepfake manipulations, Optical Flow, Video forensics, CNN.
convolutional neural nets, image classification, image sequences,
learning (artificial intelligence), video signal processing.
BibRef
Xu, Z.P.[Zhao-Peng],
Liu, J.R.[Jia-Rui],
Lu, W.[Wei],
Xu, B.[Bozhi],
Zhao, X.F.[Xian-Feng],
Li, B.[Bin],
Huang, J.W.[Ji-Wu],
Detecting facial manipulated videos based on set convolutional neural
networks,
JVCIR(77), 2021, pp. 103119.
Elsevier DOI
2106
Digital video forensics, Deepfake,
Set convolutional neural network, Set reduce
BibRef
Shang, Z.H.[Zhi-Hua],
Xie, H.T.[Hong-Tao],
Zha, Z.J.[Zheng-Jun],
Yu, L.Y.[Ling-Yun],
Li, Y.[Yan],
Zhang, Y.D.[Yong-Dong],
PRRNet: Pixel-Region relation network for face forgery detection,
PR(116), 2021, pp. 107950.
Elsevier DOI
2106
Face forgery detection, Forgery localization,
Inconsistency detection, Relation learning
BibRef
Alharbi, A.[Ahmed],
Dong, H.[Hai],
Yi, X.[Xun],
Tari, Z.[Zahir],
Khalil, I.[Ibrahim],
Social Media Identity Deception Detection: A Survey,
Surveys(54), No. 3, April 2021, pp. xx-yy.
DOI Link
2106
Identity deception, social botnet, Sybil, sockpuppet,
identity theft, identity cloning, detection techniques, fake profile
BibRef
Ferrara, M.[Matteo],
Franco, A.[Annalisa],
Maltoni, D.[Davide],
Face morphing detection in the presence of printing/scanning and
heterogeneous image sources,
IET-Bio(10), No. 3, 2021, pp. 290-303.
DOI Link
2106
BibRef
Groh, M.[Matthew],
Epstein, Z.[Ziv],
Obradovich, N.[Nick],
Cebrian, M.[Manuel],
Rahwan, I.[Iyad],
Human Detection of Machine-Manipulated Media,
CACM(64), No. 10, October 2021, pp. 40-47.
DOI Link
2109
BibRef
Kim, G.[Gihwan],
Ko, Y.J.[Young-Joong],
Effective fake news detection using graph and summarization
techniques,
PRL(151), 2021, pp. 135-139.
Elsevier DOI
2110
Fake news detection, Graph neural networks, Summarization, Deep neural networks
BibRef
Yu, P.[Peipeng],
Xia, Z.H.[Zhi-Hua],
Fei, J.W.[Jian-Wei],
Lu, Y.J.[Yu-Jiang],
A Survey on Deepfake Video Detection,
IET-Bio(10), No. 6, 2021, pp. 607-624.
DOI Link
2110
Survey, Deepfakes.
BibRef
Sabitha, R.,
Aruna, A.,
Karthik, S.,
Shanthini, J.,
Enhanced model for fake image detection (EMFID) using convolutional
neural networks with histogram and wavelet based feature extractions,
PRL(152), 2021, pp. 195-201.
Elsevier DOI
2112
Fake image detection, Image features,
Histogram based feature extraction,
Convolutional neural networks (CNN)
BibRef
Kong, C.Q.[Chen-Qi],
Chen, B.L.[Bao-Liang],
Yang, W.H.[Wen-Han],
Li, H.L.[Hao-Liang],
Chen, P.L.[Pei-Lin],
Wang, S.Q.[Shi-Qi],
Appearance Matters, So Does Audio: Revealing the Hidden Face via
Cross-Modality Transfer,
CirSysVideo(32), No. 1, January 2022, pp. 423-436.
IEEE DOI
2201
Faces, Videos, Information integrity, Face recognition, Training,
Generative adversarial networks, Testing, Deepfake, cross modality, fake face
BibRef
Choi, H.[Hyewon],
Ko, Y.J.[Young-Joong],
Effective fake news video detection using domain knowledge and
multimodal data fusion on youtube,
PRL(154), 2022, pp. 44-52.
Elsevier DOI
2202
Fake news video detection, Domain knowledge, Multimodal data,
Deep neural networks
BibRef
Hu, J.[Juan],
Liao, X.[Xin],
Wang, W.[Wei],
Qin, Z.[Zheng],
Detecting Compressed Deepfake Videos in Social Networks Using
Frame-Temporality Two-Stream Convolutional Network,
CirSysVideo(32), No. 3, March 2022, pp. 1089-1102.
IEEE DOI
2203
Videos, Information integrity, Feature extraction, Streaming media,
Faces, Forensics, Social networking (online), Video forensics,
temporality-level stream
BibRef
Nguyen, V.H.[Van-Hoang],
Sugiyama, K.[Kazunari],
Nakov, P.[Preslav],
Kan, M.Y.[Min-Yen],
FANG: Leveraging Social Context for Fake News Detection Using Graph
Representation,
CACM(65), No. 4, April 2022, pp. 124-132.
DOI Link
2204
BibRef
Zhang, X.K.[Xiao-Kang],
Zhu, Y.L.[Yuan-Lue],
Chen, W.T.[Wen-Ting],
Liu, W.S.[Wen-Shuang],
Shen, L.L.[Lin-Lin],
Gated SwitchGAN for Multi-Domain Facial Image Translation,
MultMed(24), No. 2022, pp. 1990-2003.
IEEE DOI
2204
Switches, Generators, Logic gates, Faces, Control systems,
Feature extraction, Task analysis, GANs, Image translation,
Attribute intensity control
BibRef
Li, W.C.[Wei-Chuang],
He, P.S.[Pei-Song],
Li, H.L.[Hao-Liang],
Wang, H.X.[Hong-Xia],
Zhang, R.M.[Rui-Mei],
Detection of GAN-Generated Images by Estimating Artifact Similarity,
SPLetters(29), No. 2022, pp. 862-866.
IEEE DOI
2204
Prototypes, Generative adversarial networks, Training,
Feature extraction, Testing, Optimization, Task analysis,
artifact similarity estimation
BibRef
Wang, Z.[Zhi],
Guo, Y.[Yiwen],
Zuo, W.M.[Wang-Meng],
Deepfake Forensics via an Adversarial Game,
IP(31), 2022, pp. 3541-3552.
IEEE DOI
2205
Training, Forgery, Faces, Task analysis, Predictive models,
Face recognition, Robustness, Deepfake forensics,
generalization ability
BibRef
Amorese, T.[Terry],
Cuciniello, M.[Marialucia],
Vinciarelli, A.[Alessandro],
Cordasco, G.[Gennaro],
Esposito, A.[Anna],
Synthetic vs Human Emotional Faces:
What Changes in Humans' Decoding Accuracy,
HMS(52), No. 3, June 2022, pp. 390-399.
IEEE DOI
2205
Faces, Emotion recognition, Decoding, Face recognition, Aging,
Task analysis, Portable computers, Assistive technology,
human-computer interaction
BibRef
Pu, W.[Wenbo],
Hu, J.[Jing],
Wang, X.[Xin],
Li, Y.Z.[Yue-Zun],
Hu, S.[Shu],
Zhu, B.[Bin],
Song, R.[Rui],
Song, Q.[Qi],
Wu, X.[Xi],
Lyu, S.W.[Si-Wei],
Learning a deep dual-level network for robust DeepFake detection,
PR(130), 2022, pp. 108832.
Elsevier DOI
2206
DeepFake detection, Multitask learning, Imbalanced learning, AUC optimization
BibRef
Wei, P.F.[Peng-Fei],
Wu, F.[Fei],
Sun, Y.[Ying],
Zhou, H.[Hong],
Jing, X.Y.[Xiao-Yuan],
Modality and Event Adversarial Networks for Multi-Modal Fake News
Detection,
SPLetters(29), 2022, pp. 1382-1386.
IEEE DOI
2206
Feature extraction, Fake news, Blogs, Image reconstruction,
Generators, Social networking (online), Deep learning,
multi-modal generator
BibRef
Mishima, K.[Ken],
Yamana, H.[Hayato],
A Survey on Explainable Fake News Detection,
IEICE(E105-D), No. 7, July 2022, pp. 1249-1257.
WWW Link.
2207
Survey, Fake News.
BibRef
Juefei-Xu, F.[Felix],
Wang, R.[Run],
Huang, Y.H.[Yi-Hao],
Guo, Q.[Qing],
Ma, L.[Lei],
Liu, Y.[Yang],
Countering Malicious DeepFakes: Survey, Battleground, and Horizon,
IJCV(130), No. 7, July 2022, pp. 1678-1734.
Springer DOI
2207
BibRef
Li, P.G.[Pei-Guang],
Sun, X.[Xian],
Yu, H.F.[Hong-Feng],
Tian, Y.[Yu],
Yao, F.L.[Fang-Long],
Xu, G.L.[Guang-Luan],
Entity-Oriented Multi-Modal Alignment and Fusion Network for Fake
News Detection,
MultMed(24), 2022, pp. 3455-3468.
IEEE DOI
2207
Feature extraction, Visualization, Task analysis,
Heuristic algorithms, Social networking (online), Semantics, Sun,
multi-modal
BibRef
Yang, X.[Xiao],
Liu, S.[Shilong],
Dong, Y.P.[Yin-Peng],
Su, H.[Hang],
Zhang, L.[Lei],
Zhu, J.[Jun],
Towards generalizable detection of face forgery via self-guided
model-agnostic learning,
PRL(160), 2022, pp. 98-104.
Elsevier DOI
2208
DeepFake, Face forgery detection, Face generation
BibRef
Edwards, J.[John],
Applying Signal Processing to Opposite Sides of Imaging: Separate
European research projects are focusing on aspects of completely real
and entirely fake images [Special Reports],
SPMag(39), No. 5, September 2022, pp. 18-20.
IEEE DOI
2209
Neuroimaging, Brain models, Image processing, Distortion,
Photography, Signal processing algorithms
BibRef
Wang, R.[Renying],
Yang, Z.[Zhen],
You, W.[Weike],
Zhou, L.[Linna],
Chu, B.[Beilin],
Fake Face Images Detection and Identification of Celebrities Based on
Semantic Segmentation,
SPLetters(29), 2022, pp. 2018-2022.
IEEE DOI
2210
Semantics, Faces, Detectors, Image segmentation, Forgery,
Task analysis, Feature extraction, semantic segmentation
BibRef
Nguyen, T.T.[Thanh Thi],
Nguyen, Q.V.H.[Quoc Viet Hung],
Nguyen, D.T.[Dung Tien],
Nguyen, D.T.[Duc Thanh],
Huynh-The, T.[Thien],
Nahavandi, S.[Saeid],
Nguyen, T.T.[Thanh Tam],
Pham, Q.V.[Quoc-Viet],
Nguyen, C.M.[Cuong M.],
Deep learning for deepfakes creation and detection: A survey,
CVIU(223), 2022, pp. 103525.
Elsevier DOI
2210
Deepfakes, Face manipulation, Artificial intelligence,
Deep learning, Autoencoders, GAN, Forensics, Survey
BibRef
Peng, F.[Fei],
Yin, L.P.[Li-Ping],
Long, M.[Min],
BDC-GAN: Bidirectional Conversion Between Computer-Generated and
Natural Facial Images for Anti-Forensics,
CirSysVideo(32), No. 10, October 2022, pp. 6657-6670.
IEEE DOI
2210
Forensics, Feature extraction, Generative adversarial networks,
Image color analysis, Image coding,
generative adversarial network
BibRef
Singhal, S.[Shivangi],
Kaushal, R.[Rishabh],
Shah, R.R.[Rajiv Ratn],
Kumaraguru, P.[Ponnurangam],
Fake News in India: Scale, Diversity, Solution, and Opportunities,
CACM(65), No. 11, November 2022, pp. 80-81.
DOI Link
2211
BibRef
Chu, B.[Beilin],
You, W.[Weike],
Yang, Z.[Zhen],
Zhou, L.[Linna],
Wang, R.[Renying],
Protecting World Leader Using Facial Speaking Pattern Against
Deepfakes,
SPLetters(29), 2022, pp. 2078-2082.
IEEE DOI
2211
Lips, Deepfakes, Feature extraction, Faces, Gold, Transformers,
Detectors, Face manipulation detection,
speech pattern recognition
BibRef
Tan, Z.C.[Zi-Chang],
Yang, Z.C.[Zhi-Chao],
Miao, C.T.[Chang-Tao],
Guo, G.D.[Guo-Dong],
Transformer-Based Feature Compensation and Aggregation for DeepFake
Detection,
SPLetters(29), 2022, pp. 2183-2187.
IEEE DOI
2212
Feature extraction, Deepfakes, Current transformers,
Frequency-domain analysis, Aggregates, Forgery, Standards, deep learning
BibRef
Nirkin, Y.[Yuval],
Keller, Y.[Yosi],
Hassner, T.[Tal],
FSGANv2: Improved Subject Agnostic Face Swapping and Reenactment,
PAMI(45), No. 1, January 2023, pp. 560-575.
IEEE DOI
2212
BibRef
Earlier:
FSGAN: Subject Agnostic Face Swapping and Reenactment,
ICCV19(7183-7192)
IEEE DOI
2004
Faces, Generators, Videos, Image segmentation,
Rendering (computer graphics), Training, Face swapping, deep learning.
face recognition, image colour analysis, image sequences,
interpolation, optimisation, recurrent neural nets, Hair
BibRef
Guo, Z.Q.[Zhi-Qing],
Yang, G.[Gaobo],
Wang, D.[Dewang],
Zhang, D.Y.[Deng-Yong],
A data augmentation framework by mining structured features for fake
face image detection,
CVIU(226), 2023, pp. 103587.
Elsevier DOI
2212
Deepfake detection, Data augmentation, Face forgery detection,
Structured forgery clues
BibRef
Chen, H.[Han],
Li, Y.[Yuezun],
Lin, D.D.[Dong-Dong],
Li, B.[Bin],
Wu, J.Q.[Jun-Qiang],
Watching the BiG artifacts:
Exposing DeepFake videos via Bi-granularity artifacts,
PR(135), 2023, pp. 109179.
Elsevier DOI
2212
Multimedia forensics, Deepfake detection,
Granularity artifacts, Multi-task learning
BibRef
Yuan, Y.[Yike],
Fu, X.[Xinghe],
Wang, G.[Gaoang],
Li, Q.M.[Qi-Ming],
Li, X.[Xi],
Forgery-Domain-Supervised Deepfake Detection With Non-Negative
Constraint,
SPLetters(29), 2022, pp. 2512-2516.
IEEE DOI
2301
Faces, Forgery, Deepfakes, Task analysis, Feature extraction, Crops,
Training, Classifier regularization, deepfake detection,
feature integration
BibRef
Chen, H.[Han],
Lin, Y.Z.[Yu-Zhen],
Li, B.[Bin],
Tan, S.Q.[Shun-Quan],
Learning Features of Intra-Consistency and Inter-Diversity: Keys
Toward Generalizable Deepfake Detection,
CirSysVideo(33), No. 3, March 2023, pp. 1468-1480.
IEEE DOI
2303
Deepfakes, Task analysis, Forgery, Faces, Feature extraction,
Data models, Transformers, Deepfake detection, generalization
BibRef
Hua, Y.Y.[Ying-Ying],
Shi, R.X.[Rui-Xin],
Wang, P.[Pengju],
Ge, S.M.[Shi-Ming],
Learning Patch-Channel Correspondence for Interpretable Face Forgery
Detection,
IP(32), 2023, pp. 1668-1680.
IEEE DOI
2303
Forgery, Faces, Feature extraction, Deep learning, Decorrelation,
Visualization, Task analysis, Face forgery detection,
patch-channel correspondence
BibRef
Agarwal, A.[Aayushi],
Agarwal, A.[Akshay],
Sinha, S.[Sayan],
Vatsa, M.[Mayank],
Singh, R.[Richa],
MD-CSDNetwork: Multi-Domain Cross Stitched Network for Deepfake
Detection,
FG21(1-8)
IEEE DOI
2303
Frequency-domain analysis, Face recognition,
Gesture recognition, Media, Benchmark testing, Feature extraction
BibRef
Klomp, S.R.[Sander R.],
van Rijn, M.[Matthew],
Wijnhoven, R.G.J.[Rob G.J.],
Snoek, C.G.M.[Cees G.M.],
de With, P.H.N.[Peter H.N.],
Safe Fakes: Evaluating Face Anonymizers for Face Detectors,
FG21(1-8)
IEEE DOI
2303
Training, Measurement, Degradation, Visualization, Face recognition,
Detectors, Generative adversarial networks
BibRef
Yoo, S.M.[Sahng-Min],
Choi, T.M.[Tae-Min],
Choi, J.W.[Jae-Woo],
Kim, J.H.[Jong-Hwan],
FastSwap: A Lightweight One-Stage Framework for Real-Time Face
Swapping,
WACV23(3547-3556)
IEEE DOI
2302
Training, Costs, Switches, Manuals, Control systems, Real-time systems,
Decoding, Algorithms: Biometrics, face, gesture, body pose,
Virtual/augmented reality
BibRef
Rosberg, F.[Felix],
Aksoy, E.E.[Eren Erdal],
Alonso-Fernandez, F.[Fernando],
Englund, C.[Cristofer],
FaceDancer: Pose- and Occlusion-Aware High Fidelity Face Swapping,
WACV23(3443-3452)
IEEE DOI
WWW Link.
2302
You can already play around with it over at Hugging Face:
WWW Link. The source code is available at:
WWW Link. Adaptation models, Visualization, Image coding, Shape, Fuses,
Computational modeling, Algorithms: Biometrics, face, gesture
BibRef
Agarwal, A.[Aditya],
Sen, B.[Bipasha],
Mukhopadhyay, R.[Rudrabha],
Namboodiri, V.[Vinay],
Jawahar, C.V.[C V],
FaceOff: A Video-to-Video Face Swapping System,
WACV23(3484-3493)
IEEE DOI
2302
Industries, Costing, Motion pictures, Computational efficiency,
Task analysis, Faces, Algorithms: Computational photography,
Commercial/retail
BibRef
Sun, Y.Y.[Yu-Yang],
Zhang, Z.Y.[Zhi-Yong],
Echizen, I.[Isao],
Nguyen, H.H.[Huy H.],
Qiu, C.Z.[Chang-Zhen],
Sun, L.[Lu],
Face Forgery Detection Based on Facial Region Displacement Trajectory
Series,
BioAttack23(633-642)
IEEE DOI
2302
Deepfakes, Law, Time series analysis, Logic gates, Media, Forgery, Trajectory
BibRef
Mittal, T.[Trisha],
Sinha, R.[Ritwik],
Swaminathan, V.[Viswanathan],
Collomosse, J.[John],
Manocha, D.[Dinesh],
Video Manipulations Beyond Faces:
A Dataset with Human-Machine Analysis,
BioAttack23(643-652)
IEEE DOI
2302
Deepfakes, Conferences, Artificial intelligence,
Detection algorithms, Faces, Man-machine systems
BibRef
Xu, Y.[Ying],
Raja, K.[Kiran],
Verdoliva, L.[Luisa],
Pedersen, M.[Marius],
Learning Pairwise Interaction for Generalizable DeepFake Detection,
Explain-Bio23(1-11)
IEEE DOI
2302
Deepfakes, Visualization, Conferences, Decision making, Detectors, Color
BibRef
Agarwal, S.[Shruti],
Hu, L.W.[Li-Wen],
Ng, E.[Evonne],
Darrell, T.J.[Trevor J.],
Li, H.[Hao],
Rohrbach, A.[Anna],
Watch Those Words: Video Falsification Detection Using
Word-Conditioned Facial Motion,
WACV23(4699-4708)
IEEE DOI
2302
Training, Deepfakes, Visualization, Biometrics (access control),
Forensics, Semantics, Applications: Social good, Biometrics, face,
body pose
BibRef
Liu, B.P.[Bao-Ping],
Liu, B.[Bo],
Ding, M.[Ming],
Zhu, T.Q.[Tian-Qing],
Yu, X.[Xin],
TI2Net: Temporal Identity Inconsistency Network for Deepfake
Detection,
WACV23(4680-4689)
IEEE DOI
2302
Training, Additive noise, Deepfakes, Image coding, Face recognition,
Detectors, Applications: Social good, Explainable, fair, accountable,
Arts/games/social media
BibRef
Zhao, Y.[Yuan],
Liu, B.[Bo],
Ding, M.[Ming],
Liu, B.P.[Bao-Ping],
Zhu, T.Q.[Tian-Qing],
Yu, X.[Xin],
Proactive Deepfake Defence via Identity Watermarking,
WACV23(4591-4600)
IEEE DOI
2302
Deepfakes, Visualization, Privacy, Image coding, Neural networks,
Watermarking, Robustness, Applications: Social good, Explainable,
Arts/games/social media
BibRef
Çiftçi, U.A.[Umur A.],
Yuksek, G.[Gokturk],
Demir, I.[Ilke],
My Face My Choice:
Privacy Enhancing Deepfakes for Social Media Anonymization,
WACV23(1369-1379)
IEEE DOI
2302
Measurement, Deepfakes, Privacy, Data privacy,
Social networking (online), Face recognition, Task analysis,
ethical computer vision
BibRef
Li, C.[Chuqiao],
Huang, Z.W.[Zhi-Wu],
Paudel, D.P.[Danda Pani],
Wang, Y.[Yabin],
Shahbazi, M.[Mohamad],
Hong, X.P.[Xiao-Peng],
Van Gool, L.J.[Luc J.],
A Continual Deepfake Detection Benchmark:
Dataset, Methods, and Essentials,
WACV23(1339-1349)
IEEE DOI
2302
Learning systems, Deepfakes, Visualization, Adaptation models, Codes,
Benchmark testing, and un-supervised learning)
BibRef
Hukkelås, H.[Håkon],
Lindseth, F.[Frank],
DeepPrivacy2: Towards Realistic Full-Body Anonymization,
WACV23(1329-1338)
IEEE DOI
2302
Image quality, Data privacy, Privacy, Deepfakes,
Computational modeling, Generative adversarial networks,
ethical computer vision
BibRef
Ma, T.[Tian],
Bamweyana, A.[Arnold],
Guo, M.[Ming],
Benon, K.[Kavuma],
A Face Morph Detection Method Based on Convolutional Neural Networks
and Occlusion Test,
ICIVC22(158-165)
IEEE DOI
2301
Training, Visualization, Neural networks, Decision making,
Training data, Robustness, Automatic Border Control (ABC), VGG19
BibRef
Mambreyan, A.[Ara],
Punskaya, E.[Elena],
Gunes, H.[Hatice],
Dataset Bias in Deception Detection,
ICPR22(1083-1089)
IEEE DOI
2212
Measurement, Industries, Ethics, Machine learning algorithms,
Government, Machine learning, Detectors
BibRef
Borghi, G.[Guido],
Graffieti, G.[Gabriele],
Franco, A.[Annalisa],
Maltoni, D.[Davide],
Incremental Training of Face Morphing Detectors,
ICPR22(914-921)
IEEE DOI
2212
Training, Data privacy, Face recognition, Training data, Detectors,
Data models, Stability analysis
BibRef
Ferrari, C.[Claudio],
Serpentoni, M.[Matteo],
Berretti, S.[Stefano],
del Bimbo, A.[Alberto],
What makes you, you? Analyzing Recognition by Swapping Face Parts,
ICPR22(945-951)
IEEE DOI
2212
Deep learning, Protocols, Shape, Face recognition, Fitting, Nose
BibRef
Wu, H.T.[Hao-Tian],
Wang, P.[Peipei],
Wang, X.[Xin],
Xiang, J.[Ji],
Gong, R.[Rui],
GGViT: Multistream Vision Transformer Network in Face2Face Facial
Reenactment Detection,
ICPR22(2335-2341)
IEEE DOI
2212
Image quality, Image coding, Social networking (online),
Network architecture, Transformers, Forgery
BibRef
Jevnisek, A.[Amir],
Avidan, S.[Shai],
Aggregating Layers for Deepfake Detection,
ICPR22(2027-2033)
IEEE DOI
2212
Training, Deepfakes, Visualization, Aggregates, Pipelines,
Feature extraction, Classification algorithms
BibRef
Guan, W.N.[Wei-Nan],
He, Z.[Ziwen],
Wang, W.[Wei],
Dong, J.[Jing],
Peng, B.[Bo],
Defending Against Deepfakes with Ensemble Adversarial Perturbation,
ICPR22(1952-1958)
IEEE DOI
2212
Deepfakes, Protocols, Face recognition, Perturbation methods,
Facial features, Glass box
BibRef
Li, D.Z.[Dong-Ze],
Zhuo, W.Q.[Wen-Qi],
Wang, W.[Wei],
Dong, J.[Jing],
Contrastive Knowledge Transfer for Deepfake Detection with Limited
Data,
ICPR22(1945-1951)
IEEE DOI
2212
Training, Deepfakes, Solid modeling, Robustness, Data models,
Task analysis
BibRef
Kim, J.[Jeongho],
Kim, T.[Taejune],
Kim, J.[Jeonghyeon],
Woo, S.S.[Simon S.],
Evading Deepfake Detectors via High Quality Face Pre-Processing
Methods,
ICPR22(1937-1944)
IEEE DOI
2212
Deepfakes, Face recognition, Neural networks, Supervised learning,
Pipelines, Detectors, Media
BibRef
Lim, N.T.[Nyee Thoang],
Kuan, M.Y.[Meng Yi],
Pu, M.[Muxin],
Lim, M.K.[Mei Kuan],
Chong, C.Y.[Chun Yong],
Metamorphic Testing-based Adversarial Attack to Fool Deepfake
Detectors,
ICPR22(2503-2509)
IEEE DOI
2212
Deepfakes, Adaptation models, System testing, Detectors, Media,
Probabilistic logic, Robustness
BibRef
Pavlakos, G.[Georgios],
Weber, E.[Ethan],
Tancik, M.[Matthew],
Kanazawa, A.[Angjoo],
The One Where They Reconstructed 3D Humans and Environments in TV Shows,
ECCV22(XXXVII:732-749).
Springer DOI
2211
BibRef
Bui, T.[Tu],
Yu, N.[Ning],
Collomosse, J.[John],
RepMix:
Representation Mixing for Robust Attribution of Synthesized Images,
ECCV22(XIV:146-163).
Springer DOI
2211
WWW Link.
BibRef
Dong, S.C.[Shi-Chao],
Wang, J.[Jin],
Liang, J.J.[Jia-Jun],
Fan, H.Q.[Hao-Qiang],
Ji, R.[Renhe],
Explaining Deepfake Detection by Analysing Image Matching,
ECCV22(XIV:18-35).
Springer DOI
2211
BibRef
Shao, R.[Rui],
Wu, T.X.[Tian-Xing],
Liu, Z.[Ziwei],
Detecting and Recovering Sequential DeepFake Manipulation,
ECCV22(XIII:712-728).
Springer DOI
2211
BibRef
Gu, Z.H.[Zhi-Hao],
Yao, T.P.[Tai-Ping],
Chen, Y.[Yang],
Ding, S.H.[Shou-Hong],
Ma, L.Z.[Li-Zhuang],
Hierarchical Contrastive Inconsistency Learning for Deepfake Video
Detection,
ECCV22(XII:596-613).
Springer DOI
2211
BibRef
Dufour, N.[Nicolas],
Picard, D.[David],
Kalogeiton, V.[Vicky],
SCAM! Transferring Humans Between Images with Semantic Cross Attention
Modulation,
ECCV22(XIV:713-729).
Springer DOI
2211
BibRef
Chuang, C.C.[Chia-Chi],
Yang, D.L.[Dong-Lin],
Wen, C.[Chuan],
Gao, Y.[Yang],
Resolving Copycat Problems in Visual Imitation Learning via Residual
Action Prediction,
ECCV22(XXIX:392-409).
Springer DOI
2211
BibRef
Concas, S.[Sara],
Perelli, G.[Gianpaolo],
Marcialis, G.L.[Gian Luca],
Puglisi, G.[Giovanni],
Tensor-Based Deepfake Detection in Scaled and Compressed Images,
ICIP22(3121-3125)
IEEE DOI
2211
Deep learning, Deepfakes, Image coding, Tensors, Neural networks,
Feature extraction, Deepfake, face, biometric
BibRef
Jia, S.[Shan],
Li, X.[Xin],
Lyu, S.W.[Si-Wei],
Model Attribution of Face-Swap Deepfake Videos,
ICIP22(2356-2360)
IEEE DOI
2211
Deepfakes, Image coding, Forensics, Impersonation attacks,
Video compression, Robustness, Decoding, Face-swap Deepfakes,
Deepfakes Generation
BibRef
Sun, P.[Pu],
Li, Y.[Yuezun],
Qi, H.G.[Hong-Gang],
Lyu, S.W.[Si-Wei],
Faketracer: Exposing Deepfakes with Training Data Contamination,
ICIP22(1161-1165)
IEEE DOI
2211
Training, Deepfakes, Training data, Security, Faces, Contamination,
Proactively DeepFake Defense, Multimedia Forensics, AI Security
BibRef
Lin, Y.Z.[Yu-Zhen],
Chen, H.[Han],
Li, B.[Bin],
Wu, J.Q.[Jun-Qiang],
Towards Generalizable DEEPFAKE Face Forgery Detection with
Semi-Supervised Learning and Knowledge Distillation,
ICIP22(576-580)
IEEE DOI
2211
Training, Deepfakes, Semisupervised learning, Benchmark testing,
Feature extraction, Forgery, Data models, Deepfake detection,
knowledge distillation
BibRef
Ju, Y.[Yan],
Jia, S.[Shan],
Ke, L.[Lipeng],
Xue, H.F.[Hong-Fei],
Nagano, K.[Koki],
Lyu, S.W.[Si-Wei],
Fusing Global and Local Features for Generalized AI-Synthesized Image
Detection,
ICIP22(3465-3469)
IEEE DOI
2211
Deepfakes, Fuses, Forensics, Detectors, Media, Feature extraction,
Generative adversarial networks, Index Terms, Attention Mechanism
BibRef
Chen, Q.[Qi],
Tan, M.K.[Ming-Kui],
Qi, Y.K.[Yuan-Kai],
Zhou, J.Q.[Jia-Qiu],
Li, Y.Q.[Yuan-Qing],
Wu, Q.[Qi],
V2C: Visual Voice Cloning,
CVPR22(21210-21219)
IEEE DOI
2210
Measurement, Visualization, Codes, Cloning, Motion pictures,
Pattern recognition, Datasets and evaluation, Vision+language, Vision+X
BibRef
Kim, J.[Jiseob],
Lee, J.[Jihoon],
Zhang, B.T.[Byoung-Tak],
Smooth-Swap: A Simple Enhancement for Face-Swapping with Smoothness,
CVPR22(10769-10778)
IEEE DOI
2210
Training, Shape, Face recognition, Computational modeling,
Generators, Face and gestures
BibRef
Shu, C.Y.[Chang-Yong],
Wu, H.[Hemao],
Zhou, H.[Hang],
Liu, J.[JiaMing],
Hong, Z.B.[Zhi-Bin],
Ding, C.X.[Chang-Xing],
Han, J.Y.[Jun-Yu],
Liu, J.[Jingtuo],
Ding, E.[Errui],
Wang, J.D.[Jing-Dong],
Few-Shot Head Swapping in the Wild,
CVPR22(10779-10788)
IEEE DOI
2210
Head, Image color analysis, Face recognition,
Entertainment industry, Skin, Task analysis
BibRef
Haliassos, A.[Alexandros],
Mira, R.[Rodrigo],
Petridis, S.[Stavros],
Pantic, M.[Maja],
Leveraging Real Talking Faces via Self-Supervision for Robust Forgery
Detection,
CVPR22(14930-14942)
IEEE DOI
2210
Training, Visualization, Detectors, Pressing, Forgery, Robustness,
Pattern recognition, Computer vision for social good,
Self- semi- meta- Video analysis and understanding
BibRef
Chen, L.[Liang],
Zhang, Y.[Yong],
Song, Y.B.[Yi-Bing],
Liu, L.Q.[Ling-Qiao],
Wang, J.[Jue],
Self-supervised Learning of Adversarial Example: Towards Good
Generalizations for Deepfake Detection,
CVPR22(18689-18698)
IEEE DOI
2210
Training, Deepfakes, Sensitivity, Face recognition,
Self-supervised learning, Detectors,
Face and gestures
BibRef
Shiohara, K.[Kaede],
Yamasaki, T.[Toshihiko],
Detecting Deepfakes with Self-Blended Images,
CVPR22(18699-18708)
IEEE DOI
2210
Training, Deepfakes, Protocols, Image recognition, Face recognition,
Training data, Detectors, Recognition: detection, categorization,
Image and video synthesis and generation
BibRef
Gerstner, C.R.[Candice R.],
Farid, H.[Hany],
Detecting Real-Time Deep-Fake Videos Using Active Illumination,
WMF22(53-60)
IEEE DOI
2210
Deepfakes, Teleconferencing, Forensics, Face recognition, Lighting,
Particle measurements, Real-time systems
BibRef
Guarnera, L.[Luca],
Giudice, O.[Oliver],
Nießner, M.[Matthias],
Battiato, S.[Sebastiano],
On the Exploitation of Deepfake Model Recognition,
WMF22(61-70)
IEEE DOI
2210
Training, Measurement, Deepfakes, Analytical models,
Image recognition, Forensics, Pipelines
BibRef
Nadimpalli, A.V.[Aakash Varma],
Rattani, A.[Ajita],
On Improving Cross-dataset Generalization of Deepfake Detectors,
WMF22(91-99)
IEEE DOI
2210
Deepfakes, Detectors, Reinforcement learning,
Pattern recognition
BibRef
Narayan, K.[Kartik],
Agarwal, H.[Harsh],
Mittal, S.[Surbhi],
Thakral, K.[Kartik],
Kundu, S.[Suman],
Vatsa, M.[Mayank],
Singh, R.[Richa],
DeSI: Deepfake Source Identifier for Social Media,
FaDE-TCV22(2857-2866)
IEEE DOI
2210
Deepfakes, Social networking (online), Scalability,
Blogs, Sociology
BibRef
Wang, X.[Xueyu],
Huang, J.J.[Jia-Jun],
Ma, S.Q.[Si-Qi],
Nepal, S.[Surya],
Xu, C.[Chang],
DeepFake Disrupter: The Detector of DeepFake Is My Friend,
CVPR22(14900-14909)
IEEE DOI
2210
Training, Deepfakes, Perturbation methods, Pipelines,
Neural networks, Detectors, Fasteners,
Adversarial attack and defense
BibRef
Dong, X.Y.[Xiao-Yi],
Bao, J.[Jianmin],
Chen, D.D.[Dong-Dong],
Zhang, T.[Ting],
Zhang, W.M.[Wei-Ming],
Yu, N.H.[Neng-Hai],
Chen, D.[Dong],
Wen, F.[Fang],
Guo, B.[Baining],
Protecting Celebrities from DeepFake with Identity Consistency
Transformer,
CVPR22(9458-9468)
IEEE DOI
2210
Degradation, Deepfakes, Face recognition, Semantics, Transformers,
Forgery, Recognition: detection, categorization, retrieval, Face and gestures
BibRef
Dong, C.[Chengdong],
Kumar, A.[Ajay],
Liu, E.[Eryun],
Think Twice Before Detecting GAN-generated Fake Images from their
Spectral Domain Imprints,
CVPR22(7855-7864)
IEEE DOI
2210
Privacy, Image matching, Pipelines, Detectors,
Generative adversarial networks, Security, Reliability,
Vision applications and systems
BibRef
Ramkissoon, A.N.[Amit Neil],
Goodridge, W.[Wayne],
Detecting Fake News in MANET Messaging Using an Ensemble Based
Computational Social System,
AI4DH22(278-289).
Springer DOI
2208
BibRef
Sciucca, L.D.[Laura Della],
Mameli, M.[Marco],
Balloni, E.[Emanuele],
Rossi, L.[Luca],
Frontoni, E.[Emanuele],
Zingaretti, P.[Primo],
Paolanti, M.[Marina],
FakeNED: A Deep Learning Based-System for Fake News Detection from
Social Media,
ISHAPE22(303-313).
Springer DOI
2208
BibRef
Sannino, C.[Ciro],
Gravina, M.[Michela],
Marrone, S.[Stefano],
Fiameni, G.[Giuseppe],
Sansone, C.[Carlo],
LessonAble: Leveraging Deep Fakes in MOOC Content Creation,
CIAP22(I:27-37).
Springer DOI
2205
BibRef
Concas, S.[Sara],
Gao, J.[Jie],
Cuccu, C.[Carlo],
Orrù, G.[Giulia],
Feng, X.Y.[Xiao-Yi],
Marcialis, G.L.[Gian Luca],
Puglisi, G.[Giovanni],
Roli, F.[Fabio],
Experimental Results on Multi-modal Deepfake Detection,
CIAP22(II:164-175).
Springer DOI
2205
BibRef
Boccignone, G.[Giuseppe],
Bursic, S.[Sathya],
Cuculo, V.[Vittorio],
d'Amelio, A.[Alessandro],
Grossi, G.[Giuliano],
Lanzarotti, R.[Raffaella],
Patania, S.[Sabrina],
DeepFakes Have No Heart:
A Simple rPPG-Based Method to Reveal Fake Videos,
CIAP22(II:186-195).
Springer DOI
2205
BibRef
Coccomini, D.A.[Davide Alessandro],
Messina, N.[Nicola],
Gennaro, C.[Claudio],
Falchi, F.[Fabrizio],
Combining EfficientNet and Vision Transformers for Video Deepfake
Detection,
CIAP22(III:219-229).
Springer DOI
2205
BibRef
Guarnera, L.[Luca],
Giudice, O.[Oliver],
Battiato, S.[Sebastiano],
Deepfake Style Transfer Mixture:
A First Forensic Ballistics Study on Synthetic Images,
CIAP22(II:151-163).
Springer DOI
2205
BibRef
Li, B.[Boqun],
Qian, Z.[Zhong],
Li, P.F.[Pei-Feng],
Zhu, Q.M.[Qiao-Ming],
Multi-Modal Fusion Network for Rumor Detection with Texts and Images,
MMMod22(I:15-27).
Springer DOI
2203
Best paper section
BibRef
Vo, N.H.[Ngan Hoang],
Phan, K.D.[Khoa D.],
Tran, A.D.[Anh-Duy],
Dang-Nguyen, D.T.[Duc-Tien],
Adversarial Attacks on Deepfake Detectors: A Practical Analysis,
MMMod22(II:318-330).
Springer DOI
2203
BibRef
Le, T.N.[Trung-Nghia],
Nguyen, H.H.[Huy H.],
Yamagishi, J.[Junichi],
Echizen, I.[Isao],
OpenForensics: Large-Scale Challenging Dataset For Multi-Face Forgery
Detection And Segmentation In-The-Wild,
ICCV21(10097-10107)
IEEE DOI
2203
Annotations, Social networking (online), Face recognition, Media,
Forgery, Face detection, Task analysis, Datasets and evaluation,
Image and video manipulation detection and integrity methods.
BibRef
Kwon, P.[Patrick],
You, J.[Jaeseong],
Nam, G.[Gyuhyeon],
Park, S.[Sungwoo],
Chae, G.[Gyeongsu],
KoDF: A Large-scale Korean DeepFake Detection Dataset,
ICCV21(10724-10733)
IEEE DOI
2203
Databases, Metadata, Faces, Videos, Information integrity,
Datasets and evaluation, Faces,
Image and video synthesis
BibRef
Yu, N.[Ning],
Skripniuk, V.[Vladislav],
Abdelnabi, S.[Sahar],
Fritz, M.[Mario],
Artificial Fingerprinting for Generative Models:
Rooting Deepfake Attribution in Training Data,
ICCV21(14428-14437)
IEEE DOI
2203
Visualization, Technological innovation, Computational modeling,
Weapons, Training data, Fingerprint recognition, Data models,
Image and video manipulation detection and integrity methods.
BibRef
Zhou, Y.[Yipin],
Lim, S.N.[Ser-Nam],
Joint Audio-Visual Deepfake Detection,
ICCV21(14780-14789)
IEEE DOI
2203
Deep learning, Visualization, Computational modeling,
Synchronization, Speech synthesis, Task analysis,
Vision + other modalities
BibRef
Zhao, T.[Tianchen],
Xu, X.[Xiang],
Xu, M.Z.[Ming-Ze],
Ding, H.[Hui],
Xiong, Y.J.[Yuan-Jun],
Xia, W.[Wei],
Learning Self-Consistency for Deepfake Detection,
ICCV21(15003-15013)
IEEE DOI
2203
Training, Representation learning, Image synthesis, Training data,
Feature extraction, Generators, Forgery, Fairness, accountability,
Faces
BibRef
Cozzolino, D.[Davide],
Rössler, A.[Andreas],
Thies, J.[Justus],
Nießner, M.[Matthias],
Verdoliva, L.[Luisa],
ID-Reveal: Identity-aware DeepFake Video Detection,
ICCV21(15088-15097)
IEEE DOI
2203
Training, Image coding, Social networking (online), Training data,
Robustness, Forgery, Faces,
and ethics in vision
BibRef
Kim, D.K.[Dong-Keon],
Kim, K.[Kwangsu],
Generalized Facial Manipulation Detection with Edge Region Feature
Extraction,
WACV22(2784-2794)
IEEE DOI
2202
Image color analysis, Image edge detection, Forensics,
Fingerprint recognition, Feature extraction, Robustness, Forgery,
Privacy and Ethics in Vision Biometrics
BibRef
Xu, Y.[Ying],
Raja, K.[Kiran],
Pedersen, M.[Marius],
Supervised Contrastive Learning for Generalizable and Explainable
DeepFakes Detection,
Explain-Bio22(379-389)
IEEE DOI
2202
Training, Analytical models, Visualization, Fuses, Detectors,
Media
BibRef
Jeong, Y.[Yonghyun],
Kim, D.[Doyeon],
Min, S.J.[Seung-Jai],
Joe, S.[Seongho],
Gwon, Y.[Youngjune],
Choi, J.W.[Jong-Won],
BiHPF: Bilateral High-Pass Filters for Robust Deepfake Detection,
WACV22(2878-2887)
IEEE DOI
2202
Training, Frequency synthesizers, Image resolution, Image coding,
Image color analysis, Computational modeling, Data models,
Security/Surveillance
BibRef
Wang, Y.H.[Yong-Hui],
Zarghami, V.[Vahid],
Cui, S.[Suxia],
Fake Face Detection using Local Binary Pattern and Ensemble Modeling,
ICIP21(3917-3921)
IEEE DOI
2201
Deep learning, Image texture, Image color analysis,
Image representation, Feature extraction,
Ensemble model
BibRef
Wang, X.[Xiying],
Ni, R.R.[Rong-Rong],
Li, W.J.[Wen-Jie],
Zhao, Y.[Yao],
Adversarial Attack on Fake-Faces Detectors Under White and Black Box
Scenarios,
ICIP21(3627-3631)
IEEE DOI
2201
Forensics, Detectors, Generative adversarial networks,
Feature extraction, Generators, Security, Adversarial attack,
Forensic models
BibRef
Lu, C.L.[Chang-Lei],
Liu, B.[Bin],
Zhou, W.[Wenbo],
Chu, Q.[Qi],
Yu, N.H.[Neng-Hai],
Deepfake Video Detection Using 3D-Attentional Inception Convolutional
Neural Network,
ICIP21(3572-3576)
IEEE DOI
2201
Solid modeling, Image processing, Data models, Security,
Convolutional neural networks, Deepfake Detection,
3D Attention
BibRef
Hu, J.S.[Jia-Shang],
Wang, S.L.[Shi-Lin],
Li, X.Y.[Xiao-Yong],
Improving the Generalization Ability of Deepfake Detection via
Disentangled Representation Learning,
ICIP21(3577-3581)
IEEE DOI
2201
Deep learning, Neural networks, Feature extraction, Forgery,
Data mining, Faces, Disentangle representation learning,
deep neural network
BibRef
Song, L.C.[Lu-Chuan],
Yin, G.J.[Guo-Jun],
Liu, B.[Bin],
Zhang, Y.[Yuhui],
Yu, N.H.[Neng-Hai],
Fsft-Net: Face Transfer Video Generation With Few-Shot Views,
ICIP21(3582-3586)
IEEE DOI
2201
Training, Deep learning, Image processing, Distortion, Generators,
Task analysis, Faces, Face Transfer, Adversarial Training,
Deepfake Generation
BibRef
Li, G.[Gen],
Cao, Y.[Yun],
Zhao, X.F.[Xian-Feng],
Exploiting Facial Symmetry to Expose Deepfakes,
ICIP21(3587-3591)
IEEE DOI
2201
Feature extraction, Data models, Faces, Videos,
Information integrity, Residual neural networks,
angular hyperspace
BibRef
Ren, Y.Z.[Yan-Zhen],
Liu, W.[Wuyang],
Liu, D.[Dengkai],
Wang, L.[Lina],
Recalibrated Bandpass Filtering on Temporal Waveform for Audio Spoof
Detection,
ICIP21(3907-3911)
IEEE DOI
2201
Filtering, Convolution, Tools, Feature extraction, Cognition,
Speech synthesis, Audio spoof detection, Deepfake,
ASVspoof
BibRef
Liao, Q.Y.[Quan-Yu],
Li, Y.Z.[Yue-Zun],
Wang, X.[Xin],
Kong, B.[Bin],
Zhu, B.[Bin],
Lyu, S.W.[Si-Wei],
Yin, Y.[Youbing],
Song, Q.[Qi],
Wu, X.[Xi],
Imperceptible Adversarial Examples for Fake Image Detection,
ICIP21(3912-3916)
IEEE DOI
2201
Perturbation methods, Image processing, Detectors, Videos,
Information integrity, Deepfake, Adversarial Example
BibRef
Das, S.[Sowmen],
Seferbekov, S.[Selim],
Datta, A.[Arup],
Islam, M.S.[Md. Saiful],
Amin, M.R.[Md. Ruhul],
Towards Solving the DeepFake Problem : An Analysis on Improving
DeepFake Detection using Dynamic Face Augmentation,
RPRMI21(3769-3778)
IEEE DOI
2112
Training, Pipelines, Training data,
Data models, Robustness, Faces
BibRef
Huang, J.J.[Jia-Jun],
Wang, X.[Xueyu],
Du, B.[Bo],
Du, P.[Pei],
Xu, C.[Chang],
DeepFake MNIST+: A DeepFake Facial Animation Dataset,
AIM21(1973-1982)
IEEE DOI
2112
Image recognition, Face recognition, Detectors,
Generators, Facial animation, Security
BibRef
Haliassos, A.[Alexandros],
Vougioukas, K.[Konstantinos],
Petridis, S.[Stavros],
Pantic, M.[Maja],
Lips Don't Lie: A Generalisable and Robust Approach to Face Forgery
Detection,
CVPR21(5037-5047)
IEEE DOI
2111
Visualization, Face recognition, Perturbation methods, Semantics,
Meetings, Mouth, Speech recognition
BibRef
Zhao, H.Q.[Han-Qing],
Wei, T.Y.[Tian-Yi],
Zhou, W.[Wenbo],
Zhang, W.M.[Wei-Ming],
Chen, D.D.[Dong-Dong],
Yu, N.H.[Neng-Hai],
Multi-attentional Deepfake Detection,
CVPR21(2185-2194)
IEEE DOI
2111
Measurement, Semantics, Feature extraction, Forgery,
Pattern recognition, Feeds, Task analysis
BibRef
Sun, Z.[Zekun],
Han, Y.J.[Yu-Jie],
Hua, Z.[Zeyu],
Ruan, N.[Na],
Jia, W.J.[Wei-Jia],
Improving the Efficiency and Robustness of Deepfakes Detection
through Precise Geometric Features,
CVPR21(3608-3617)
IEEE DOI
2111
Recurrent neural networks, Feature extraction,
Robustness, Pattern recognition, Organ transplantation, Complexity theory
BibRef
Chen, Z.[Zhikai],
Xie, L.X.[Ling-Xi],
Pang, S.[Shanmin],
He, Y.[Yong],
Zhang, B.[Bo],
MagDR: Mask-guided Detection and Reconstruction for Defending
Deepfakes,
CVPR21(9010-9019)
IEEE DOI
2111
Visualization, Perturbation methods, Pipelines, Semantics,
Prediction algorithms, Pattern recognition, Task analysis
BibRef
Li, D.Z.[Dong-Ze],
Wang, W.[Wei],
Fan, H.X.[Hong-Xing],
Dong, J.[Jing],
Exploring Adversarial Fake Images on Face Manifold,
CVPR21(5785-5794)
IEEE DOI
2111
Manifolds, Visualization, Privacy, Image forensics, Ethics,
Face recognition
BibRef
Black, A.[Alexander],
Bui, T.[Tu],
Jin, H.L.[Hai-Lin],
Swaminathan, V.[Vishy],
Collomosse, J.[John],
Deep Image Comparator: Learning to Visualize Editorial Change,
WMF21(972-980)
IEEE DOI
2109
Heating systems, Training, Location awareness, Degradation,
Visualization, Databases, Shape
BibRef
Hosler, B.[Brian],
Salvi, D.[Davide],
Murray, A.[Anthony],
Antonacci, F.[Fabio],
Bestagini, P.[Paolo],
Tubaro, S.[Stefano],
Stamm, M.C.[Matthew C.],
Do Deepfakes Feel Emotions? A Semantic Approach to Detecting
Deepfakes Via Emotional Inconsistencies,
WMF21(1013-1022)
IEEE DOI
2109
Emotion recognition, Law, Semantics,
Speech recognition, Media, Forgery
BibRef
Kim, M.[Minha],
Tariq, S.[Shahroz],
Woo, S.S.[Simon S.],
FReTAL: Generalizing Deepfake Detection using Knowledge Distillation
and Representation Learning,
WMF21(1001-1012)
IEEE DOI
2109
Adaptation models,
Computational modeling, Transfer learning, Data models, Pattern recognition
BibRef
Neekhara, P.[Paarth],
Dolhansky, B.[Brian],
Bitton, J.[Joanna],
Ferrer, C.C.[Cristian Canton],
Adversarial Threats to DeepFake Detection: A Practical Perspective,
WMF21(923-932)
IEEE DOI
2109
Social networking (online), Perturbation methods,
Neural networks, Multimedia Web sites, Detectors,
Security
BibRef
Tinsley, P.[Patrick],
Czajka, A.[Adam],
Flynn, P.J.[Patrick J.],
This Face Does Not Exist... But It Might Be Yours! Identity Leakage
in Generative Models,
WACV21(1319-1327)
IEEE DOI
2106
Training, Image resolution, Databases, Training data,
Generative adversarial networks, Data models, Faces
BibRef
Trinh, L.[Loc],
Tsang, M.[Michael],
Rambhatla, S.[Sirisha],
Liu, Y.[Yan],
Interpretable and Trustworthy Deepfake Detection via Dynamic
Prototypes,
WACV21(1972-1982)
IEEE DOI
2106
Visualization, Prototypes, Detectors,
Forgery, Faces
BibRef
Hussain, S.[Shehzeen],
Neekhara, P.[Paarth],
Jere, M.[Malhar],
Koushanfar, F.[Farinaz],
McAuley, J.[Julian],
Adversarial Deepfakes: Evaluating Vulnerability of Deepfake Detectors
to Adversarial Examples,
WACV21(3347-3356)
IEEE DOI
2106
Industries, Perturbation methods, Pipelines, Neural networks,
Detectors, Media, Video compression
BibRef
Zhang, Z.[Zhewei],
Mal, C.[Can],
Ding, B.[Bowen],
Gao, M.[Meilin],
Detecting Manipulated Facial Videos: A Time Series Solution,
ICPR21(2817-2823)
IEEE DOI
2105
Deep learning, Correlation, Face recognition, Time series analysis,
Memory architecture, Physiology, Complexity theory,
pattern recognization
BibRef
Bonettini, N.[Nicolò],
Cannas, E.D.[Edoardo Daniele],
Mandelli, S.[Sara],
Bondi, L.[Luca],
Bestagini, P.[Paolo],
Tubaro, S.[Stefano],
Video Face Manipulation Detection Through Ensemble of CNNs,
ICPR21(5012-5019)
IEEE DOI
2105
Training, Computational modeling, Veins, Video sequences, Tools,
Feature extraction, Data models, deepfake, video forensics, attention
BibRef
Li, M.[Meng],
Liu, B.B.[Bei-Bei],
Hu, Y.J.[Yong-Jian],
Wang, Y.[Yufei],
Exposing Deepfake Videos by Tracking Eye Movements,
ICPR21(5184-5189)
IEEE DOI
2105
Support vector machines, Tracking, Neural networks, Media, Tools,
Feature extraction, Physiology
BibRef
Liu, Y.C.[Yu-Cheng],
Chang, C.M.[Chia-Ming],
Chen, I.H.[I-Hsuan],
Ku, Y.R.[Yu-Ru],
Chen, J.C.[Jun-Cheng],
An Experimental Evaluation of Recent Face Recognition Losses for
Deepfake Detection,
ICPR21(9827-9834)
IEEE DOI
2105
Face recognition, Network architecture, Data models, Task analysis,
Faces, Videos, Information integrity
BibRef
Masi, I.[Iacopo],
Killekar, A.[Aditya],
Mascarenhas, R.M.[Royston Marian],
Gurudatt, S.P.[Shenoy Pratik],
Abd Almageed, W.[Wael],
Two-branch Recurrent Network for Isolating Deepfakes in Videos,
ECCV20(VII:667-684).
Springer DOI
2011
BibRef
Gu, Y.W.[Ye-Wei],
Zhao, X.F.[Xian-Feng],
Gong, C.[Chen],
Yi, X.W.[Xiao-Wei],
Deepfake Video Detection Using Audio-visual Consistency,
IWDW20(168-180).
Springer DOI
2103
BibRef
Schütz, M.[Mina],
Schindler, A.[Alexander],
Siegel, M.[Melanie],
Nazemi, K.[Kawa],
Automatic Fake News Detection with Pre-trained Transformer Models,
RISS20(627-641).
Springer DOI
2103
BibRef
Tolosana, R.[Ruben],
Romero-Tapiador, S.[Sergio],
Fierrez, J.[Julian],
Vera-Rodriguez, R.[Ruben],
Deepfakes Evolution: Analysis of Facial Regions and Fake Detection
Performance,
IWBDAF20(442-456).
Springer DOI
2103
BibRef
Mishra, R.,
Fake News Detection using Higher-order User to User Mutual-attention
Progression in Propagation Paths,
WMF20(2775-2783)
IEEE DOI
2008
Feature extraction, Twitter, Linear programming,
Linguistics, Time series analysis
BibRef
Chai, L.[Lucy],
Bau, D.[David],
Lim, S.N.[Ser-Nam],
Isola, P.[Phillip],
What Makes Fake Images Detectable? Understanding Properties that
Generalize,
ECCV20(XXVI:103-120).
Springer DOI
2011
BibRef
Zhou, J.,
Pun, C.M.,
Tong, Y.,
News Image Steganography: A Novel Architecture Facilitates the Fake
News Identification,
VCIP20(235-238)
IEEE DOI
2102
Decoding, Training, Perturbation methods, Forgery,
Printers, Media, image steganography, information hiding,
fake news identification
BibRef
Choi, D.H.,
Lee, H.J.,
Lee, S.,
Kim, J.U.,
Ro, Y.M.,
Fake Video Detection With Certainty-Based Attention Network,
ICIP20(823-827)
IEEE DOI
2011
DeepFake video detection, predictive uncertainty,
certainty-key frame, certainty-based attention
BibRef
Fernandes, S.,
Raj, S.,
Ewetz, R.,
Pannu, J.S.,
Jha, S.K.[S. Kumar],
Ortiz, E.,
Vintila, I.,
Salter, M.,
Detecting Deepfake Videos using Attribution-Based Confidence Metric,
CVPM20(1250-1259)
IEEE DOI
2008
Videos, Face, Measurement, Computational modeling, Training data,
Machine learning, Databases
BibRef
Tursman, E.,
George, M.,
Kamara, S.,
Tompkin, J.,
Towards Untrusted Social Video Verification to Combat Deepfakes via
Face Geometry Consistency,
WMF20(2784-2793)
IEEE DOI
2008
Face, Streaming media, Principal component analysis, Cameras, Mouth,
Covariance matrices, Geometry
BibRef
Khalid, H.,
Woo, S.S.,
OC-FakeDect: Classifying Deepfakes Using One-class Variational
Autoencoder,
WMF20(2794-2803)
IEEE DOI
2008
Face, Training, Image reconstruction, Forensics, Streaming media,
Anomaly detection, Benchmark testing
BibRef
Carlini, N.,
Farid, H.,
Evading Deepfake-Image Detectors with White- and Black-Box Attacks,
WMF20(2804-2813)
IEEE DOI
2008
Forensics, Generators, Perturbation methods, Training, Twitter,
Robustness, Optimization
BibRef
Agarwal, S.[Shruti],
Farid, H.[Hany],
Detecting Deep-Fake Videos from Aural and Oral Dynamics,
WMF21(981-989)
IEEE DOI
2109
Irrigation, Shape, Tracking, Face recognition, Forensics, Dynamics, Mouth
BibRef
Agarwal, S.[Shruti],
Farid, H.[Hany],
Fried, O.,
Agrawala, M.,
Detecting Deep-Fake Videos from Phoneme-Viseme Mismatches,
WMF20(2814-2822)
IEEE DOI
2008
Videos, Lips, Face, Shape, Teeth, Robustness
BibRef
Guarnera, L.,
Giudice, O.,
Battiato, S.,
DeepFake Detection by Analyzing Convolutional Traces,
WMF20(2841-2850)
IEEE DOI
2008
Generative adversarial networks, Videos,
Data models, Convolution, Feature extraction
BibRef
Montserrat, D.M.,
Hao, H.,
Yarlagadda, S.K.,
Baireddy, S.,
Shao, R.,
Horváth, J.,
Bartusiak, E.,
Yang, J.,
Güera, D.,
Zhu, F.,
Delp, E.J.,
Deepfakes Detection with Automatic Face Weighting,
WMF20(2851-2859)
IEEE DOI
2008
Face, Feature extraction, Streaming media,
Recurrent neural networks, Training, Tools, Social network services
BibRef
Li, Y.,
Yang, X.,
Sun, P.,
Qi, H.,
Lyu, S.,
Celeb-DF: A Large-Scale Challenging Dataset for DeepFake Forensics,
CVPR20(3204-3213)
IEEE DOI
2008
Videos, Visualization, Image color analysis, Decoding, YouTube,
Training, Detection algorithms
BibRef
Wang, Y.,
Dantcheva, A.,
A video is worth more than 1000 lies. Comparing 3DCNN approaches for
detecting deepfakes,
FG20(515-519)
IEEE DOI
2102
Videos, Information integrity,
Training, Face recognition, Solid modeling, Faces
BibRef
Tong, X.,
Wang, L.,
Pan, X.,
Wang, J.G.,
An Overview of Deepfake: The Sword of Damocles in AI,
CVIDL20(265-273)
IEEE DOI
2102
face recognition, feature extraction, image classification,
video signal processing, confrontation detection,
Variational Auto-Encoder
BibRef
Yeh, C.,
Chen, H.,
Tsai, S.,
Wang, S.,
Disrupting Image-Translation-Based DeepFake Algorithms with
Adversarial Attacks,
WACVWS20(53-62)
IEEE DOI
2006
Generators, Mathematical model, Hair,
Software algorithms, Software, Machine learning
BibRef
Matern, F.,
Riess, C.,
Stamminger, M.,
Exploiting Visual Artifacts to Expose Deepfakes and Face
Manipulations,
IVF19(83-92)
IEEE DOI
1902
Face, Visualization, Lighting, Estimation, Geometry
BibRef
Jeon, H.,
Bang, Y.,
Woo, S.S.,
FakeTalkerDetect: Effective and Practical Realistic Neural Talking
Head Detection with a Highly Unbalanced Dataset,
HBU19(1285-1287)
IEEE DOI
2004
face recognition, learning (artificial intelligence),
neural nets, video signal processing, FakeTalkerDetect,
few shot learning
BibRef
He, P.,
Li, H.,
Wang, H.,
Detection of Fake Images Via The Ensemble of Deep Representations
from Multi Color Spaces,
ICIP19(2299-2303)
IEEE DOI
1910
generative adversarial network, fake image detection,
multi color spaces, random forest
BibRef
Huh, M.Y.[Min-Young],
Liu, A.[Andrew],
Owens, A.[Andrew],
Efros, A.A.[Alexei A.],
Fighting Fake News: Image Splice Detection via Learned Self-Consistency,
ECCV18(XI: 106-124).
Springer DOI
1810
BibRef
Chapter on 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing continues in
Face Swapping .