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
Yang, J.C.[Jia-Chen],
Zhu, Y.[Yong],
Xiao, S.[Shuai],
Lan, G.P.[Gui-Peng],
Li, Y.[Yang],
A controllable face forgery framework to enrich
face-privacy-protection datasets,
IVC(127), 2022, pp. 104566.
Elsevier DOI
2211
Privacy and security, Explainable artificial intelligence,
Facial forgery, Generative adversarial network, Data diversity
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Yang, X.[Xiao],
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Zhang, L.[Lei],
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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
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
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
Yu, B.Y.[Bing-Yao],
Li, X.[Xiu],
Li, W.H.[Wan-Hua],
Zhou, J.[Jie],
Lu, J.W.[Ji-Wen],
Discrepancy-Aware Meta-Learning for Zero-Shot Face Manipulation
Detection,
IP(32), 2023, pp. 3759-3773.
IEEE DOI
2307
Faces, Face recognition, Metalearning, Forgery, Task analysis,
Adaptation models, Optimization, Face manipulation detection,
zero-shot problem
BibRef
Qiu, H.[Haonan],
Chen, S.[Siyu],
Gan, B.[Bei],
Wang, K.[Kun],
Shi, H.F.[Hua-Feng],
Shao, J.[Jing],
Liu, Z.W.[Zi-Wei],
Few-shot forgery detection via Guided Adversarial Interpolation,
PR(144), 2023, pp. 109863.
Elsevier DOI
2310
Forgery detection, DeepFake, Few-shot, Face manipulation
BibRef
Liu, X.L.[Xiao-Long],
Yu, Y.[Yang],
Li, X.L.[Xiao-Long],
Zhao, Y.[Yao],
Magnifying multimodal forgery clues for Deepfake detection,
SP:IC(118), 2023, pp. 117010.
Elsevier DOI
2310
Deepfake forgery detection, Multimodal clues magnification,
Cross-modal inconsistency, Multi-scale representation
BibRef
Wu, B.[Bin],
Su, L.C.[Li-Chao],
Chen, D.[Dan],
Cheng, Y.L.[Yong-Li],
FPC-Net: Learning to detect face forgery by adaptive feature fusion
of patch correlation with CG-Loss,
IET-CV(17), No. 3, 2023, pp. 330-340.
DOI Link
2305
adaptive feature fusion, facial forgery detection
BibRef
Zhu, X.Y.[Xiang-Yu],
Fei, H.Y.[Hong-Yan],
Zhang, B.[Bin],
Zhang, T.S.[Tian-Shuo],
Zhang, X.Y.[Xiao-Yu],
Li, S.Z.[Stan Z.],
Lei, Z.[Zhen],
Face Forgery Detection by 3D Decomposition and Composition Search,
PAMI(45), No. 7, July 2023, pp. 8342-8357.
IEEE DOI
2306
Faces, Forgery, Face recognition, Feature extraction, Lighting,
Composition search, differentiable search, fake face,
3D face model
BibRef
Zhu, X.Y.[Xiang-Yu],
Wang, H.[Hao],
Fei, H.Y.[Hong-Yan],
Lei, Z.[Zhen],
Li, S.Z.[Stan Z.],
Face Forgery Detection by 3D Decomposition,
CVPR21(2928-2938)
IEEE DOI
2111
Geometry, Shape,
Face recognition, Lighting, Production
BibRef
She, H.M.[Hui-Min],
Hu, Y.J.[Yong-Jian],
Liu, B.B.[Bei-Bei],
Li, J.[Jicheng],
Li, C.T.[Chang-Tsun],
Learnable Information-Preserving Image Resizer for Face Forgery
Detection,
SPLetters(30), 2023, pp. 1657-1661.
IEEE DOI
2311
BibRef
Wang, Y.[Yukai],
Peng, C.L.[Chun-Lei],
Liu, D.[Decheng],
Wang, N.N.[Nan-Nan],
Gao, X.B.[Xin-Bo],
Spatial-Temporal Frequency Forgery Clue for Video Forgery Detection
in VIS and NIR Scenario,
CirSysVideo(33), No. 12, December 2023, pp. 7943-7956.
IEEE DOI Code:
WWW Link.
2312
BibRef
Guo, Z.Q.[Zhi-Qing],
Yang, G.[Gaobo],
Chen, J.[Jiyou],
Sun, X.M.[Xing-Ming],
Exposing Deepfake Face Forgeries With Guided Residuals,
MultMed(25), 2023, pp. 8458-8470.
IEEE DOI
2312
BibRef
Fu, Z.X.[Zhi-Xiao],
Chen, X.Y.[Xin-Yuan],
Liu, D.[Daizong],
Qu, X.Y.[Xiao-Ye],
Dong, J.F.[Jian-Feng],
Zhang, X.H.[Xu-Hong],
Ji, S.[Shouling],
Multi-level feature disentanglement network for cross-dataset face
forgery detection,
IVC(135), 2023, pp. 104686.
Elsevier DOI
2306
Face forgery detection, Cross-dataset evaluation,
Multi-level representation, Feature disentangling, Adversarial learning
BibRef
Xiao, S.[Shuai],
Lan, G.[Guipeng],
Yang, J.C.[Jia-Chen],
Lu, W.[Wen],
Meng, Q.G.[Qing-Gang],
Gao, X.B.[Xin-Bo],
MCS-GAN: A Different Understanding for Generalization of Deep Forgery
Detection,
MultMed(26), 2024, pp. 1333-1345.
IEEE DOI
2402
Forgery, Faces, Deepfakes, Anomaly detection,
Generative adversarial networks, Data models, Feature extraction,
image reconstruction
BibRef
Guo, Z.Q.[Zhi-Qing],
Wang, L.[Liejun],
Yang, W.Z.[Wen-Zhong],
Yang, G.[Gaobo],
Li, K.Q.[Ke-Qin],
LDFnet: Lightweight Dynamic Fusion Network for Face Forgery Detection
by Integrating Local Artifacts and Global Texture Information,
CirSysVideo(34), No. 2, February 2024, pp. 1255-1265.
IEEE DOI
2402
Forgery, Faces, Feature extraction, Face recognition, Visualization,
Magnetic heads, Computational modeling, Face forgery detection,
dynamic fusion
BibRef
Liu, D.[Decheng],
Zheng, Z.[Zeyang],
Peng, C.L.[Chun-Lei],
Wang, Y.[Yukai],
Wang, N.N.[Nan-Nan],
Gao, X.B.[Xin-Bo],
Hierarchical Forgery Classifier on Multi-Modality Face Forgery Clues,
MultMed(26), 2024, pp. 2894-2905.
IEEE DOI
2402
Forgery, Faces, Face recognition, Feature extraction, Videos,
Task analysis, Frequency-domain analysis, Face forgery detection,
hierarchical classifier
BibRef
Yu, Y.[Yang],
Ni, R.R.[Rong-Rong],
Yang, S.Y.[Si-Yuan],
Zhao, Y.[Yao],
Kot, A.C.[Alex C.],
Narrowing Domain Gaps With Bridging Samples for Generalized Face
Forgery Detection,
MultMed(26), 2024, pp. 3405-3417.
IEEE DOI
2402
Faces, Forgery, Feature extraction, Finite element analysis,
Generative adversarial networks, Nickel,
cross-domain alignment
BibRef
Ghosh, T.[Tanusree],
Naskar, R.[Ruchira],
Less is more: A minimalist approach to robust GAN-generated face
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PRL(179), 2024, pp. 185-191.
Elsevier DOI
2403
Fake image detection, Deepfake detection, GAN forensics,
Digital image forensics, Synthetic image detection, GAN-face detection
BibRef
N, A.R.P.[Aravinda Reddy P],
Ramachandra, R.[Raghavendra],
Rao, K.S.[Krothapalli Sreenivasa],
Mitra, P.[Pabitra],
MLSD-GAN: Generating Strong High Quality Face Morphing Attacks Using
Latent Semantic Disentanglement,
ICCVMI23(1-6)
IEEE DOI
2403
Training, Interpolation, Face recognition,
Semantics, Machine intelligence, Biometrics, Face recognition, bStyleGAN
BibRef
Huang, J.J.[Jia-Jun],
Du, C.B.[Cheng-Bin],
Zhu, X.[Xinqi],
Ma, S.Q.[Si-Qi],
Nepal, S.[Surya],
Xu, C.[Chang],
Anti-Compression Contrastive Facial Forgery Detection,
MultMed(26), 2024, pp. 6166-6177.
IEEE DOI
2404
Forgery, Image coding, Deepfakes, Data models, Faces, Training,
Feature extraction, Facial forgery detection,
anti-compression
BibRef
Bai, W.M.[Wei-Ming],
Liu, Y.F.[Yu-Fan],
Zhang, Z.P.[Zhi-Peng],
Li, B.[Bing],
Hu, W.M.[Wei-Ming],
AUNet: Learning Relations Between Action Units for Face Forgery
Detection,
CVPR23(24709-24719)
IEEE DOI
2309
BibRef
Shi, L.[Liang],
Zhang, J.[Jie],
Liang, C.Y.[Chen-Yue],
Shan, S.G.[Shi-Guang],
Unknown Aware Feature Learning for Face Forgery Detection,
FG21(1-5)
IEEE DOI
2303
Representation learning, Face recognition,
Predictive models, Benchmark testing, Forgery
BibRef
Zhu, Y.Z.[Yi-Zhe],
Gao, J.L.[Jia-Lin],
Liu, Q.[Qiong],
Zhou, X.[Xi],
Attention-guided Fine-grained Feature Learning For Robust Face
Forgery Detection,
ICPR22(1222-1228)
IEEE DOI
2212
Representation learning, Face recognition,
Frequency-domain analysis, Perturbation methods, Semantics,
Streaming media
BibRef
Zhuang, W.[Wanyi],
Chu, Q.[Qi],
Tan, Z.T.[Zhen-Tao],
Liu, Q.K.[Qian-Kun],
Yuan, H.J.[Hao-Jie],
Miao, C.T.[Chang-Tao],
Luo, Z.X.[Zi-Xiang],
Yu, N.H.[Neng-Hai],
UIA-ViT: Unsupervised Inconsistency-Aware Method Based on Vision
Transformer for Face Forgery Detection,
ECCV22(V:391-407).
Springer DOI
2211
BibRef
Sun, K.[Ke],
Liu, H.[Hong],
Yao, T.P.[Tai-Ping],
Sun, X.S.[Xiao-Shuai],
Chen, S.[Shen],
Ding, S.H.[Shou-Hong],
Ji, R.R.[Rong-Rong],
An Information Theoretic Approach for Attention-Driven Face Forgery
Detection,
ECCV22(XIV:111-127).
Springer DOI
2211
BibRef
Liang, J.H.[Jia-Hao],
Shi, H.F.[Hua-Feng],
Deng, W.H.[Wei-Hong],
Exploring Disentangled Content Information for Face Forgery Detection,
ECCV22(XIV:128-145).
Springer DOI
2211
BibRef
Song, L.[Luchuan],
Fang, Z.[Zheng],
Li, X.D.[Xiao-Dan],
Dong, X.Y.[Xiao-Yi],
Jin, Z.C.[Zhen-Chao],
Chen, Y.F.[Yue-Feng],
Lyu, S.W.[Si-Wei],
Adaptive Face Forgery Detection in Cross Domain,
ECCV22(XXXIV:467-484).
Springer DOI
2211
BibRef
Ni, Y.S.[Yun-Sheng],
Meng, D.[Depu],
Yu, C.Q.[Chang-Qian],
Quan, C.B.[Cheng-Bin],
Ren, D.C.[Dong-Chun],
Zhao, Y.J.[You-Jian],
CORE: Consistent Representation Learning for Face Forgery Detection,
WMF22(12-21)
IEEE DOI
2210
Representation learning, Codes, Face recognition,
Market research, Forgery
BibRef
Cao, J.[Junyi],
Ma, C.[Chao],
Yao, T.P.[Tai-Ping],
Chen, S.[Shen],
Ding, S.H.[Shou-Hong],
Yang, X.K.[Xiao-Kang],
End-to-End Reconstruction-Classification Learning for Face Forgery
Detection,
CVPR22(4103-4112)
IEEE DOI
2210
Training, Visualization, Face recognition, Benchmark testing,
Forgery, Cognition, Robustness, Face and gestures, Biometrics
BibRef
Jia, S.[Shuai],
Ma, C.[Chao],
Yao, T.P.[Tai-Ping],
Yin, B.[Bangjie],
Ding, S.H.[Shou-Hong],
Yang, X.K.[Xiao-Kang],
Exploring Frequency Adversarial Attacks for Face Forgery Detection,
CVPR22(4093-4102)
IEEE DOI
2210
Visualization, Face recognition, Frequency-domain analysis,
Perturbation methods, Computational modeling, Detectors,
Face and gestures
BibRef
Fei, J.W.[Jian-Wei],
Dai, Y.S.[Yun-Shu],
Yu, P.P.[Pei-Peng],
Shen, T.R.[Tian-Run],
Xia, Z.H.[Zhi-Hua],
Weng, J.[Jian],
Learning Second Order Local Anomaly for General Face Forgery
Detection,
CVPR22(20238-20248)
IEEE DOI
2210
Representation learning, Adaptation models, Annotations,
Face recognition, Forgery, Filtering theory, Biometrics,
Representation learning
BibRef
Liu, J.[Jie],
Wang, J.J.[Jing-Jing],
Zhang, P.[Peng],
Wang, C.[Chunmao],
Xie, D.[Di],
Pu, S.L.[Shi-Liang],
Multi-scale Wavelet Transformer for Face Forgery Detection,
ACCV22(VI:52-68).
Springer DOI
2307
BibRef
Yang, P.[Puning],
Huang, H.B.[Huai-Bo],
Wang, Z.Y.[Zhi-Yong],
Yu, A.[Aijing],
He, R.[Ran],
Confidence-calibrated Face Image Forgery Detection with Contrastive
Representation Distillation,
ACCV22(IV:3-19).
Springer DOI
2307
BibRef
Chen, H.[Han],
Lin, Y.Z.[Yu-Zhen],
Li, B.[Bin],
Exposing Face Forgery Clues via Retinex-based Image Enhancement,
ACCV22(IV:20-34).
Springer DOI
2307
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
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
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
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
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
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
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
Luo, Y.C.[Yu-Chen],
Zhang, Y.[Yong],
Yan, J.C.[Jun-Chi],
Liu, W.[Wei],
Generalizing Face Forgery Detection with High-frequency Features,
CVPR21(16312-16321)
IEEE DOI
2111
Training, Correlation, Image color analysis, Databases,
Face recognition, Detectors, Feature extraction
BibRef
Li, J.M.[Jia-Ming],
Xie, H.T.[Hong-Tao],
Li, J.H.[Jia-Hong],
Wang, Z.Y.[Zhong-Yuan],
Zhang, Y.D.[Yong-Dong],
Frequency-aware Discriminative Feature Learning Supervised by
Single-Center Loss for Face Forgery Detection,
CVPR21(6454-6463)
IEEE DOI
2111
Measurement, Face recognition,
Frequency-domain analysis, Filter banks, Boosting, Forgery
BibRef
Zhou, T.F.[Tian-Fei],
Wang, W.G.[Wen-Guan],
Liang, Z.Y.[Zhi-Yuan],
Shen, J.B.[Jian-Bing],
Face Forensics in the Wild,
CVPR21(5774-5784)
IEEE DOI
2111
Location awareness, Costs, Face recognition, Forensics,
Benchmark testing, Forgery, Classification algorithms
BibRef
He, Y.N.[Yi-Nan],
Gan, B.[Bei],
Chen, S.[Siyu],
Zhou, Y.C.[Yi-Chun],
Yin, G.J.[Guo-Jun],
Song, L.C.[Lu-Chuan],
Sheng, L.[Lu],
Shao, J.[Jing],
Liu, Z.W.[Zi-Wei],
ForgeryNet: A Versatile Benchmark for Comprehensive Forgery Analysis,
CVPR21(4358-4367)
IEEE DOI
2111
Location awareness, Image segmentation, Technological innovation,
Annotations, Face recognition, Perturbation methods, Benchmark testing
BibRef
Liu, H.G.[Hong-Gu],
Li, X.D.[Xiao-Dan],
Zhou, W.B.[Wen-Bo],
Chen, Y.F.[Yue-Feng],
He, Y.[Yuan],
Xue, H.[Hui],
Zhang, W.M.[Wei-Ming],
Yu, N.H.[Neng-Hai],
Spatial-Phase Shallow Learning:
Rethinking Face Forgery Detection in Frequency Domain,
CVPR21(772-781)
IEEE DOI
2111
Face recognition, Frequency-domain analysis,
Semantics, Forgery, Robustness, Security
BibRef
Wang, C.R.[Cheng-Rui],
Deng, W.H.[Wei-Hong],
Representative Forgery Mining for Fake Face Detection,
CVPR21(14918-14927)
IEEE DOI
2111
Codes, Face recognition, Refining, Training data, Data visualization,
Detectors, Forgery
BibRef
Schwarcz, S.[Steven],
Chellappa, R.[Rama],
Finding Facial Forgery Artifacts with Parts-Based Detectors,
WMF21(933-942)
IEEE DOI
2109
Deep learning, Social networking (online),
Face recognition, Neural networks, Detectors
BibRef
Han, J.[Jian],
Gevers, T.[Theo],
MMD Based Discriminative Learning for Face Forgery Detection,
ACCV20(V:121-136).
Springer DOI
2103
BibRef
Tarasiou, M.,
Zafeiriou, S.P.,
Extracting Deep Local Features to Detect Manipulated Images of Human
Faces,
ICIP20(1821-1825)
IEEE DOI
2011
Faces, Feature extraction, Training, Forgery, Task analysis,
Videos, Image segmentation
BibRef
Huang, R.,
Fang, F.,
Nguyen, H.H.,
Yamagishi, J.,
Echizen, I.,
Security of Facial Forensics Models Against Adversarial Attacks,
ICIP20(2236-2240)
IEEE DOI
2011
Perturbation methods, Image segmentation, Neurons,
Linear programming, Security, Forensics, Forgery, forgery forensics,
over-firing
BibRef
Li, L.,
Bao, J.,
Yang, H.,
Chen, D.,
Wen, F.,
Advancing High Fidelity Identity Swapping for Forgery Detection,
CVPR20(5073-5082)
IEEE DOI
2008
Face, Lighting, Image resolution, Adaptive systems, Shape, Generators, Training
BibRef
Hulzebosch, N.,
Ibrahimi, S.,
Worring, M.,
Detecting CNN-Generated Facial Images in Real-World Scenarios,
WMF20(2729-2738)
IEEE DOI
2008
Training, Image color analysis, Data models,
Visualization, Forgery, Image resolution
BibRef
Jiang, L.,
Li, R.,
Wu, W.,
Qian, C.,
Loy, C.C.,
DeeperForensics-1.0: A Large-Scale Dataset for Real-World Face
Forgery Detection,
CVPR20(2886-2895)
IEEE DOI
2008
Videos, Face, Forgery, Benchmark testing, Perturbation methods,
Data collection, Lighting
BibRef
Wang, Z.D.[Zhen-Dong],
Bao, J.M.[Jian-Min],
Zhou, W.G.[Wen-Gang],
Wang, W.L.[Wei-Lun],
Li, H.Q.[Hou-Qiang],
AltFreezing for More General Video Face Forgery Detection,
CVPR23(4129-4138)
IEEE DOI
2309
BibRef
Zheng, Y.L.[Ying-Lin],
Bao, J.M.[Jian-Min],
Chen, D.[Dong],
Zeng, M.[Ming],
Wen, F.[Fang],
Exploring Temporal Coherence for More General Video Face Forgery
Detection,
ICCV21(15024-15034)
IEEE DOI
2203
Convolution, Coherence, Transformers, Feature extraction, Forgery,
Robustness, Kernel,
Video analysis and understanding
BibRef
Li, L.Z.[Ling-Zhi],
Bao, J.M.[Jian-Min],
Zhang, T.[Ting],
Yang, H.[Hao],
Chen, D.[Dong],
Wen, F.[Fang],
Guo, B.N.[Bai-Ning],
Face X-Ray for More General Face Forgery Detection,
CVPR20(5000-5009)
IEEE DOI
2008
Face, Forgery, X-ray imaging, Image color analysis, Detectors,
Forensics, Focusing
BibRef
Dang, H.,
Liu, F.,
Stehouwer, J.,
Liu, X.,
Jain, A.K.,
On the Detection of Digital Face Manipulation,
CVPR20(5780-5789)
IEEE DOI
2008
Face, Forgery, Videos, Machine learning, Cameras
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Chapter on 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing continues in
Emotions in Face Animation, Video Face Synthesis .