Fetching the paper…
Reading the bibliography…
This paper presents a method to automatically and efficiently detect face tampering in videos, and particularly focuses on two recent techniques used to generate hyper-realistic forged videos: Deepfake and Face2Face.
Rapid object detection using a boosted cascade of simple features
P. Viola and M. Jones · 2001
Earlier work this paper cites.
Exposing digital forgeries in video by detecting double mpeg compression
W. Wang and H. Farid · 2006
Earlier work this paper cites.
Detecting re-projected video
W. Wang and H. Farid · 2008
Earlier work this paper cites.
Visualizing higher-layer features of a deep network
D. Erhan, Y. Bengio, A. Courville, and P. Vincent · 2009
Earlier work this paper cites.
A Survey Of Image Forgery Detection
H. Farid · 2009
Earlier work this paper cites.
Dlib-ml: A machine learning toolkit
D. E. King · 2009
Earlier work this paper cites.
Screenshot identification using combing artifact from interlaced video
J.-W. Lee, M.-J. Lee, T.-W. Oh, S.-J. Ryu, and H.-K. Lee · 2010
Earlier work this paper cites.
Digital image forensics: a booklet for beginners
J. A. Redi, W. Taktak, and J.-L. Dugelay · 2011
Earlier work this paper cites.
Imagenet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
Earlier work this paper cites.
An overview on video forensics
S. Milani, M. Fontani, P. Bestagini, M. Barni, A. Piva, M. Tagliasacchi, and S. Tubaro · 2012
Earlier work this paper cites.
Face animacy is not all in the eyes: Evidence from contrast chimeras
B. Balas and C. Tonsager · 2014
Cited alongside, same era.
Human perception of visual realism for photo and computer-generated face images
S. Fan, R. Wang, T.-T. Ng, C. Y.-C. Tan, J. S. Herberg, and B. L. Koenig · 2014
Cited alongside, same era.
Automatic face reenactment
P. Garrido, L. Valgaerts, O. Rehmsen, T. Thormahlen, P. Perez, and C. Theobalt · 2014
Cited alongside, same era.
Adam: A method for stochastic optimization
D. P. Kingma and J. Ba · 2014
Cited alongside, same era.
Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2014
Cited alongside, same era.
Multi-scale context aggregation by dilated convolutions
F. Yu and V. Koltun · 2015
Later among the works it cites.
A deep learning approach to universal image manipulation detection using a new convolutional layer
B. Bayar and M. C. Stamm · 2016
Later among the works it cites.
A deep learning approach to detection of splicing and copy-move forgeries in images
Y. Rao and J. Ni · 2016
Later among the works it cites.
Face2face: Real-time face capture and reenactment of rgb videos
J. Thies, M. Zollhofer, M. Stamminger, C. Theobalt, and M. Nießner · 2016
Later among the works it cites.
Aligned and non-aligned double jpeg detection using convolutional neural networks
M. Barni, L. Bondi, N. Bonettini, P. Bestagini, A. Costanzo, M. Maggini, B. Tondi, and S. Tubaro · 2017
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
N. Srivastava, G. Hinton, A. Krizhevsky, I. Sutskever, and R. Salakhutdinov · 2014
Cited alongside, same era.
Batch normalization: Accelerating deep network training by reducing internal covariate shift
S. Ioffe and C. Szegedy · 2015
Cited alongside, same era.
Image noise and digital image forensics
T. Julliand, V. Nozick, and H. Talbot · 2015
Cited alongside, same era.
Humans are easily fooled by digital images
V. Schetinger, M. M. Oliveira, R. da Silva, and T. J. Carvalho · 2015
Cited alongside, same era.
Going deeper with convolutions
C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke, A. Rabinovich, et al · 2015
Cited alongside, same era.
Xception: Deep learning with depthwise separable convolutions
F. Chollet · 2017
Later among the works it cites.
Distinguishing computer graphics from natural images using convolution neural networks
N. Rahmouni, V. Nozick, J. Yamagishi, and I. Echizen · 2017
Later among the works it cites.
W. Shi, F. Jiang, and D. Zhao · 2017
Later among the works it cites.
Faceforensics: A large-scale video dataset for forgery detection in human faces
A. Rössler, D. Cozzolino, L. Verdoliva, C. Riess, J. Thies, and M. Nießner · 2018
Closest in time.