Fetching the paper…
Reading the bibliography…
Distinguishing manipulated from real images is becoming increasingly difficult as new sophisticated image forgery approaches come out by the day.
Domain adaptation for large-scale sentiment classification: A deep learning approach
X. Glorot, A. Bordes, and Y. Bengio · 2011
Earlier work this paper cites.
Marginalized denoising autoencoders for domain adaptation
M. Chen, Z. Xu, K.Q. Weinberger, and F. Sha · 2012
Earlier work this paper cites.
Image Forgery Localization via Fine-Grained Analysis of CFA Artifacts
P. Ferrara, T. Bianchi, A. De Rosa, and A. Piva · 2012
Earlier work this paper cites.
Exposing digital image forgeries by illumination color classification
T. de Carvalho, C. Riess, E. Angelopoulou, H. Pedrini, and A. Rocha · 2013
Earlier work this paper cites.
Exposing region splicing forgeries with blind local noise estimation
S. Lyu, X. Pan, and X. Zhang · 2014
Earlier work this paper cites.
Deep transfer metric learning
J. Hu, J. Lu, and Y. Tan · 2015
Earlier work this paper cites.
Deep learning face attributes in the wild
Ziwei Liu, Ping Luo, Xiaogang Wang, and Xiaoou Tang · 2015
Earlier work this paper cites.
ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, Alexander C. Berg, and Li Fei-Fei · 2015
Earlier work this paper cites.
Going deeper with convolutions
C. Szegedy, Wei Liu, Yangqing Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke, and A. Rabinovich · 2015
Earlier work this paper cites.
Learning a Discriminative Model for the Perception of Realism in Composite Images
J.-Y. Zhu, P. Krähenbühl, E. Shechtman, and A.A. Efros · 2015
Earlier work this paper cites.
A deep learning approach to universal image manipulation detection using a new convolutional layer
B. Bayar and M.C. Stamm · 2016
Earlier work this paper cites.
Photo Forensics
H. Farid · 2016
Earlier work this paper cites.
Large-margin softmax loss for convolutional neural networks
W. Liu et al · 2016
Earlier work this paper cites.
A deep learning approach to detection of splicing and copy-move forgeries in images
Y. Rao and J. Ni · 2016
Earlier work this paper cites.
Face2Face: Real-Time Face Capture and Reenactment of RGB Videos
J. Thies, M. Zollhöfer, M. Stamminger, C. Theobalt, and M. Nießner · 2016
Earlier work this paper cites.
Matching networks for one shot learning
O. Vinyals, C. Blundell, T. Lillicrap, K. Kavukcuoglu, and D. Wierstra · 2016
Earlier work this paper cites.
Learning deep features for discriminative localization
Bolei Zhou, Aditya Khosla, Agata Lapedriza, Aude Oliva, and Antonio Torralba · 2016
Earlier work this paper cites.
Photo Forensics from JPEG Dimples
S. Agarwal and H. Farid · 2017
Earlier work this paper cites.
Bringing portraits to life
Hadar Averbuch-Elor, Daniel Cohen-Or, Johannes Kopf, and Michael F. Cohen · 2017
Earlier work this paper cites.
Exploiting spatial structure for localizing manipulated image regions
J.H. Bappy, A.K. Roy-Chowdhury, J. Bunk, L. Nataraj, and B.S. Manjunath · 2017
Cited alongside, same era.
Xception: Deep Learning with Depthwise Separable Convolutions
F. Chollet · 2017
Cited alongside, same era.
Recasting residual-based local descriptors as convolutional neural networks: an application to image forgery detection
D. Cozzolino, G. Poggi, and L. Verdoliva · 2017
Cited alongside, same era.
A Comprehensive Survey on Domain Adaptation for Visual Applications
Gabriela Csurka · 2017
Cited alongside, same era.
Cycada: Cycle-consistent adversarial domain adaptation
Judy Hoffman, Eric Tzeng, Taesung Park, Jun-Yan Zhu, Phillip Isola, Kate Saenko, Alexei A Efros, and Trevor Darrell · 2017
Cited alongside, same era.
Progressive Growing of GANs for Improved Quality, Stability, and Variation
Tero Karras, Timo Aila, Samuli Laine, and Jaakko Lehtinen · 2018
Closest in time.
Deep Video Portraits
H. Kim, P. Garrido, A. Tewari, W. Xu, J. Thies M. Nießner, P. Pérez, C. Richardt, M. Zollhöfer, and C. Theobalt · 2018
Closest in time.
Glow: Generative flow with invertible 1x1 convolutions
D.P. Kingma and P. Dhariwal · 2018
Closest in time.
Generative semantic manipulation with mask-contrasting gan
X. Liang, H. Zhang, L. Lin, and E. Xing · 2018
Closest in time.
Image forgery localization based on multi-scale convolutional neural networks
Y. Liu, Q. Guan, X. Zhao, and Y. Cao · 2018
Closest in time.
Detection of GAN-Generated Fake Images over Social Networks
F. Marra, D. Gragnaniello, D. Cozzolino, and L. Verdoliva · 2018
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Satoshi Iizuka, Edgar Simo-Serra, and Hiroshi Ishikawa · 2017
Cited alongside, same era.
Semantic autoencoder for zero-shot learning
E. Kodirov, T. Xiang, and S. Gong · 2017
Cited alongside, same era.
Few-shot adversarial domain adaptation
S. Motiian, Q. Jones, S. Iranmanesh, and G. Doretto · 2017
Cited alongside, same era.
Distinguishing computer graphics from natural images using convolution neural networks
N. Rahmouni, V. Nozick, J. Yamagishi, and I. Echizeny · 2017
Cited alongside, same era.
Prototypical networks for few-shot learning
J. Snell, K. Swersky, and R. Zemel · 2017
Cited alongside, same era.
Synthesizing Obama: learning lip sync from audio
Supasorn Suwajanakorn, Steven M Seitz, and Ira Kemelmacher-Shlizerman · 2017
Cited alongside, same era.
Adversarial discriminative domain adaptation
Eric Tzeng, Judy Hoffman, Kate Saenko, and Trevor Darrell · 2017
Cited alongside, same era.
Closest in time.
GANimation: Anatomically-aware Facial Animation from a Single Image
A. Pumarola, A. Agudo, A.M. Martinez, A. Sanfeliu, and F. Moreno-Noguer · 2018
Closest in time.
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.
Image Splicing Localization using a Multi-task Fully Convolutional Network (MFCN)
R. Salloum, Y. Ren, and C. C. Jay Kuo · 2018
Closest in time.
Learning to compare: Relation network for few-shot learning
F. Sung, Y. Yang, L. Zhang, T. Xiang, P. H.S. Torr, and T. M. Hospedales · 2018
Closest in time.
Recent advances in autoencoder-based representation learning
M. Tschannen, O. Bachem, and M. Lucic · 2018
Closest in time.
Digital image forgery detection based on lens and sensor aberration
I. Yerushalmy and H. Hel-Or · 2018
Closest in time.
Generative image inpainting with contextual attention
Jiahui Yu, Zhe Lin, Jimei Yang, Xiaohui Shen, Xin Lu, and Thomas S Huang · 2018
Closest in time.
Learning rich features for image manipulation detection
P. Zhou, X. Han, V.I. Morariu, and L.S. Davis · 2018
Closest in time.
A closer look at few shot classification
W.-Y. Chen, Y.-C. Liu, Z. Kira, Y.-C. Frank Wang, and J.-B. Huang · 2019
Closest in time.
A style-based generator architecture for generative adversarial networks
T. Karras et al · 2019
Closest in time.
Detecting and Simulating Artifacts in GAN Fake Images
X. Zhang, S. Karaman, and S.-F. Chang · 2019
Closest in time.
Noiseprint: a CNN-based camera model fingerprint
D. Cozzolino and L. Verdoliva · 2020
Closest in time.