Fetching the paper…
Reading the bibliography…
We present a learning-based method for detecting real and fake deepfake multimedia content.
The relative contribution of visual and auditory components of speech to speech intelligibility as a function of three conditions of frequency distortion
Derek A Sanders and Sharon J Goodrich. 1971 · 1971
Earlier work this paper cites.
Facial signs of emotional experience
Paul Ekman, Wallace V Freisen, and Sonia Ancoli. 1980 · 1980
Earlier work this paper cites.
The vidtimit database
Conrad Sanderson. 2002 · 2002
Earlier work this paper cites.
Vocal expression of emotion
Klaus R Scherer, Tom Johnstone, and Gundrun Klasmeyer. 2003 · 2003
Earlier work this paper cites.
Emotion analysis in man-machine interaction systems. In International Workshop on Machine Learning for Multimodal Interaction . Springer, 318–328
Themis Balomenos, Amaryllis Raouzaiou, Spiros Ioannou, Athanasios Drosopoulos, Kostas Karpouzis, and Stefanos Kollias. 2004 · 2004
Earlier work this paper cites.
Seeing to hear better: evidence for early audio-visual interactions in speech identification
Jean-Luc Schwartz, Frédéric Berthommier, and Christophe Savariaux. 2004 · 2004
Earlier work this paper cites.
Affective multimodal human-computer interaction. In Proceedings of the 13th annual ACM international conference on Multimedia . 669–676
Maja Pantic, Nicu Sebe, Jeffrey F Cohn, and Thomas Huang. 2005 · 2005
Earlier work this paper cites.
Bi-modal emotion recognition from expressive face and body gestures
Hatice Gunes and Massimo Piccardi. 2007 · 2007
Earlier work this paper cites.
Do you see what I am saying? Exploring visual enhancement of speech comprehension in noisy environments
Lars A Ross, Dave Saint-Amour, Victoria M Leavitt, Daniel C Javitt, and John J Foxe. 2007 · 2007
Earlier work this paper cites.
Beyond Facial Expressions: Learning Human Emotion from Body Gestures.. In BMVC . 1–10
Caifeng Shan, Shaogang Gong, and Peter W McOwan. 2007 · 2007
Earlier work this paper cites.
Dynamic modality weighting for multi-stream hmms inaudio-visual speech recognition. In Proceedings of the 10th international conference on Multimodal interfaces . 237–240
Mihai Gurban, Jean-Philippe Thiran, Thomas Drugman, and Thierry Dutoit. 2008 · 2008
Earlier work this paper cites.
Face alignment through subspace constrained mean-shifts. In ICCV . IEEE, 1034–1041
Jason M Saragih, Simon Lucey, and Jeffrey F Cohn. 2009 · 2009
Earlier work this paper cites.
VizWiz: nearly real-time answers to visual questions. In Proceedings of the 23nd annual ACM symposium on User interface software and technology . 333–342
Jeffrey P Bigham, Chandrika Jayant, Hanjie Ji, Greg Little, Andrew Miller, Robert C Miller, Robin Miller, Aubrey Tatarowicz, Brandyn White, Samual White, et al · 2010
Earlier work this paper cites.
Physiological signals and their use in augmenting emotion recognition for human–machine interaction
R Benjamin Knapp, Jonghwa Kim, and Elisabeth André. 2011 · 2011
Earlier work this paper cites.
Individuality in communicative bodily behaviours
Costanza Navarretta. 2012 · 2012
Earlier work this paper cites.
Facial emotion recognition for intelligent tutoring environment. In IMLCS . 9–13
Kingsley Oryina Akputu, Kah Phooi Seng, and Yun Li Lee. 2013 · 2013
Earlier work this paper cites.
Framing image description as a ranking task: Data, models and evaluation metrics
Micah Hodosh, Peter Young, and Julia Hockenmaier. 2013 · 2013
Earlier work this paper cites.
Inducing and measuring emotion and affect: Tips, tricks, and secrets
Karen S Quigley, Kristen A Lindquist, and Lisa Feldman Barrett. 2014 · 2014
Earlier work this paper cites.
pyaudioanalysis: An open-source python library for audio signal analysis
Theodoros Giannakopoulos. 2015 · 2015
Earlier work this paper cites.
Openface: an open source facial behavior analysis toolkit. In 2016 IEEE Winter Conference on Applications of Computer Vision (WACV) . IEEE, 1–10
Tadas Baltrušaitis, Peter Robinson, and Louis-Philippe Morency. 2016 · 2016
Earlier work this paper cites.
Multimedia forensics: discovering the history of multimedia contents. In Proceedings of the 17th International Conference on Computer Systems and Technologies 2016 . 5–16
Sebastiano Battiato, Oliver Giudice, and Antonino Paratore. 2016 · 2016
Earlier work this paper cites.
Emotion recognition from speech with recurrent neural networks
Vladimir Chernykh and Pavel Prikhodko. 2017 · 2017
Cited alongside, same era.
Web Video Verification Using Contextual Cues. In Proceedings of the 2nd International Workshop on Multimedia Forensics and Security (Bucharest, Romania) (MFSec ’17) . Association for Computing Machinery, New York, NY, USA, 6–10
Olga Papadopoulou, Markos Zampoglou, Symeon Papadopoulos, and Yiannis Kompatsiaris. 2017 · 2017
Cited alongside, same era.
The influence of affective cues on positive emotion in predicting instant information sharing on microblogs: Gender as a moderator
Chuang Wang, Zhongyun Zhou, Xiao-Ling Jin, Yulin Fang, and Matthew KO Lee. 2017 · 2017
Cited alongside, same era.
Two-stream neural networks for tampered face detection. In 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) . IEEE, 1831–1839
Peng Zhou, Xintong Han, Vlad I Morariu, and Larry S Davis. 2017 · 2017
Cited alongside, same era.
The Deepfake Detection Challenge (DFDC) Preview Dataset
Brian Dolhansky, Russ Howes, Ben Pflaum, Nicole Baram, and Cristian Canton Ferrer. 2019 · 2019
Later among the works it cites.
FakeTalkerDetect: Effective and Practical Realistic Neural Talking Head Detection with a Highly Unbalanced Dataset. In Proceedings of the IEEE International Conference on Computer Vision Workshops . 0–0
Hyeonseong Jeon, Youngoh Bang, and Simon S Woo. 2019 · 2019
Later among the works it cites.
Celeb-df: A new dataset for deepfake forensics
Yuezun Li, Xin Yang, Pu Sun, Honggang Qi, and Siwei Lyu. 2019 · 2019
Later among the works it cites.
Exploiting visual artifacts to expose deepfakes and face manipulations. In 2019 IEEE Winter Applications of Computer Vision Workshops (WACVW) . IEEE, 83–92
Falko Matern, Christian Riess, and Marc Stamminger. 2019 · 2019
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Mouth and voice: a relationship between visual and auditory preference in the human superior temporal sulcus
Lin L Zhu and Michael S Beauchamp. 2017 · 2017
Cited alongside, same era.
Mesonet: a compact facial video forgery detection network. In 2018 IEEE International Workshop on Information Forensics and Security (WIFS) . IEEE, 1–7
Darius Afchar, Vincent Nozick, Junichi Yamagishi, and Isao Echizen. 2018 · 2018
Cited alongside, same era.
Multimodal machine learning: A survey and taxonomy
Tadas Baltrušaitis, Chaitanya Ahuja, and Louis-Philippe Morency. 2018 · 2018
Cited alongside, same era.
Enhanced movie content similarity based on textual, auditory and visual information
Konstantinos Bougiatiotis and Theodoros Giannakopoulos. 2018 · 2018
Cited alongside, same era.
Densely connected convolutional neural network for multi-purpose image forensics under anti-forensic attacks. In Proceedings of the 6th ACM Workshop on Information Hiding and Multimedia Security . 91–96
Yifang Chen, Xiangui Kang, Z Jane Wang, and Qiong Zhang. 2018 · 2018
Cited alongside, same era.
Deep fakes: A looming challenge for privacy, democracy, and national security
Robert Chesney and Danielle Keats Citron. 2018 · 2018
Cited alongside, same era.
Deepfake video detection using recurrent neural networks. In 2018 15th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS) . IEEE, 1–6
David Güera and Edward J Delp. 2018 · 2018
Cited alongside, same era.
Deepfakes: a new threat to face recognition? assessment and detection
Pavel Korshunov and Sébastien Marcel. 2018a · 2018
Cited alongside, same era.
Trisha Mittal, Uttaran Bhattacharya, Rohan Chandra, Aniket Bera, and Dinesh Manocha. 2019 · 2019
Later among the works it cites.
Multi-task learning for detecting and segmenting manipulated facial images and videos
Huy H Nguyen, Fuming Fang, Junichi Yamagishi, and Isao Echizen. 2019a · 2019
Later among the works it cites.
Capsule-forensics: Using capsule networks to detect forged images and videos. In ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) . IEEE, 2307–2311
Huy H Nguyen, Junichi Yamagishi, and Isao Echizen. 2019b · 2019
Later among the works it cites.
The Liar’s Walk: Detecting Deception with Gait and Gesture
Tanmay Randhavane, Uttaran Bhattacharya, Kyra Kapsaskis, Kurt Gray, Aniket Bera, and Dinesh Manocha. 2019 · 2019
Later among the works it cites.
Faceforensics++: Learning to detect manipulated facial images. In Proceedings of the IEEE International Conference on Computer Vision . 1–11
Andreas Rossler, Davide Cozzolino, Luisa Verdoliva, Christian Riess, Justus Thies, and Matthias Nießner. 2019 · 2019
Later among the works it cites.
Recurrent convolutional strategies for face manipulation detection in videos
Ekraam Sabir, Jiaxin Cheng, Ayush Jaiswal, Wael AbdAlmageed, Iacopo Masi, and Prem Natarajan. 2019 · 2019
Later among the works it cites.
Exposing deep fakes using inconsistent head poses. In ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) . IEEE, 8261–8265
Xin Yang, Yuezun Li, and Siwei Lyu. 2019 · 2019
Later among the works it cites.
Faceswap: Deepfakes Software For All
[n.d.]a · 2020
Closest in time.
FakeApp 2.2.0
[n.d.] · 2020
Closest in time.
GitHub - dfaker/df: Larger resolution face masked, weirdly warped, deepfake,
[n.d.] · 2020
Closest in time.
GitHub - iperov/DeepFaceLab: DeepFaceLab is the leading software for creating deepfakes
[n.d.] · 2020
Closest in time.
GitHub - shaoanlu/faceswap-GAN: A denoising autoencoder + adversarial losses and attention mechanisms for face swapping
[n.d.]b · 2020
Closest in time.
Google AI Blog: Contributing Data to Deepfake Detection Research
[n.d.] · 2020
Closest in time.
YouTube Video 1
[n.d.] · 2020
Closest in time.
YouTube Video 2
[n.d.] · 2020
Closest in time.
DeeperForensics-1.0: A Large-Scale Dataset for Real-World Face Forgery Detection
Liming Jiang, Wayne Wu, Ren Li, Chen Qian, and Chen Change Loy. 2020 · 2020
Closest in time.