Towards Understanding Perceptual Differences between Genuine and Face-Swapped Videos
暂无分享,去创建一个
Leslie Wöhler | Marcus Magnor | Susana Castillo | Martin Zembaty | M. Magnor | Susana Castillo | L. Wöhler | Martin Zembaty
[1] H. Bülthoff,et al. The MPI Facial Expression Database — A Validated Database of Emotional and Conversational Facial Expressions , 2012, PloS one.
[2] K. Munhall,et al. Spatial statistics of gaze fixations during dynamic face processing , 2007, Social neuroscience.
[3] Andreas Rössler,et al. FaceForensics: A Large-scale Video Dataset for Forgery Detection in Human Faces , 2018, ArXiv.
[4] P. Ekman,et al. Pan-Cultural Elements in Facial Displays of Emotion , 1969, Science.
[5] Corinna E. Löckenhoff,et al. Age differences in recognition of emotion in lexical stimuli and facial expressions. , 2007, Psychology and aging.
[6] Mario Fritz,et al. It’s Written All Over Your Face: Full-Face Appearance-Based Gaze Estimation , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
[7] Andrew Owens,et al. CNN-Generated Images Are Surprisingly Easy to Spot… for Now , 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[8] Hao Li,et al. Protecting World Leaders Against Deep Fakes , 2019, CVPR Workshops.
[9] L F Dell'Osso,et al. Eyes as the Center of Focus in the Visual Examination of Human Faces , 1978, Perceptual and motor skills.
[10] Chen Change Loy,et al. DeeperForensics-1.0: A Large-Scale Dataset for Real-World Face Forgery Detection , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[11] Leslie Wöhler,et al. PEFS: A Validated Dataset for Perceptual Experiments on Face Swap Portrait Videos , 2020, Communications in Computer and Information Science.
[12] P. Hills,et al. Eye-tracking the own-gender bias in face recognition: Other-gender faces are viewed differently to own-gender faces , 2016 .
[13] Lucas Theis,et al. Fast Face-Swap Using Convolutional Neural Networks , 2016, 2017 IEEE International Conference on Computer Vision (ICCV).
[14] Haibin Ling,et al. Revisiting Video Saliency Prediction in the Deep Learning Era , 2021, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[15] S. Pollak,et al. Probabilistic learning of emotion categories. , 2019, Journal of experimental psychology. General.
[16] Tim H. W. Cornelissen,et al. A Validation of Automatically-Generated Areas-of-Interest in Videos of a Face for Eye-Tracking Research , 2018, Front. Psychol..
[17] S. Yantis,et al. Visual attention: control, representation, and time course. , 1997, Annual review of psychology.
[18] Tal Hassner,et al. FSGAN: Subject Agnostic Face Swapping and Reenactment , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[19] S. Demleitner. [Communication without words]. , 1997, Pflege aktuell.
[20] Diego Gutierrez,et al. Using eye-tracking to assess different image retargeting methods , 2011, APGV '11.
[21] I. Gilchrist,et al. Does narrative drive dynamic attention to a prolonged stimulus? , 2018, Cognitive research: principles and implications.
[22] Heinrich H. Bülthoff,et al. Evaluation of real-world and computer-generated stylized facial expressions , 2007, TAP.
[23] Effie J. Pereira,et al. The eyes do not have it after all? Attention is not automatically biased towards faces and eyes , 2019, Psychological Research.
[24] Sumit Kumar Jha,et al. Predicting Heart Rate Variations of Deepfake Videos using Neural ODE , 2019, 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW).
[25] B. Mesquita,et al. Context in Emotion Perception , 2011 .
[26] J. Henderson,et al. Do the eyes really have it? Dynamic allocation of attention when viewing moving faces. , 2012, Journal of vision.
[27] Davis E. King,et al. Dlib-ml: A Machine Learning Toolkit , 2009, J. Mach. Learn. Res..
[28] Siwei Lyu,et al. Exposing DeepFake Videos By Detecting Face Warping Artifacts , 2018, CVPR Workshops.
[29] Andrew Chadwick,et al. Deepfakes and Disinformation: Exploring the Impact of Synthetic Political Video on Deception, Uncertainty, and Trust in News , 2020, Social Media + Society.
[30] Frédo Durand,et al. Learning to predict where humans look , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[31] Junichi Yamagishi,et al. MesoNet: a Compact Facial Video Forgery Detection Network , 2018, 2018 IEEE International Workshop on Information Forensics and Security (WIFS).
[32] Xiongkuo Min,et al. Influence of compression artifacts on visual attention , 2014, 2014 IEEE International Conference on Multimedia and Expo (ICME).
[33] John M. Henderson,et al. Clustering of Gaze During Dynamic Scene Viewing is Predicted by Motion , 2011, Cognitive Computation.
[34] N. J. Cohen,et al. Eye-movement-based memory effect: a reprocessing effect in face perception. , 1999, Journal of experimental psychology. Learning, memory, and cognition.
[35] G. Rousselet,et al. Is it an animal? Is it a human face? Fast processing in upright and inverted natural scenes. , 2003, Journal of vision.
[36] Abhinav Dhall,et al. The eyes know it: FakeET- An Eye-tracking Database to Understand Deepfake Perception , 2020, ICMI.
[37] J. Fernández-Dols,et al. Neutral faces in context: Their emotional meaning and their function , 1994 .
[38] Andreas Rössler,et al. FaceForensics++: Learning to Detect Manipulated Facial Images , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[39] C. Collin,et al. Faces elicit different scanning patterns depending on task demands , 2017, Attention, perception & psychophysics.
[40] Edward J. Delp,et al. Deepfake Video Detection Using Recurrent Neural Networks , 2018, 2018 15th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS).
[41] G. Kuhn,et al. Why are you looking at me? It’s because I’m talking, but mostly because I’m staring or not doing much , 2018, Attention, perception & psychophysics.
[42] B. Rossion,et al. Fixation Patterns During Recognition of Personally Familiar and Unfamiliar Faces , 2010, Front. Psychology.
[43] A. Kingstone,et al. Human Social Attention , 2009, Annals of the New York Academy of Sciences.
[44] Siwei Lyu,et al. In Ictu Oculi: Exposing AI Created Fake Videos by Detecting Eye Blinking , 2018, 2018 IEEE International Workshop on Information Forensics and Security (WIFS).
[45] Pia Rotshtein,et al. Identification of Emotional Facial Expressions: Effects of Expression, Intensity, and Sex on Eye Gaze , 2016, PloS one.
[46] Julian Fierrez,et al. GANprintR: Improved Fakes and Evaluation of the State of the Art in Face Manipulation Detection , 2019, IEEE Journal of Selected Topics in Signal Processing.
[47] Sebastian Bosse,et al. Psychophysiology-Based QoE Assessment: A Survey , 2017, IEEE Journal of Selected Topics in Signal Processing.
[48] G. Zelinsky. Understanding scene understanding , 2013, Front. Psychol..
[49] Wojciech Matusik,et al. Eye Tracking for Everyone , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[50] D. Isaacowitz,et al. Age effects and gaze patterns in recognising emotional expressions: An in-depth look at gaze measures and covariates , 2010 .
[51] A. J. Fridlund,et al. Facial Expressions , 2018, Encyclopedia of Evolutionary Psychological Science.
[52] G. Alpers,et al. Happy mouth and sad eyes: scanning emotional facial expressions. , 2011, Emotion.
[53] Marcus A. Magnor,et al. Comparative Analysis of Three Different Modalities for Perception of Artifacts in Videos , 2017, TAP.
[54] Hans-Peter Seidel,et al. Learning to Predict Localized Distortions in Rendered Images , 2013, Comput. Graph. Forum.
[55] Yoshua Bengio,et al. Generative Adversarial Nets , 2014, NIPS.
[56] Xin Yang,et al. Exposing Deep Fakes Using Inconsistent Head Poses , 2018, ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[57] O. Grüsser,et al. Gaze motor asymmetries in the perception of faces during a memory task , 1993, Neuropsychologia.
[58] Matthias Kohring,et al. Mistrust, Disinforming News, and Vote Choice: A Panel Survey on the Origins and Consequences of Believing Disinformation in the 2017 German Parliamentary Election , 2020, Political Communication.
[59] Hui Zhang,et al. A Generalized and Robust Method Towards Practical Gaze Estimation on Smart Phone , 2019, 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW).
[60] L. Nummenmaa,et al. Eye-movement assessment of the time course in facial expression recognition: Neurophysiological implications , 2009, Cognitive, affective & behavioral neuroscience.
[61] H. Bülthoff,et al. The contribution of different facial regions to the recognition of conversational expressions. , 2008, Journal of vision.
[62] Tal Hassner,et al. On Face Segmentation, Face Swapping, and Face Perception , 2017, 2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018).
[63] Christian Wallraven,et al. The semantic space for facial communication , 2014, Comput. Animat. Virtual Worlds.
[64] Charissa R Lansing,et al. Word identification and eye fixation locations in visual and visual-plus-auditory presentations of spoken sentences , 2003, Perception & psychophysics.
[65] N. Helberger,et al. Do (Microtargeted) Deepfakes Have Real Effects on Political Attitudes , 2020 .