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Deepfake attacks, malicious manipulation of media containing people, are a serious concern for society.
300 faces in-the-wild challenge: The first facial landmark localization challenge
Christos Sagonas, Georgios Tzimiropoulos, Stefanos Zafeiriou, and Maja Pantic · 2013
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Microsoft coco: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014
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Detecting check-worthy factual claims in presidential debates
Naeemul Hassan, Chengkai Li, and Mark Tremayne · 2015
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Ms-celeb-1m: A dataset and benchmark for large-scale face recognition
Yandong Guo, Lei Zhang, Yuxiao Hu, Xiaodong He, and Jianfeng Gao · 2016
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Photo forensics from jpeg dimples
Shruti Agarwal and Hany Farid · 2017
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Fast face-swap using convolutional neural networks
Iryna Korshunova, Wenzhe Shi, Joni Dambre, and Lucas Theis · 2017
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Truth of varying shades: Analyzing language in fake news and political fact-checking
Hannah Rashkin, Eunsol Choi, Jin Yea Jang, Svitlana Volkova, and Yejin Choi · 2017
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Residual attention network for image classification
Fei Wang, Mengqing Jiang, Chen Qian, Shuo Yang, Cheng Li, Honggang Zhang, Xiaogang Wang, and Xiaoou Tang · 2017
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Towards open-set identity preserving face synthesis
Jianmin Bao, Dong Chen, Fang Wen, Houqiang Li, and Gang Hua · 2018
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Transfer learning from speaker verification to multispeaker text-to-speech synthesis
Ye Jia, Yu Zhang, Ron Weiss, Quan Wang, Jonathan Shen, Fei Ren, Patrick Nguyen, Ruoming Pang, Ignacio Lopez Moreno, Yonghui Wu, et al · 2018
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The deepfake detection challenge (dfdc) preview dataset
Brian Dolhansky, Russ Howes, Ben Pflaum, Nicole Baram, and Cristian Canton Ferrer · 2019
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A style-based generator architecture for generative adversarial networks
Tero Karras, Samuli Laine, and Timo Aila · 2019
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Capsule-forensics: Using capsule networks to detect forged images and videos
Huy H Nguyen, Junichi Yamagishi, and Isao Echizen · 2019
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Fsgan: Subject agnostic face swapping and reenactment
Yuval Nirkin, Yosi Keller, and Tal Hassner · 2019
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FaceForensics++: Learning to detect manipulated facial images
Andreas Rössler, Davide Cozzolino, Luisa Verdoliva, Christian Riess, Justus Thies, and Matthias Nießner · 2019
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Efficientnet: Rethinking model scaling for convolutional neural networks
Mingxing Tan and Quoc Le · 2019
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Detecting photoshopped faces by scripting photoshop
Sheng-Yu Wang, Oliver Wang, Andrew Owens, Richard Zhang, and Alexei A Efros · 2019
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What makes fake images detectable? understanding properties that generalize
Lucy Chai, David Bau, Ser-Nam Lim, and Phillip Isola · 2020
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Not made for each other-audio-visual dissonance-based deepfake detection and localization
Komal Chugh, Parul Gupta, Abhinav Dhall, and Ramanathan Subramanian · 2020
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On the detection of digital face manipulation
Hao Dang, Feng Liu, Joel Stehouwer, Xiaoming Liu, and Anil K Jain · 2020
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Leveraging frequency analysis for deep fake image recognition
Joel Frank, Thorsten Eisenhofer, Lea Schönherr, Asja Fischer, Dorothea Kolossa, and Thorsten Holz · 2020
Cited alongside, same era.
Bootstrap your own latent-a new approach to self-supervised learning
Jean-Bastien Grill, Florian Strub, Florent Altché, Corentin Tallec, Pierre Richemond, Elena Buchatskaya, Carl Doersch, Bernardo Avila Pires, Zhaohan Guo, Mohammad Gheshlaghi Azar, et al · 2020
Cited alongside, same era.
Celeb-df: A large-scale challenging dataset for deepfake forensics
Yuezun Li, Xin Yang, Pu Sun, Honggang Qi, and Siwei Lyu · 2020
Cited alongside, same era.
Emotions don’t lie: An audio-visual deepfake detection method using affective cues
Trisha Mittal, Uttaran Bhattacharya, Rohan Chandra, Aniket Bera, and Dinesh Manocha · 2020
Cited alongside, same era.
Deepfacelab: Integrated, flexible and extensible face-swapping framework
Ivan Perov, Daiheng Gao, Nikolay Chervoniy, Kunlin Liu, Sugasa Marangonda, Chris Umé, Mr Dpfks, Carl Shift Facenheim, Luis RP, Jian Jiang, et al · 2020
Facex-zoo: A pytorch toolbox for face recognition
Jun Wang, Yinglu Liu, Yibo Hu, Hailin Shi, and Tao Mei · 2021
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Exploring temporal coherence for more general video face forgery detection
Yinglin Zheng, Jianmin Bao, Dong Chen, Ming Zeng, and Fang Wen · 2021
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Joint audio-visual deepfake detection
Yipin Zhou and Ser-Nam Lim · 2021
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End-to-end reconstruction-classification learning for face forgery detection
Junyi Cao, Chao Ma, Taiping Yao, Shen Chen, Shouhong Ding, and Xiaokang Yang · 2022
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A survey on automated fact-checking
Zhijiang Guo, Michael Schlichtkrull, and Andreas Vlachos · 2022
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Leveraging real talking faces via self-supervision for robust forgery detection
Alexandros Haliassos, Rodrigo Mira, Stavros Petridis, and Maja Pantic · 2022
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Cited alongside, same era.
A lip sync expert is all you need for speech to lip generation in the wild
KR Prajwal, Rudrabha Mukhopadhyay, Vinay P Namboodiri, and CV Jawahar · 2020
Cited alongside, same era.
Thinking in frequency: Face forgery detection by mining frequency-aware clues
Yuyang Qian, Guojun Yin, Lu Sheng, Zixuan Chen, and Jing Shao · 2020
Cited alongside, same era.
Cnn-generated images are surprisingly easy to spot… for now
Sheng-Yu Wang, Oliver Wang, Richard Zhang, Andrew Owens, and Alexei A Efros · 2020
Cited alongside, same era.
Taming transformers for high-resolution image synthesis
Patrick Esser, Robin Rombach, and Bjorn Ommer · 2021
Cited alongside, same era.
www.github.com/MarekKowalski/FaceSwap Accessed 2021-04-24
FaceSwap · 2021
Cited alongside, same era.
Lips don’t lie: A generalisable and robust approach to face forgery detection
Alexandros Haliassos, Konstantinos Vougioukas, Stavros Petridis, and Maja Pantic · 2021
Cited alongside, same era.
OpenCLIP, July 2021
Gabriel Ilharco, Mitchell Wortsman, Ross Wightman, Cade Gordon, Nicholas Carlini, Rohan Taori, Achal Dave, Vaishaal Shankar, Hongseok Namkoong, John Miller, Hannaneh Hajishirzi, Ali Farhadi, and Ludwig Schmidt · 2021
Cited alongside, same era.
Later among the works it cites.
Hierarchical text-conditional image generation with clip latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 2022
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High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
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Photorealistic text-to-image diffusion models with deep language understanding
Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily L Denton, Kamyar Ghasemipour, Raphael Gontijo Lopes, Burcu Karagol Ayan, Tim Salimans, et al · 2022
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Learning audio-visual speech representation by masked multimodal cluster prediction
Bowen Shi, Wei-Ning Hsu, Kushal Lakhotia, and Abdelrahman Mohamed · 2022
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Dual contrastive learning for general face forgery detection
Ke Sun, Taiping Yao, Shen Chen, Shouhong Ding, Jilin Li, and Rongrong Ji · 2022
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Uia-vit: Unsupervised inconsistency-aware method based on vision transformer for face forgery detection
Wanyi Zhuang, Qi Chu, Zhentao Tan, Qiankun Liu, Haojie Yuan, Changtao Miao, Zixiang Luo, and Nenghai Yu · 2022
Later among the works it cites.
Attend-and-excite: Attention-based semantic guidance for text-to-image diffusion models
Hila Chefer, Yuval Alaluf, Yael Vinker, Lior Wolf, and Daniel Cohen-Or · 2023
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Self-supervised video forensics by audio-visual anomaly detection
Chao Feng, Ziyang Chen, and Andrew Owens · 2023
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Implicit identity driven deepfake face swapping detection
Baojin Huang, Zhongyuan Wang, Jifan Yang, Jiaxin Ai, Qin Zou, Qian Wang, and Dengpan Ye · 2023
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Junnan Li, Dongxu Li, Silvio Savarese, and Steven Hoi · 2023
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Towards universal fake image detectors that generalize across generative models
Utkarsh Ojha, Yuheng Li, and Yong Jae Lee · 2023
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Imagereward: Learning and evaluating human preferences for text-to-image generation
Jiazheng Xu, Xiao Liu, Yuchen Wu, Yuxuan Tong, Qinkai Li, Ming Ding, Jie Tang, and Yuxiao Dong · 2023
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Ucf: Uncovering common features for generalizable deepfake detection
Zhiyuan Yan, Yong Zhang, Yanbo Fan, and Baoyuan Wu · 2023
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