Fetching the paper…
Reading the bibliography…
Deepfake detection remains a challenging task due to the difficulty of generalizing to new types of forgeries.
Visualizing data using t-sne
Laurens Van der Maaten and Geoffrey Hinton · 2008
Earlier work this paper cites.
Representation learning: A review and new perspectives
Yoshua Bengio, Aaron Courville, and Pascal Vincent · 2013
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
Earlier work this paper cites.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper cites.
300 faces in-the-wild challenge: Database and results
Christos Sagonas, Epameinondas Antonakos, Georgios Tzimiropoulos, Stefanos Zafeiriou, and Maja Pantic · 2016
Earlier work this paper cites.
Face2face: Real-time face capture and reenactment of rgb videos
Justus Thies, Michael Zollhofer, Marc Stamminger, Christian Theobalt, and Matthias Nießner · 2016
Earlier work this paper cites.
Arbitrary style transfer in real-time with adaptive instance normalization
Xun Huang and Serge Belongie · 2017
Earlier work this paper cites.
Two-stream neural networks for tampered face detection
Peng Zhou, Xintong Han, Vlad I. Morariu, and Larry S. Davis · 2017
Earlier work this paper cites.
Mesonet: a compact facial video forgery detection network
Darius Afchar, Vincent Nozick, Junichi Yamagishi, and Isao Echizen · 2018
Earlier work this paper cites.
Multimodal unsupervised image-to-image translation
Xun Huang, Ming-Yu Liu, Serge Belongie, and Jan Kautz · 2018
Earlier work this paper cites.
Exposing deepfake videos by detecting face warping artifacts
Yuezun Li and Siwei Lyu · 2018
Earlier work this paper cites.
Deepfake video detection through optical flow based cnn
Irene Amerini, Leonardo Galteri, Roberto Caldelli, and Alberto Del Bimbo · 2019
Earlier work this paper cites.
Exploiting visual artifacts to expose deepfakes and face manipulations
Falko Matern, Christian Riess, and Marc Stamminger · 2019
Earlier work this paper cites.
Multi-task learning for detecting and segmenting manipulated facial images and videos
Huy H Nguyen, Fuming Fang, Junichi Yamagishi, and Isao Echizen · 2019
Earlier work this paper cites.
Capsule-forensics: Using capsule networks to detect forged images and videos
Huy H. Nguyen, Junichi Yamagishi, and Isao Echizen · 2019
Earlier work this paper cites.
Faceforensics++: Learning to detect manipulated facial images
Andreas Rossler, Davide Cozzolino, Luisa Verdoliva, Christian Riess, Justus Thies, and Matthias Nießner · 2019
Earlier work this paper cites.
Recurrent convolutional strategies for face manipulation detection in videos
Ekraam Sabir, Jiaxin Cheng, Ayush Jaiswal, Wael AbdAlmageed, Iacopo Masi, and Prem Natarajan · 2019
Earlier work this paper cites.
Efficientnet: Rethinking model scaling for convolutional neural networks
Mingxing Tan and Quoc Le · 2019
Earlier work this paper cites.
Deferred neural rendering: Image synthesis using neural textures
Justus Thies, Michael Zollhöfer, and Matthias Nießner · 2019
Earlier work this paper cites.
Fakespotter: A simple yet robust baseline for spotting ai-synthesized fake faces
Run Wang, Felix Juefei-Xu, Lei Ma, Xiaofei Xie, Yihao Huang, Jian Wang, and Yang Liu · 2019
Earlier work this paper cites.
Exposing deep fakes using inconsistent head poses
Xin Yang, Yuezun Li, and Siwei Lyu · 2019
Cited alongside, same era.
https://github.com/iperov/DeepFaceLab
Deepfakes · 2020
Cited alongside, same era.
https://github.com/MarekKowalski/FaceSwap
Faceswap · 2020
Cited alongside, same era.
On the detection of digital face manipulation
Hao Dang, Feng Liu, Joel Stehouwer, Xiaoming Liu, and Anil K Jain · 2020
Cited alongside, same era.
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.
Face x-ray for more general face forgery detection
Lingzhi Li, Jianmin Bao, Ting Zhang, Hao Yang, Dong Chen, Fang Wen, and Baining Guo · 2020
Cited alongside, same era.
Improving the efficiency and robustness of deepfakes detection through precise geometric features
Zekun Sun, Yujie Han, Zeyu Hua, Na Ruan, and Weijia Jia · 2021
Later among the works it cites.
Representative forgery mining for fake face detection
Chengrui Wang and Weihong Deng · 2021
Later among the works it cites.
Learning to disentangle gan fingerprint for fake image attribution
Tianyun Yang, Juan Cao, Qiang Sheng, Lei Li, Jiaqi Ji, Xirong Li, and Sheng Tang · 2021
Later among the works it cites.
Multi-attentional deepfake detection
Hanqing Zhao, Wenbo Zhou, Dongdong Chen, Tianyi Wei, Weiming Zhang, and Nenghai Yu · 2021
Later among the works it cites.
Learning self-consistency for deepfake detection
Tianchen Zhao, Xiang Xu, Mingze Xu, Hui Ding, Yuanjun Xiong, and Wei Xia · 2021
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Sharp multiple instance learning for deepfake video detection
Xiaodan Li, Yining Lang, Yuefeng Chen, Xiaofeng Mao, Yuan He, Shuhui Wang, Hui Xue, and Quan Lu · 2020
Cited alongside, same era.
Celeb-df: A new dataset for deepfake forensics
Yuezun Li, Xin Yang, Pu Sun, Honggang Qi, and Siwei Lyu · 2020
Cited alongside, same era.
Two-branch recurrent network for isolating deepfakes in videos
Iacopo Masi, Aditya Killekar, Royston Marian Mascarenhas, Shenoy Pratik Gurudatt, and Wael AbdAlmageed · 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.
Face anti-spoofing via disentangled representation learning
Ke-Yue Zhang, Taiping Yao, Jian Zhang, Ying Tai, Shouhong Ding, Jilin Li, Feiyue Huang, Haichuan Song, and Lizhuang Ma · 2020
Cited alongside, same era.
Local relation learning for face forgery detection
Shen Chen, Taiping Yao, Yang Chen, Shouhong Ding, Jilin Li, and Rongrong Ji · 2021
Cited alongside, same era.
Yinglin Zheng, Jianmin Bao, Dong Chen, Ming Zeng, and Fang Wen · 2021
Later among the works it cites.
Face forgery detection by 3d decomposition
Xiangyu Zhu, Hao Wang, Hongyan Fei, Zhen Lei, and Stan Z Li · 2021
Later among the works it cites.
End-to-end reconstruction-classification learning for face forgery detection
Junyi Cao, Chao Ma, Taiping Yao, Shen Chen, Shouhong Ding, and Xiaokang Yang · 2022
Later among the works it cites.
Self-supervised learning of adversarial example: Towards good generalizations for deepfake detection
Liang Chen, Yong Zhang, Yibing Song, Lingqiao Liu, and Jue Wang · 2022
Later among the works it cites.
Ost: Improving generalization of deepfake detection via one-shot test-time training
Liang Chen, Yong Zhang, Yibing Song, Jue Wang, and Lingqiao Liu · 2022
Later among the works it cites.
Exploiting fine-grained face forgery clues via progressive enhancement learning
Qiqi Gu, Shen Chen, Taiping Yao, Yang Chen, Shouhong Ding, and Ran Yi · 2022
Later among the works it cites.
Exploring disentangled content information for face forgery detection
Jiahao Liang, Huafeng Shi, and Weihong Deng · 2022
Later among the works it cites.
A convnet for the 2020s
Zhuang Liu, Hanzi Mao, Chao-Yuan Wu, Christoph Feichtenhofer, Trevor Darrell, and Saining Xie · 2022
Later among the works it cites.
Core: Consistent representation learning for face forgery detection
Yunsheng Ni, Depu Meng, Changqian Yu, Chengbin Quan, Dongchun Ren, and Youjian Zhao · 2022
Later among the works it cites.
Detecting deepfakes with self-blended images
Kaede Shiohara and Toshihiko Yamasaki · 2022
Later among the works it cites.
M2tr: Multi-modal multi-scale transformers for deepfake detection
Junke Wang, Zuxuan Wu, Wenhao Ouyang, Xintong Han, Jingjing Chen, Yu-Gang Jiang, and Ser-Nam Li · 2022
Later among the works it cites.
Improving generalization by commonality learning in face forgery detection
Peipeng Yu, Jianwei Fei, Zhihua Xia, Zhili Zhou, and Jian Weng · 2022
Later among the works it cites.
Towards intrinsic common discriminative features learning for face forgery detection using adversarial learning
Wanyi Zhuang, Qi Chu, Haojie Yuan, Changtao Miao, Bin Liu, and Nenghai Yu · 2022
Later among the works it cites.
Implicit identity leakage: The stumbling block to improving deepfake detection generalization
Shichao Dong, Jin Wang, Renhe Ji, Jiajun Liang, Haoqiang Fan, and Zheng Ge · 2023
Closest in time.
Dynamic graph learning with content-guided spatial-frequency relation reasoning for deepfake detection
Yuan Wang, Kun Yu, Chen Chen, Xiyuan Hu, and Silong Peng · 2023
Closest in time.