LIU Yalin, LU Tianliang. Deepfake Video Detection Method Improved by GRU and Involution[J]. Computer Engineering and Applications, 2023, 59(22): 276-283.
[1] STUPP C.Fraudsters used AI to mimic CEO’s voice in unusual cybercrime case[J].The Wall Street Journal,2019,30(8).
[2] SUWAJANAKORN S,SEITZ S I,KEMELMACHER-SHLIZERMAN I.Synthesizing Obama:learning lip sync from,audio[J].ACM Transactions on Graphics,2017,36(4):95.
[3] KOOPMAN M,RODRIGUEZ A M,GERADTS Z.Detection of deepfake video manipulation[C]//Proceedings of the 20th Irish Machine Vision and Image Processing Conference,2018:133-136.
[4] 李纪成,刘琲贝,胡永健,等.基于光照方向一致性的换脸视频检测[J].南京航空航天大学学报,2020,52(5):760-767.
LI J C,LIU B B,HU Y J,et al.Deepfake video detection based on consistency of illumination direction[J].Journal of Nanjing University of Aeronautics & Astronautics,2020,52(5):760-767.
[5] YANG J,XIAO S,LI A,et al.Detecting fake images by identifying potential texture difference[J].Future Generation Computer Systems,2021,125(7553):127-135.
[6] DEMIR I,CIFTCI U A.Where do deep fakes look? Synthetic face detection via gaze tracking[C]//Proceedings of the 2021 ACM Symposium on Eye Tracking Research and Applications,2021:1-11.
[7] LI X,LANG Y,CHEN Y,et al.Sharp multiple instance learning for deepfake video detection[C]//Proceedings of the 28th ACM International Conference on Multimedia,2020:1864-1872.
[8] NGUYEN H,YAMAGISHI J,ECHIZEN I.Use of a capsule network to detect fake images and videos[J].arXiv:1910.12467,2019.
[9] HARA K,KATAOK H,SATOH Y.Learning spatio-temporal features with 3D residual networks for action recognition[C]//Proceedings of the 2017 IEEE International Conference on Computer Vision Workshops,Venice,2017:3154-3160.
[10] CARREIRA J,ZISSERMAN A.Quo vadis,action recognition? A new model and the kinetics dataset[C]//Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition,Honolulu,2017:4724-4733.
[11] WANG Y,DANTCHEVA A.A video is worth more than 1000 lies.Comparing 3DCNN approaches for detecting deepfakes[C]//Proceedings of the 2020 15th IEEE International Conference on Automatic Face and Gesture Recognition,2020.
[12] SEBYAKIN A,SOLOVIEV V,ZOLOTARYUK A.Spatio-temporal deepfake detection with deep neural networks[C]//Proceedings of the 16th International Conference on Diversity,Divergence,Dialogue.Cham:Springer,2021:78-94.
[13] GANIYUSUFOGLU I,NG? L M,SAVOV N,et al.Spatio-temporal features for generalized detection of deepfake videos[J].arXiv:2010.11844,2020.
[14] XUAN H N,TRAN T S,LE V T,et al.Learning spatio-temporal features to detect manipulated facial videos created by the deepfake techniques[J].Forensic Science International Digital Investigation,2021,36(4):301108.
[15] CALDELLI R,GALTERI L,AMERINI I,et al.Optical flow based CNN for detection of unlearnt deepfake manipulations[J].Pattern Recognition Letters,2021,146:31-37.
[16] HU J,LIAO X,WANG W,et al.Detecting compressed deepfake videos in social networks using frame-temporality two-stream convolutional network[J].IEEE Transactions on Circuits and Systems for Video Technology,2022,32(3):1089-1102.
[17] BCA B,Tl A,WD C.Detecting deepfake videos based on spatiotemporal attention and convolutional LSTM[J].Information Sciences,2022,601:58-70.
[18] SABIR E,CHENG J,JAISWAL A,et al.Recurrent convo-lutional strategies for face manipulation detection in videos[J].arXiv:1905.00582,2019.
[19] GUERA D,DELP E J.Deepfake video detection using recurrent neural networks[C]//Proceedings of the 2018 15th IEEE International Conference on Advanced Video and Signal Based Surveillance,2018.
[20] XIAO Y,YIN H,ZHANG Y,et al.A dual-stage attention-based Conv-LSTM network for spatio-temporal correlation and multivariate time series prediction[J].International Journal of Intelligent Systems,2021,36(5):2036-2057.
[21] MASI I,KILLEKAR A,MASCARENHAS R M,et al.Two-branch recurrent network for isolating deepfakes in videos[C]//Proceedings of the 16th European Conference on Computer Vision.Cham:Springer,2020:667-684.
[22] WU X,XIE Z,GAO Y T,et al.SSTNet:detecting manipulated faces through spatial,steganalysis and temporal features[C]//Proceedings of the 2020 IEEE International Conference on Acoustics,Speech and Signal Processing,2020:2952-2956.
[23] WANG Z,LI X,NI R,et al.Attention guided spatio-temporal artifacts extraction for deepfake detection[C]//Proceedings of the 4th Chinese Conference on Pattern Recognition and Computer Vision.Cham:Springer,2021:374-386.
[24] SU Y,XIA H,LIANG Q,et al.Exposing deepfake videos using attention based convolutional LSTM network[J].Neural Processing Letters,2021,53(6):4159-4175.
[25] CHEN B,LI T,DING W.Detecting deepfake videos based on spatiotemporal attention and convolutional LSTM[J].Information Sciences,2022,601:58-70.
[26] KIMY,KOH Y J,LEE C,et al.Dark image enhancement based on pairwise target contrast and multiscale detail boosting[C]//Proceedings of the 2015 IEEE International Conference on Image Processing,2015:1404-1408.
[27] SIMONYAN K,ZISSERMAN A.Very deep convolutional networks for large-scale image recognition[J].arXiv:1409.
1556,2014.
[28] HINTON G E,KRIZHEVSKY A,WANG S D.Transforming auto-encoders[C]//Proceedings of the 21st International Conference on Artificial Neural Networks.Berlin,Heidelberg:Springer,2011:44-51.
[29] CHUNG J,GULCEHRE C,CHO K H,et al.Empirical evaluation of gated recurrent neural networks on sequence modeling[J].arXiv:1412.3555,2014.
[30] LI D,HU J,WANG C,et al.Involution:inverting the inherence of convolution for visual recognition[J].Computer Vision and Pattern Recognition,2021,26(1):1-12.
[31] LIN T Y,GOYAL P,GIRSHICK R,et al.Focal loss for dense object detection[C]//Proceedings of the 2017 IEEE International Conference on Computer Vision,Venice,2017:2999-3007.
[32] ROSSLER A,COZZOLINO D,VERDOLIVA L,et al.FaceForensics++:learning to detect manipulated facial images[C]//Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision,2019:1-11.
[33] LI Y,YANG X,SUN P,et al.Celeb-DF:a large-scale chal-lenging dataset for deepfake forensics[C]//Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition,2020:3207-3216.