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Face Swapping

Face swapping refers to the task of swapping faces between images or in an video, while maintaining the rest of the body and environment context.

( Image credit: Swapped Face Detection using Deep Learning and Subjective Assessment )

Papers

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Showing 251–275 of 914 papers

TitleStatusHype
Deepfake in the Metaverse: Security Implications for Virtual Gaming, Meetings, and Offices—0
Beyond Deepfake Images: Detecting AI-Generated Videos—0
Deepfake Representation with Multilinear Regression—0
Deepfake Image Generation for Improved Brain Tumor Segmentation—0
Deepfake histological images for enhancing digital pathology—0
An Experimental Evaluation on Deepfake Detection using Deep Face Recognition—0
Advancing High Fidelity Identity Swapping for Forgery Detection—0
BERT Transformer model for Detecting Arabic GPT2 Auto-Generated Tweets—0
Deepfake Forensics Using Recurrent Neural Networks—0
Deepfake Face Traceability with Disentangling Reversing Network—0
BENet: A Cross-domain Robust Network for Detecting Face Forgeries via Bias Expansion and Latent-space Attention—0
An Examination of Fairness of AI Models for Deepfake Detection—0
A3:Ambiguous Aberrations Captured via Astray-Learning for Facial Forgery Semantic Sublimation—0
DeepFake Doctor: Diagnosing and Treating Audio-Video Fake Detection—0
Benchmarking Joint Face Spoofing and Forgery Detection with Visual and Physiological Cues—0
DeepFake Disrupter: The Detector of DeepFake Is My Friend—0
Benchmarking Foundation Models for Zero-Shot Biometric Tasks—0
Advancing Continual Learning for Robust Deepfake Audio Classification—0
Deepfake Detection with Optimized Hybrid Model: EAR Biometric Descriptor via Improved RCNN—0
DeepFake Detection with Inconsistent Head Poses: Reproducibility and Analysis—0
Benchmarking Deepart Detection—0
Deepfake Detection with Deep Learning: Convolutional Neural Networks versus Transformers—0
Deepfake Detection via Knowledge Injection—0
Benchmarking Audio Deepfake Detection Robustness in Real-world Communication Scenarios—0
A New Approach to Improve Learning-based Deepfake Detection in Realistic Conditions—0
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