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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 751–800 of 914 papers

TitleStatusHype
Physics guided deep learning generative models for crystal materials discovery—0
Practical Deepfake Detection: Vulnerabilities in Global Contexts—0
Practical Digital Disguises: Leveraging Face Swaps to Protect Patient Privacy—0
Preliminary Forensics Analysis of DeepFake Images—0
Principles of Designing Robust Remote Face Anti-Spoofing Systems—0
Protecting Against Image Translation Deepfakes by Leaking Universal Perturbations from Black-Box Neural Networks—0
ProtoExplorer: Interpretable Forensic Analysis of Deepfake Videos using Prototype Exploration and Refinement—0
Psychophysical Evaluation of Human Performance in Detecting Digital Face Image Manipulations—0
PUDD: Towards Robust Multi-modal Prototype-based Deepfake Detection—0
Quality-Agnostic Deepfake Detection with Intra-model Collaborative Learning—0
Quantitative Metrics for Evaluating Explanations of Video DeepFake Detectors—0
Quantum-Trained Convolutional Neural Network for Deepfake Audio Detection—0
Rank-based No-reference Quality Assessment for Face Swapping—0
Real-centric Consistency Learning for Deepfake Detection—0
REALEDIT: Reddit Edits As a Large-scale Empirical Dataset for Image Transformations—0
0-1 laws for pattern occurrences in phylogenetic trees and networks—0
Real, fake and synthetic faces - does the coin have three sides?—0
RealSeal: Revolutionizing Media Authentication with Real-Time Realism Scoring—0
Real-Time Deepfake Detection in the Real-World—0
Real-time Detection of AI-Generated Speech for DeepFake Voice Conversion—0
Real-time face swapping as a tool for understanding infant self-recognition—0
Recap: Detecting Deepfake Video with Unpredictable Tampered Traces via Recovering Faces and Mapping Recovered Faces—0
Recent Advancements In The Field Of Deepfake Detection—0
Reduced Spatial Dependency for More General Video-level Deepfake Detection—0
Region-Aware Face Swapping—0
Reinforced Disentanglement for Face Swapping without Skip Connection—0
Reject Threshold Adaptation for Open-Set Model Attribution of Deepfake Audio—0
Replay Attacks Against Audio Deepfake Detection—0
Representation Loss Minimization with Randomized Selection Strategy for Efficient Environmental Fake Audio Detection—0
Restricted Black-box Adversarial Attack Against DeepFake Face Swapping—0
Retrieval-Augmented Audio Deepfake Detection—0
Robust Deepfake On Unrestricted Media: Generation And Detection—0
Robust Identity Perceptual Watermark Against Deepfake Face Swapping—0
RobustSwap: A Simple yet Robust Face Swapping Model against Attribute Leakage—0
Room Impulse Responses help attackers to evade Deep Fake Detection—0
RSGAN: Face Swapping and Editing using Face and Hair Representation in Latent Spaces—0
Scapegoat Generation for Privacy Protection from Deepfake—0
Searching for the Fakes: Efficient Neural Architecture Search for General Face Forgery Detection—0
Securing Social Media Against Deepfakes using Identity, Behavioral, and Geometric Signatures—0
Seeing is Living? Rethinking the Security of Facial Liveness Verification in the Deepfake Era—0
Selective Domain-Invariant Feature for Generalizable Deepfake Detection—0
SELFI: Selective Fusion of Identity for Generalizable Deepfake Detection—0
Self-supervised Auxiliary Learning for Texture and Model-based Hybrid Robust and Fair Featuring in Face Analysis—0
Self-Supervised Graph Transformer for Deepfake Detection—0
Self-supervised Transformer for Deepfake Detection—0
SelfSwapper: Self-Supervised Face Swapping via Shape Agnostic Masked AutoEncoder—0
Shaking the Fake: Detecting Deepfake Videos in Real Time via Active Probes—0
ShapeEditer: a StyleGAN Encoder for Face Swapping—0
Sharp Multiple Instance Learning for DeepFake Video Detection—0
SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks—0
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