Papers Face Swapping
“Face Swapping” 태그가 달린 논문 947편 · 필터 해제
Multi-Agent Forensic Reasoning for Generalizable Deepfake Video Detection
The malicious use of generative artificial intelligence to create highly realistic deepfake videos raises serious ethical concerns and poses substantial challenges to AI safety. However, existing deepfake video benchmark…
Face SwappingAdaptive Identity Anchoring: Closed-Loop Keyframe Placement for Synthetic Paired Supervision in Video Face Swapping
Video face swapping has no natural paired supervision: no real footage exists of one person's face performing another person's video. The strongest current answer, DreamID-V's SyncID-Pipe, mints pairs by replacing the id…
Face SwappingSwapping Faces, Saving Features: A Dual-Purpose Pipeline for Pedestrian Privacy in ITS
Large-scale and diverse datasets are needed to train AI models to take real-time decisions for autonomous vehicles (AVs), an intelligent transportation system (ITS) application. Pedestrian intention and trajectory predic…
Trajectory PredictionAutonomous VehiclesFace SwappingTransferable Attack against Face Swapping in an Extended Space
Although deep Face Swapping (FS) models may benefit the entertainment industry, they pose severe threats to privacy and security. Existing protections, including deepfake detection and adversarial perturbation, are eithe…
DeepFake DetectionFace SwappingTowards High Fidelity Face Swapping: A Comprehensive Survey and New Benchmark
Face swapping has witnessed significant progress in recent years, largely driven by advances in deep generative models such as GANs and diffusion models.Despite these advances, existing methods remain fragmented across d…
Face SwappingCA-IDD: Cross-Attention Guided Identity-Conditional Diffusion for Identity-Consistent Face Swapping
Face swapping aims to optimize realistic facial image generation by leveraging the identity of a source face onto a target face while preserving pose, expression, and context. However, existing methods, especially GAN-ba…
Image GenerationFace SwappingID-Eraser: Proactive Defense Against Face Swapping via Identity Perturbation
Deepfake technologies have rapidly advanced with modern generative AI, and face swapping in particular poses serious threats to privacy and digital security. Existing proactive defenses mostly rely on pixel-level perturb…
Face RecognitionFace SwappingActivityForensics: A Comprehensive Benchmark for Localizing Manipulated Activity in Videos
Temporal forgery localization aims to temporally identify manipulated segments in videos. Most existing benchmarks focus on appearance-level forgeries, such as face swapping and object removal. However, recent advances i…
Video GenerationFace SwappingTowards Source-Aware Object Swapping with Initial Noise Perturbation
Object swapping aims to replace a source object in a scene with a reference object while preserving object fidelity, scene fidelity, and object-scene harmony. Existing methods either require per-object finetuning and slo…
Face SwappingRealHD: A High-Quality Dataset for Robust Detection of State-of-the-Art AI-Generated Images
The rapid advancement of generative AI has raised concerns about the authenticity of digital images, as highly realistic fake images can now be generated at low cost, potentially increasing societal risks. In response, s…
Text-to-Image GenerationImage InpaintingFace SwappingVFace: A Training-Free Approach for Diffusion-Based Video Face Swapping
We present a training-free, plug-and-play method, namely VFace, for high-quality face swapping in videos. It can be seamlessly integrated with image-based face swapping approaches built on diffusion models. First, we int…
Face SwappingBeauty and the Beast: Imperceptible Perturbations Against Diffusion-Based Face Swapping via Directional Attribute Editing
Diffusion-based face swapping achieves state-of-the-art performance, yet it also exacerbates the potential harm of malicious face swapping to violate portraiture right or undermine personal reputation. This has spurred t…
Face SwappingSafeguarding Facial Identity against Diffusion-based Face Swapping via Cascading Pathway Disruption
The rapid evolution of diffusion models has democratized face swapping but also raises concerns about privacy and identity security. Existing proactive defenses, often adapted from image editing attacks, prove ineffectiv…
Face SwappingImage EditingAPPLE: Attribute-Preserving Pseudo-Labeling for Diffusion-Based Face Swapping
Face swapping aims to transfer the identity of a source face onto a target face while preserving target-specific attributes such as pose, expression, lighting, skin tone, and makeup. However, since real ground truth for …
Face SwappingTwoHead-SwinFPN: A Unified DL Architecture for Synthetic Manipulation, Detection and Localization in Identity Documents
The proliferation of sophisticated generative AI models has significantly escalated the threat of synthetic manipulations in identity documents, particularly through face swapping and text inpainting attacks. This paper …
Computational EfficiencyBinary ClassificationMulti-Task LearningFace SwappingGaussianSwap: Animatable Video Face Swapping with 3D Gaussian Splatting
We introduce GaussianSwap, a novel video face swapping framework that constructs a 3D Gaussian Splatting based face avatar from a target video while transferring identity from a source image to the avatar. Conventional v…
Face RecognitionVideo GenerationFace SwappingDreamID-V:Bridging the Image-to-Video Gap for High-Fidelity Face Swapping via Diffusion Transformer
Video Face Swapping (VFS) requires seamlessly injecting a source identity into a target video while meticulously preserving the original pose, expression, lighting, background, and dynamic information. Existing methods s…
Reinforcement LearningFace SwappingBLANKET: Anonymizing Faces in Infant Video Recordings
Ensuring the ethical use of video data involving human subjects, particularly infants, requires robust anonymization methods. We propose BLANKET (Baby-face Landmark-preserving ANonymization with Keypoint dEtection consis…
Keypoint DetectionPose EstimationFace SwappingTowards Robust Protective Perturbation against DeepFake Face Swapping
DeepFake face swapping enables highly realistic identity forgeries, posing serious privacy and security risks. A common defence embeds invisible perturbations into images, but these are fragile and often destroyed by bas…
Reinforcement LearningFace SwappingPreserving Source Video Realism: High-Fidelity Face Swapping for Cinematic Quality
Video face swapping is crucial in film and entertainment production, where achieving high fidelity and temporal consistency over long and complex video sequences remains a significant challenge. Inspired by recent advanc…
Face SwappingImage Editing