Papers DeepFake Detection
“DeepFake Detection” 태그가 달린 논문 828편 · 필터 해제
From Scores to Evidence: Auditable Decisions Can Improve Speech Deepfake Detection
Speech deepfakes can mimic a speaker's voice convincingly enough to deceive listeners and automated systems. This has driven strong progress in speech deepfake detection, but most detectors still end with one score per u…
DeepFake DetectionAdaptive Gated Deepfake Detection for Low-Resolution and Resource-Constrained Environments
Deepfake detection models often rely on high-quality inputs, fixed inference paths, and computationally expensive architectures, limiting their use in low-resolution and resource-constrained settings. This paper proposes…
Computational EfficiencyDeepFake DetectionDF-MoE: Generalizable Deepfake Detection via Multimodal Sparse Mixture-of-Experts
Audio-visual deepfake detection is an actively studied topic, where one of the main challenges is to develop detectors able to generalize across deepfake generation methods. We conjecture that overfitting can be mitigate…
DeepFake DetectionFace ParsingExplainable Deepfake Detection with Feature-robust Augmentation and Evidence-grounded Explanation Optimization
Explainable deepfake detection extends binary classification by requiring models to not only predict authenticity but also provide interpretable justifications. This expanded scope is critical in practice, where users li…
Binary ClassificationContrastive LearningDeepFake DetectionEnvironment-Invariant Subspace Learning for Generalizable Deepfake Detection
Cross-distribution generalization remains a critical bottleneck in deepfake detection. While recent efforts leverage the semantic priors of large-scale visual foundation models (VFMs), a noteworthy yet underexplored chal…
DeepFake DetectionSpreadMark: Robust Image Watermarking via Spread-Spectrum Embedding
Invisible image watermarks are increasingly used for deepfake detection and provenance tracking, where they must survive not only incidental distortions but also deliberate removal. We revisit spread-spectrum embedding, …
DeepFake DetectionREIMU: Efficient Heterogeneous Hierarchical Reasoning for SSL-Based Speech Deepfake Detection
The increasing realism of speech generated by text-to-speech and voice conversion systems poses growing challenges to media integrity and voice authentication. Self-supervised learning (SSL) has substantially advanced sp…
Self-Supervised LearningDeepFake DetectionVoice ConversionTeffic-Audio: Tell Fact from Fiction
Speech deepfake detection has expanded in scope with increasingly heterogeneous spoofing mechanisms, including speech synthesis, voice conversion, vocoder reconstruction, and neural-codec resynthesis. The resulting spoof…
DeepFake DetectionSpeech SynthesisVoice ConversionLaP-Forensics: Latent-Pixel Consistency Guided Multimodal Reasoning for Deepfake Detection
Recent generative models can produce images with few obvious visual artifacts, weakening detectors and explanations that rely only on surface appearance. We present LaP-Forensics, a multimodal framework that augments RGB…
Multimodal ReasoningDeepFake DetectionAdversarial Deepfake Generation and an Investigation of Purification-Based Adversarial Detection
This paper describes the participation of team "Go To Germany" in the ImageCLEF 2026 Deepfake Detection and Generation Task. For the image generation task, we employ FLUX.1-dev with PuLID for identity-preserving face syn…
DeepFake DetectionAdversarial AttackImage GenerationTime-Frequency Consistency Learning for Robust Speech Deepfake Detection
Recently, speech deepfake detection (SDD) has achieved significant progress. However, its robustness evaluation remains largely confined to controlled additive noise scenarios, lacking systematic investigation of the com…
Activity DetectionDeepFake DetectionLarge Audio Language Models for Spoofing-Aware Speaker Verification
Recent advances in text-to-speech and voice cloning make high-quality spoofing inexpensive and scalable, threatening voice authentication systems, especially automatic speaker verification (ASV). Existing defenses mainly…
Speaker VerificationDeepFake DetectionDetecting AI-Generated Video: A Vision-Language Dual-View Survey
The evolving realism of AI-generated Videos (AIGC-V) is rapidly rendering traditional artifact-centric detection insufficient, necessitating a paradigm shift from low-level inspection to high-level semantic verification.…
DeepFake DetectionEnsemble Deep Learning Approaches for AI-Altered Video Detection
The increasing accessibility of artificial intelligence has led to a rapid rise in AI-generated videos, making it more difficult to distinguish between real and manipulated content. Many existing detection methods rely o…
DeepFake DetectionXPlainVerse: A Million-Scale Benchmark for Explainable Deepfake Detection
As deepfake detection models increasingly produce natural language explanations, their reasoning often remains weakly grounded in visual artifacts, limiting reliability and user trust. Existing benchmarks mainly evaluate…
DeepFake DetectionImage EditingThe Calibrated Deepfake Trust Score (CDTS): Competence-Coupled Trust Degradation Across Deepfake Detectors
Modern deepfake detectors are rarely consumed as bare classifiers. In moderation, provenance, and verification pipelines their output probability is read as a degree of trust, so its calibration matters as much as raw ac…
DeepFake DetectionGenerative AI Literacy Training Improves Intelligence Analysts' Discrimination of Real and AI-Generated Images
Across social and online platforms, people are increasingly exposed to AI-generated images. As a consequence, the task of distinguishing AI-generated from authentic images is becoming a central challenge for information …
DeepFake DetectionPerception, Verdict, and Evolution: Hindsight-Driven Self-Refining Forensics Agent for AI-Generated Image Detection
The rapid advancement of generative models presents a significant challenge to existing deepfake detection methods, particularly given the widespread dissemination of highly realistic AI-generated images. Although Multim…
DeepFake DetectionSupervised Post-training of Speech Foundation Models for Robust Adaptation in Speech Deepfake Detection
Large speech foundation models have shown strong potential for speech deepfake detection, but direct fine-tuning is limited by a mismatch between self-supervised pre-training objectives and spoof-specific artifacts. To a…
DeepFake DetectionData AugmentationSpoof DetectionTransferable 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 Swapping