Program - AI4MFDD2026
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8:50 – 9:00 |
Welcome |
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9:00 – 10:00 |
Keynote Speaker: Prof. Sebastiano Battiato |
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10:00 – 10:15 |
Break |
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10:15 – 11:00 |
Session 1 (Oral) Training-Free Reconstruction-Based AI-Generated Image Detectors Are Inherently Vulnerable to Adversarial Examples Fast, Secure, and High-Capacity Image Watermarking with Autoencoded Text Vectors Non-Intrusive and Scalable Watermarking for Latent Diffusion Models via a Shared LoRA Adapter |
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11:00 – 11:15 |
Break |
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11:15 – 12:00 |
Session 2 (Oral) LSViT: Locality-Sensitive Vision Transformer Adaptation for Generalizable Deepfake Detection Unifying Semantic Priors and High-Frequency Traces: Enhancing V-JEPA with Mixture-of-Experts for Robust Synthetic Image Forensics Dissecting Agentic Forensics: The Role of Triage, Prompting, and Evidence Arbitration in Open-World Fake Image Detection |
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12:00 – 13:30 |
Lunch Break |
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13:30 – 14:30 |
Keynote Speaker: Prof. Roberto Caldelli |
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14:30 –14:45 |
Break |
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14:45 – 15:45 |
Session 3 (IAPR-TC6 Best Paper Award) DINO-FIL: Multi-Layer Transformer Fusion for Generative Inpainting Forgery Localization DF-CBM: Region-Aware Concept Bottleneck Models for Deepfake Detection Understanding Why Foundation Models Work for Diffusion-Generated Image Detection Latent Optimization Dynamics for Latent Diffusion Model Attribution |
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15:45 – 16:00 |
Break |
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16:00 – 16:15 |
IAPR-TC6 Best Paper Award Announcement |
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16:15 – 18:30 |
Session 4 (Posters) LAION-Mobile: Evaluating Deepfake Detectors On One Million Smartphone Photos Media Intelligence Platform: Multimodal Detection of Synthetic and Manipulated Content Periocular Soft Biometrics: A Survey and Applications to Multimedia Forensics and Disinformation Detection A Cross-View Consistent Multi-Branch Framework for Synthetic Image Source Attribution AIGen4Det: Leveraging AI-Regeneration for Generalizable Synthetic Facial Image Detection Don’t Guess, Escalate: Towards Explainable Uncertainty-Calibrated AI Forensic Agent Leveraging Speech-to-Facial-Electromyography Mapping for Singing Voice Deepfake Source Tracing: A Pilot Experiment |