{"total":94,"rows":[{"id":"2311.12832","title":"Toward effective protection against diffusion based mimicry through score distillation","created":"2023-10-02","cited_by_count":65,"area":"diffusion"},{"id":"2311.13127","title":"MetaCloak: Preventing Unauthorized Subject-driven Text-to-image Diffusion-based Synthesis via Meta-learning","created":"2023-11-22","cited_by_count":44,"area":"diffusion"},{"id":"2402.02333","title":"Copyright Protection in Generative AI: A Technical Perspective","created":"2024-02-04","cited_by_count":38,"area":null},{"id":"2408.03400","title":"Attacks and Defenses for Generative Diffusion Models: A Comprehensive Survey","created":"2024-08-06","cited_by_count":32,"area":"diffusion"},{"id":"2404.09401","title":"Watermark-embedded Adversarial Examples for Copyright Protection against Diffusion Models","created":"2024-04-15","cited_by_count":23,"area":"diffusion"},{"id":"2310.04687","title":"Targeted Attack Improves Protection against Unauthorized Diffusion Customization","created":"2023-10-07","cited_by_count":18,"area":"diffusion"},{"id":"2311.18815","title":"IMMA: Immunizing text-to-image Models against Malicious Adaptation","created":"2023-11-30","cited_by_count":18,"area":null},{"id":"2405.19424","title":"Diffusion Policy Attacker: Crafting Adversarial Attacks for Diffusion-based Policies","created":"2024-05-29","cited_by_count":18,"area":"diffusion"},{"id":"2407.10575","title":"A Survey of Defenses Against AI-Generated Visual Media: Detection,Disruption, and Authentication","created":"2024-07-15","cited_by_count":13,"area":null},{"id":"2408.10901","title":"A Gray-box Attack against Latent Diffusion Model-based Image Editing by Posterior Collapse","created":"2024-08-20","cited_by_count":13,"area":"diffusion"},{"id":"2408.00001","title":"Replication in Visual Diffusion Models: A Survey and Outlook","created":"2024-07-07","cited_by_count":11,"area":"diffusion"},{"id":"2503.10081","title":"AdvPaint: Protecting Images from Inpainting Manipulation via Adversarial Attention Disruption","created":"2025-03-13","cited_by_count":11,"area":"diffusion"},{"id":"2404.13320","title":"Pixel is a Barrier: Diffusion Models Are More Adversarially Robust Than We Think","created":"2024-04-20","cited_by_count":10,"area":"diffusion"},{"id":"2411.17957","title":"DiffVax: Optimization-Free Image Immunization Against Diffusion-Based Editing","created":"2024-11-27","cited_by_count":10,"area":null},{"id":"2512.07247","title":"AdLift: Lifting Adversarial Perturbations to Safeguard 3D Gaussian Splatting Assets Against Instruction-Driven Editing","created":"2025-12-08","cited_by_count":10,"area":null},{"id":"2403.19254","title":"Imperceptible Protection against Style Imitation from Diffusion Models","created":"2024-03-28","cited_by_count":9,"area":"diffusion"},{"id":"2411.16164","title":"Text-to-Image Synthesis: A Decade Survey","created":"2024-11-25","cited_by_count":9,"area":null},{"id":"2404.05783","title":"A Survey on Responsible Generative AI: What to Generate and What Not","created":"2024-04-08","cited_by_count":8,"area":null},{"id":"2412.09921","title":"FaceShield: Defending Facial Image against Deepfake Threats","created":"2024-12-13","cited_by_count":8,"area":null},{"id":"2505.18766","title":"StyleGuard: Preventing Text-to-Image-Model-based Style Mimicry Attacks by Style Perturbations","created":"2025-05-24","cited_by_count":8,"area":"diffusion"},{"id":"2506.01591","title":"Silence is Golden: Leveraging Adversarial Examples to Nullify Audio Control in LDM-based Talking-Head Generation","created":"2025-06-02","cited_by_count":8,"area":"diffusion"},{"id":"2509.23279","title":"Vid-Freeze: Protecting Images from Malicious Image-to-Video Generation via Temporal Freezing","created":"2025-09-27","cited_by_count":8,"area":null},{"id":"2406.15386","title":"U Can't Gen This? A Survey of Intellectual Property Protection Methods for Data in Generative AI","created":"2024-04-22","cited_by_count":7,"area":null},{"id":"2412.11423","title":"Nearly Zero-Cost Protection Against Mimicry by Personalized Diffusion Models","created":"2024-12-16","cited_by_count":7,"area":"diffusion"},{"id":"2503.13994","title":"TarPro: Targeted Protection against Malicious Image Editing","created":"2025-03-18","cited_by_count":7,"area":null},{"id":"2504.17894","title":"DCT-Shield: A Robust Frequency Domain Defense against Malicious Image Editing","created":"2025-04-24","cited_by_count":7,"area":"diffusion"},{"id":"2603.24570","title":"Anti-I2V: Safeguarding your photos from malicious image-to-video generation","created":"2026-03-25","cited_by_count":7,"area":"diffusion"},{"id":"2406.15305","title":"PID: Prompt-Independent Data Protection Against Latent Diffusion Models","created":"2024-06-14","cited_by_count":6,"area":"diffusion"},{"id":"2411.13144","title":"CopyrightMeter: Revisiting Copyright Protection in Text-to-image Models","created":"2024-11-20","cited_by_count":6,"area":"diffusion"},{"id":"2504.17219","title":"Enhancing Variational Autoencoders with Smooth Robust Latent Encoding","created":"2025-04-24","cited_by_count":6,"area":"diffusion"},{"id":"2311.13713","title":"A Somewhat Robust Image Watermark against Diffusion-based Editing Models","created":"2023-11-22","cited_by_count":5,"area":"diffusion"},{"id":"2312.00057","title":"VA3: Virtually Assured Amplification Attack on Probabilistic Copyright Protection for Text-to-Image Generative Models","created":"2023-11-29","cited_by_count":5,"area":null},{"id":"2401.07087","title":"Exploring Adversarial Attacks against Latent Diffusion Model from the Perspective of Adversarial Transferability","created":"2024-01-13","cited_by_count":5,"area":"diffusion"},{"id":"2503.03944","title":"GuardDoor: Safeguarding Against Malicious Diffusion Editing via Protective Backdoors","created":"2025-03-05","cited_by_count":5,"area":"diffusion"},{"id":"2503.13576","title":"A Comprehensive Survey on Visual Concept Mining in Text-to-image Diffusion Models","created":"2025-03-17","cited_by_count":5,"area":"diffusion"},{"id":"2505.15336","title":"My Face Is Mine, Not Yours: Facial Protection Against Diffusion Model Face Swapping","created":"2025-05-21","cited_by_count":5,"area":"diffusion"},{"id":"2511.00143","title":"BlurGuard: A Simple Approach for Robustifying Image Protection Against AI-Powered Editing","created":"2025-10-31","cited_by_count":5,"area":null},{"id":"2512.23953","title":"T2VAttack: Adversarial Attack on Text-to-Video Diffusion Models","created":"2025-12-30","cited_by_count":5,"area":"diffusion"},{"id":"2607.13336","title":"Delving into the Temporal Challenges of Unified Video Protection Against Image-to-Video and Fine-Tuning-based Customization","created":"2026-07-14","cited_by_count":5,"area":null},{"id":"2412.15320","title":"Multi-concept Model Immunization through Differentiable Model Merging","created":"2024-12-19","cited_by_count":4,"area":null},{"id":"2502.07225","title":"CAT: Contrastive Adversarial Training for Evaluating the Robustness of Protective Perturbations in Latent Diffusion Models","created":"2025-02-11","cited_by_count":4,"area":"diffusion"},{"id":"2505.08197","title":"Visual Watermarking in the Era of Diffusion Models: Advances and Challenges","created":"2025-05-13","cited_by_count":4,"area":"diffusion"},{"id":"2508.01845","title":"Beyond Vulnerabilities: A Survey of Adversarial Attacks as Both Threats and Defenses in Computer Vision Systems","created":"2025-08-03","cited_by_count":4,"area":null},{"id":"2509.13711","title":"StyleProtect: Safeguarding Artistic Identity in Fine-tuned Diffusion Models","created":"2025-09-17","cited_by_count":4,"area":"diffusion"},{"id":"2604.10837","title":"Immune2V: Image Immunization Against Dual-Stream Image-to-Video Generation","created":"2026-04-12","cited_by_count":4,"area":null},{"id":"2405.16596","title":"Protect-Your-IP: Scalable Source-Tracing and Attribution against Personalized Generation","created":"2024-05-26","cited_by_count":3,"area":"safety"},{"id":"2407.20141","title":"DDAP: Dual-Domain Anti-Personalization against Text-to-Image Diffusion Models","created":"2024-07-29","cited_by_count":3,"area":"diffusion"},{"id":"2505.13023","title":"Anti-Inpainting: A Proactive Defense Approach against Malicious Diffusion-based Inpainters under Unknown Conditions","created":"2025-05-19","cited_by_count":3,"area":null},{"id":"2507.03953","title":"Evaluating Adversarial Protections for Diffusion Personalization: A Comprehensive Study","created":"2025-07-05","cited_by_count":3,"area":"diffusion"},{"id":"2507.22499","title":"LoReUn: Data Itself Implicitly Provides Cues to Improve Machine Unlearning","created":"2025-07-30","cited_by_count":3,"area":"safety"},{"id":"2509.13922","title":"Towards Robust Defense against Customization via Protective Perturbation Resistant to Diffusion-based Purification","created":"2025-09-17","cited_by_count":3,"area":"diffusion"},{"id":"2512.14320","title":"Semantic Mismatch and Perceptual Degradation: A New Perspective on Image Editing Immunity","created":"2025-12-16","cited_by_count":3,"area":"diffusion"},{"id":"2512.14341","title":"Towards Transferable Defense Against Malicious Image Edits","created":"2025-12-16","cited_by_count":3,"area":"diffusion"},{"id":"2603.26154","title":"IPV-Bench: Benchmarking Image Protection Methods under Diverse Image-to-Video Generation Scenarios","created":"2026-03-27","cited_by_count":3,"area":null},{"id":"2411.17746","title":"UVCG: Leveraging Temporal Consistency for Universal Video Protection","created":"2024-11-25","cited_by_count":2,"area":null},{"id":"2412.18791","title":"Protective Perturbations against Unauthorized Data Usage in Diffusion-based Image Generation","created":"2024-12-25","cited_by_count":2,"area":"diffusion"},{"id":"2507.10578","title":"When and Where do Data Poisons Attack Textual Inversion?","created":"2025-07-11","cited_by_count":2,"area":"diffusion"},{"id":"2507.17554","title":"An h-space Based Adversarial Attack for Protection Against Few-shot Personalization","created":"2025-07-23","cited_by_count":2,"area":"diffusion"},{"id":"2508.16217","title":"PromptFlare: Prompt-Generalized Defense via Cross-Attention Decoy in Diffusion-Based Inpainting","created":"2025-08-22","cited_by_count":2,"area":"diffusion"},{"id":"2509.10359","title":"Immunizing Images from Text to Image Editing via Adversarial Cross-Attention","created":"2025-09-12","cited_by_count":2,"area":null},{"id":"2602.03878","title":"Intellectual Property Protection for 3D Gaussian Splatting Assets: A Survey","created":"2026-02-02","cited_by_count":2,"area":null},{"id":"2603.13028","title":"Purify Once, Edit Freely: Breaking Image Protections under Model Mismatch","created":"2026-03-13","cited_by_count":2,"area":"diffusion"},{"id":"2604.08405","title":"SyncBreaker:Stage-Aware Multimodal Adversarial Attacks on Audio-Driven Talking Head Generation","created":"2026-04-09","cited_by_count":2,"area":null},{"id":"2408.11408","title":"Latent Feature and Attention Dual Erasure Attack against Multi-View Diffusion Models for 3D Assets Protection","created":"2024-08-21","cited_by_count":1,"area":"diffusion"},{"id":"2410.03640","title":"Real-World Benchmarks Make Membership Inference Attacks Fail on Diffusion Models","created":"2024-10-04","cited_by_count":1,"area":"diffusion"},{"id":"2505.19425","title":"Structure Disruption: Subverting Malicious Diffusion-Based Inpainting via Self-Attention Query Perturbation","created":"2025-05-26","cited_by_count":1,"area":"diffusion"},{"id":"2506.04394","title":"Is Perturbation-Based Image Protection Disruptive to Image Editing?","created":"2025-06-04","cited_by_count":1,"area":"diffusion"},{"id":"2512.10433","title":"Targeted Data Protection for Diffusion Model by Matching Training Trajectory","created":"2025-12-11","cited_by_count":1,"area":"diffusion"},{"id":"2512.14333","title":"Dual Attention Guided Defense Against Malicious Edits","created":"2025-12-16","cited_by_count":1,"area":"diffusion"},{"id":"2512.21019","title":"Efficient and Robust Video Defense Framework against 3D-field Personalized Talking Face","created":"2025-12-24","cited_by_count":1,"area":null},{"id":"2601.14738","title":"Safeguarding Facial Identity against Diffusion-based Face Swapping via Cascading Pathway Disruption","created":"2026-01-21","cited_by_count":1,"area":"diffusion"},{"id":"2601.22744","title":"Beauty and the Beast: Imperceptible Perturbations Against Diffusion-Based Face Swapping via Directional Attribute Editing","created":"2026-01-30","cited_by_count":1,"area":null},{"id":"2604.23688","title":"Do Protective Perturbations Really Protect Portrait Privacy under Real-world Image Transformations?","created":"2026-04-26","cited_by_count":1,"area":null},{"id":"2404.16336","title":"FedStyle: Style-Based Federated Learning Crowdsourcing Framework for Art Commissions","created":"2024-04-25","cited_by_count":0,"area":null},{"id":"2409.10578","title":"GLEAN: Generative Learning for Eliminating Adversarial Noise","created":"2024-09-15","cited_by_count":0,"area":"diffusion"},{"id":"2410.05694","title":"DiffusionGuard: A Robust Defense Against Malicious Diffusion-based Image Editing","created":"2024-10-08","cited_by_count":0,"area":"diffusion"},{"id":"2504.08782","title":"Embedding Hidden Adversarial Capabilities in Pre-Trained Diffusion Models","created":"2025-04-05","cited_by_count":0,"area":"diffusion"},{"id":"2505.21742","title":"What is Adversarial Training for Diffusion Models?","created":"2025-05-27","cited_by_count":0,"area":"diffusion"},{"id":"2506.02665","title":"Beyond Invisibility: Learning Robust Visible Watermarks for Stronger Copyright Protection","created":"2025-06-03","cited_by_count":0,"area":null},{"id":"2603.14860","title":"Architecture-Agnostic Feature Synergy for Universal Defense Against Heterogeneous Generative Threats","created":"2026-03-16","cited_by_count":0,"area":null},{"id":"2605.12919","title":"GuardMarkGS: Unified Ownership Tracing and Edit Deterrence for 3D Gaussian Splatting","created":"2026-05-13","cited_by_count":0,"area":"safety"},{"id":"2606.12263","title":"VOID: Defeating Unauthorized Mimicry in Latent Diffusion Models","created":"2026-06-10","cited_by_count":0,"area":"diffusion"},{"id":"2607.03277","title":"Defending from GeoLocalization through Adversarial Road Trips","created":"2026-07-03","cited_by_count":0,"area":null},{"id":"2607.16898","title":"Cross-Branch Conflict as a Shield: Safeguarding Facial Identities in Unified Multimodal Image Editing","created":"2026-07-18","cited_by_count":0,"area":null},{"id":"2607.26976","title":"InkShield: Writing Style Protection Against Unauthorized Handwriting Mimicry","created":"2026-07-29","cited_by_count":0,"area":null},{"id":"2608.03395","title":"SRAP: SVD-Refined Adversarial Perturbations for Imperceptible Face-Swap Defense","created":"2026-08-04","cited_by_count":0,"area":null},{"id":"2608.24068","title":"Representation Learning in Diffusion and Flow-based Model: An Application Aspect","created":"2026-08-25","cited_by_count":0,"area":"diffusion"},{"id":"2608.30951","title":"Audio-Driven Adversarial Defense for 3D Talking Face Generation with totally Visual Fidelity Preservation","created":"2026-08-31","cited_by_count":0,"area":null},{"id":"2609.05503","title":"A Survey on Adversarial Attacks and Defenses for Diffusion Models Across Multiple Modalities","created":"2026-08-28","cited_by_count":0,"area":"diffusion"},{"id":"2609.34232","title":"Trustworthy synthetic visual media: Evidence across the media lifecycle","created":"2026-09-28","cited_by_count":0,"area":null},{"id":"2610.01944","title":"Anti-Persona: Disrupting Unauthorized Identity Binding and Recognition in Personalized Vision--Language Models","created":"2026-10-01","cited_by_count":0,"area":null},{"id":"2610.06334","title":"SPIN: Image Immunization Against Diffusion Editing via Single-Step Projection in Stochastic Neighborhoods","created":"2026-10-05","cited_by_count":0,"area":"diffusion"},{"id":"2610.07464","title":"Protective Perturbations Must Survive the Resize: Scale-Robust Image Immunization against Malicious Editing","created":"2026-10-05","cited_by_count":0,"area":"diffusion"},{"id":"2610.16835","title":"Beyond User-Side Defenses: Image Protection in Open-Weight Diffusion Models","created":"2026-10-12","cited_by_count":0,"area":"diffusion"}],"next_cursor":null}