Copertina

How to Trace Latent Generative Model Generated Images without Artificial Watermark?

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Wang, Zhenting, Sehwag, Vikash, Chen, Chen, Lyu, Lingjuan, Metaxas, Dimitris N., Ma, Shiqing
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Computer Vision and Pattern Recognition Artificial Intelligence Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Finding needles in a haystack: A Black-Box Approach to Invisible Watermark Detection
di: Pan, Minzhou, et al.
Pubblicazione: (2024)

Evaluating and Mitigating IP Infringement in Visual Generative AI
di: Wang, Zhenting, et al.
Pubblicazione: (2024)

DIAGNOSIS: Detecting Unauthorized Data Usages in Text-to-image Diffusion Models
di: Wang, Zhenting, et al.
Pubblicazione: (2023)

LED: LLM Enhanced Open-Vocabulary Object Detection without Human Curated Data Generation
di: Zhou, Yang, et al.
Pubblicazione: (2025)

CO-SPY: Combining Semantic and Pixel Features to Detect Synthetic Images by AI
di: Cheng, Siyuan, et al.
Pubblicazione: (2025)

Stretching Each Dollar: Diffusion Training from Scratch on a Micro-Budget
di: Sehwag, Vikash, et al.
Pubblicazione: (2024)

Test-Time Spectrum-Aware Latent Steering for Zero-Shot Generalization in Vision-Language Models
di: Dafnis, Konstantinos M., et al.
Pubblicazione: (2025)

PrefGen: Multimodal Preference Learning for Preference-Conditioned Image Generation
di: Mo, Wenyi, et al.
Pubblicazione: (2025)

Is Synthetic Image Useful for Transfer Learning? An Investigation into Data Generation, Volume, and Utilization
di: Li, Yuhang, et al.
Pubblicazione: (2024)

SINE: SINgle Image Editing with Text-to-Image Diffusion Models
di: Zhang, Zhixing, et al.
Pubblicazione: (2022)

DiMSUM: Diffusion Mamba -- A Scalable and Unified Spatial-Frequency Method for Image Generation
di: Phung, Hao, et al.
Pubblicazione: (2024)

Learning to Watermark in the Latent Space of Generative Models
di: Rebuffi, Sylvestre-Alvise, et al.
Pubblicazione: (2026)

A Simple Background Augmentation Method for Object Detection with Diffusion Model
di: Li, Yuhang, et al.
Pubblicazione: (2024)

The Hidden Life of Tokens: Reducing Hallucination of Large Vision-Language Models via Visual Information Steering
di: Li, Zhuowei, et al.
Pubblicazione: (2025)

RAC: Rectified Flow Auto Coder
di: Fang, Sen, et al.
Pubblicazione: (2026)

CopyJudge: Automated Copyright Infringement Identification and Mitigation in Text-to-Image Diffusion Models
di: Liu, Shunchang, et al.
Pubblicazione: (2025)

BitMark: Watermarking Bitwise Autoregressive Image Generative Models
di: Kerner, Louis, et al.
Pubblicazione: (2025)

Luminark: Training-free, Probabilistically-Certified Watermarking for General Vision Generative Models
di: Xu, Jiayi, et al.
Pubblicazione: (2026)

Trigger without Trace: Towards Stealthy Backdoor Attack on Text-to-Image Diffusion Models
di: Zhang, Jie, et al.
Pubblicazione: (2025)

RadAlign: Advancing Radiology Report Generation with Vision-Language Concept Alignment
di: Gu, Difei, et al.
Pubblicazione: (2025)

DiffusionAgent: Navigating Expert Models for Agentic Image Generation
di: Qin, Jie, et al.
Pubblicazione: (2024)

K-Prism: A Knowledge-Guided and Prompt Integrated Universal Medical Image Segmentation Model
di: Guo, Bangwei, et al.
Pubblicazione: (2025)

MLLM-as-a-Judge for Image Safety without Human Labeling
di: Wang, Zhenting, et al.
Pubblicazione: (2024)

Understanding Semantic Perturbations on In-Processing Generative Image Watermarks
di: Nakra, Anirudh, et al.
Pubblicazione: (2026)

Beyond Interpretability: When, Why, and How Sparse Autoencoders Enable Label-Free Visual Steering
di: Chatzoudis, Gerasimos, et al.
Pubblicazione: (2025)

Learning Patient-Specific Disease Dynamics with Latent Flow Matching for Longitudinal Imaging Generation
di: Chen, Hao, et al.
Pubblicazione: (2025)

TLCM: Training-efficient Latent Consistency Model for Image Generation with 2-8 Steps
di: Xie, Qingsong, et al.
Pubblicazione: (2024)

Anatomy-VLM: A Fine-grained Vision-Language Model for Medical Interpretation
di: Gu, Difei, et al.
Pubblicazione: (2025)

On the Robustness of Watermarking for Autoregressive Image Generation
di: Müller, Andreas, et al.
Pubblicazione: (2026)

Latent Action Control for Reasoning-Guided Unified Image Generation
di: Zhai, Fuxiang, et al.
Pubblicazione: (2026)

Warfare:Breaking the Watermark Protection of AI-Generated Content
di: Li, Guanlin, et al.
Pubblicazione: (2023)

Empirical Recipes for Efficient and Compact Vision-Language Models
di: Huang, Jiabo, et al.
Pubblicazione: (2026)

SignVerse-2M: A Two-Million-Clip Pose-Native Universe of 55+ Sign Languages
di: Fang, Sen, et al.
Pubblicazione: (2026)

Training-Free Watermarking for Autoregressive Image Generation
di: Tong, Yu, et al.
Pubblicazione: (2025)

SWA-LDM: Toward Stealthy Watermarks for Latent Diffusion Models
di: Yang, Zhonghao, et al.
Pubblicazione: (2025)

FEDEXCHANGE: Bridging the Domain Gap in Federated Object Detection for Free
di: Yuan, Haolin, et al.
Pubblicazione: (2025)

Robust Latent Matters: Boosting Image Generation with Sampling Error Synthesis
di: Qiu, Kai, et al.
Pubblicazione: (2025)

Watermarking Autoregressive Image Generation
di: Jovanović, Nikola, et al.
Pubblicazione: (2025)

CPO: Condition Preference Optimization for Controllable Image Generation
di: Lyu, Zonglin, et al.
Pubblicazione: (2025)

FissionVAE: Federated Non-IID Image Generation with Latent Space and Decoder Decomposition
di: Hu, Chen, et al.
Pubblicazione: (2024)