arXiv:2607. 13336v1 Announce Type: cross Abstract: Recent diffusion-based video generation models have enabled high-quality personalized video customization through both tuning-based pipelines, which fine-tune a video diffusion model, and reference-based pipelines such as image-to-video generation.
By Yuxin Huang, Ziming Hong, Mingming Gong, Wanyu Wang, Jing Zhang, Tongliang Liu
arXiv:2610.19717v1 Announce Type: new
Abstract: Recent advances in diffusion models have enabled high-fidelity, identity-preserving image generation for personalized applications such as digital avat...
By Lizhi Xiong, Jun Li, Ziqiang Li, Weiwei Jiang, Zhangjie Fu
arXiv:2502. 16167v2 Announce Type: replace-cross Abstract: Diffusion models (DMs) have advanced text-to-image (T2I) synthesis, yet their personalization capabilities raise serious privacy and copyright concerns.
By Xinwei Liu, Xiaojun Jia, Yuan Xun, Hua Zhang, Xiaochun Cao
LETHE is a new protection method that defends against unauthorized image‑to‑video generation by disrupting how diffusion models read a reference image. It achieves this by collapsing the spread of reference value vectors and attracting subsequent frames to these collapsed tokens, thereby severely degrading generated videos. Extensive experiments on modern I2V models and two human‑centric benchmarks show that LETHE outperforms existing protection techniques.
By Boheng Li, Yueming Xing, Yiming Li, Jie Zhang, Tianwei Zhang
The paper introduces Anti-Persona, an image-level defense that prevents unauthorized identity binding and recognition in personalized vision–language models. By aggregating visual features from multiple reference images into an identity prototype and applying subtle perturbations, the method disrupts prototype alignment in the vision‑encoder space while maintaining visual fidelity. Experiments on two personalized LVLMs show protection rates up to 95.0% and robustness across prompt variations and encoder mismatches.
By Abhishek Basu, Fahad Shamshad, Karthik Nandakumar
arXiv:2607. 22830v2 Announce Type: replace Abstract: In visual storytelling, human performances are central to creative intent and narrative meaning.
By Yuancheng Xu, Mingming He, Pablo Salamanca, Li Ma, Yash Kant, Emmett Steven, Paul Debevec, Ning Yu