collaborators

5 papers

cs.CV2026

Evaluating Dataset Watermarking for Fine-tuning Traceability of Customized Diffusion Models: A Comprehensive Benchmark and Removal Approach

Xincheng Wang, Hanchi Sun, Wenjun Sun +8

Recent fine-tuning techniques for diffusion models enable them to reproduce specific image sets, such as particular faces or artistic styles, but also introduce copyright and secur…

cs.CV2026

AMIF: Authorizable Medical Image Fusion Model with Built-in Authentication

Jie Song, Jun Jia, Wei Sun +3

Multimodal image fusion enables precise lesion localization and characterization for accurate diagnosis, thereby strengthening clinical decision-making and driving its growing prom…

cs.CV2026

DP^2-VL: Private Photo Dataset Protection by Data Poisoning for Vision-Language Models

Hongyi Miao, Jun Jia, Xincheng Wang +7

Recent advances in visual-language alignment have endowed vision-language models (VLMs) with fine-grained image understanding capabilities. However, this progress also introduces n…

cs.CV2025

Adapter Shield: A Unified Framework with Built-in Authentication for Preventing Unauthorized Zero-Shot Image-to-Image Generation

Jun Jia, Hongyi Miao, Yingjie Zhou +8

With the rapid progress in diffusion models, image synthesis has advanced to the stage of zero-shot image-to-image generation, where high-fidelity replication of facial identities…

eess.IV2025

DLADiff: A Dual-Layer Defense Framework against Fine-Tuning and Zero-Shot Customization of Diffusion Models

Jun Jia, Hongyi Miao, Yingjie Zhou +8

With the rapid advancement of diffusion models, a variety of fine-tuning methods have been developed, enabling high-fidelity image generation with high similarity to the target con…