5 papers
IDATA: Scalable Invertible Diffusion for Unrestricted Adversarial Transfer Attack
Yi Pan, Jun-Jie Huang, Tianrui Liu +3
Unrestricted adversarial transfer attacks are important for evaluating the black-box robustness of deep visual models. Diffusion-based attacks have shown promising transferability…
MissClick: Exploiting Digit-Serialized Coordinates to Attack GUI Grounding Models
Yu Ran, Wentao Zhao, Xin Zhang +1
Recent GUI visual grounding models generate screen coordinates as sequences of digit tokens that are parsed into numerical values and mapped to executable clicks. The security impl…
Combined Dictionary Unfolding Network with Gradient-Adaptive Fidelity for Transferable Multi-Source Fusion
Ge Luo, Jun-Jie Huang, Qi Yu +6
Deep Unfolding Network-based methods have emerged as effective solutions for multi-source image fusion by combining model-driven iterative optimization with data-driven deep learni…
SMILENet: Unleashing Extra-Large Capacity Image Steganography via a Synergistic Mosaic InvertibLE Hiding Network
Jun-Jie Huang, Zihan Chen, Tianrui Liu +5
Existing image steganography methods face fundamental limitations in hiding capacity (typically images) due to severe information interference and uncoordinated capacity-d…
SVASTIN: Sparse Video Adversarial Attack via Spatio-Temporal Invertible Neural Networks
Yi Pan, Jun-Jie Huang, Zihan Chen +2
Robust and imperceptible adversarial video attack is challenging due to the spatial and temporal characteristics of videos. The existing video adversarial attack methods mainly tak…