activity
20232026
collaborators

5 papers

cs.CV2026

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…

cs.CV2025

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…

eess.IV2025

A Lightweight Deep Exclusion Unfolding Network for Single Image Reflection Removal

Jun-Jie Huang, Tianrui Liu, Zihan Chen +3

Single Image Reflection Removal (SIRR) is a canonical blind source separation problem and refers to the issue of separating a reflection-contaminated image into a transmission and…

cs.CV2024

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…

cs.MM2023

Invertible Mosaic Image Hiding Network for Very Large Capacity Image Steganography

Zihan Chen, Tianrui Liu, Jun-Jie Huang +3

The existing image steganography methods either sequentially conceal secret images or conceal a concatenation of multiple images. In such ways, the interference of information amon…