8 papers
MODAL: Multi-Modal Object Re-ID via Model-Driven Sparse Decoupling and Text-Image Differential Filtering
Chengbo Huang, Jun-Jie Huang, Long Lan +5
Multi-modal object re-identification (Re-ID) aims to facilitate cross-camera object retrieval in complex environments by leveraging complementary information from visual (e.g., RGB…
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…
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…
CLUENet: Cluster Attention Makes Neural Networks Have Eyes
Xiangshuai Song, Jun-Jie Huang, Tianrui Liu +2
Despite the success of convolution- and attention-based models in vision tasks, their rigid receptive fields and complex architectures limit their ability to model irregular spatia…
Enhancing Kernel Power K-means: Scalable and Robust Clustering with Random Fourier Features and Possibilistic Method
Yixi Chen, Weixuan Liang, Tianrui Liu +4
Kernel power -means (KPKM) leverages a family of means to mitigate local minima issues in kernel -means. However, KPKM faces two key limitations: (1) the computational burden…
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…