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cs.CV2026

Latent Geometric Chords for Query-Efficient Decision-Based Adversarial Attacks

Ei Hmue Khine, Yao Li, Jiebao Sun +3

While decision-based black-box adversarial attacks present a severe security threat, current methodologies suffer from fundamental limitations. Pixel-wise attacks frequently introd…

cs.CV2025

TA-LSDiff:Topology-Aware Diffusion Guided by a Level Set Energy for Pancreas Segmentation

Yue Gou, Fanghui Song, Yuming Xing +3

Pancreas segmentation in medical image processing is a persistent challenge due to its small size, low contrast against adjacent tissues, and significant topological variations. Tr…

cs.CV2025

Progressive Alignment Degradation Learning for Pansharpening

Enzhe Zhao, Zhichang Guo, Yao Li +2

Deep learning-based pansharpening has been shown to effectively generate high-resolution multispectral (HRMS) images. To create supervised ground-truth HRMS images, synthetic data…

cs.CV2024

A Tunable Despeckling Neural Network Stabilized via Diffusion Equation

Yi Ran, Zhichang Guo, Jia Li +3

The removal of multiplicative Gamma noise is a critical research area in the application of synthetic aperture radar (SAR) imaging, where neural networks serve as a potent tool. Ho…

cs.CV2024

Adversarial Transferability in Deep Denoising Models: Theoretical Insights and Robustness Enhancement via Out-of-Distribution Typical Set Sampling

Jie Ning, Jiebao Sun, Shengzhu Shi +4

Deep learning-based image denoising models demonstrate remarkable performance, but their lack of robustness analysis remains a significant concern. A major issue is that these mode…