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20212026
most citedPerturbing Attention Gives You More Bang for the Buck: Subtle Imaging Perturbations That Efficiently Fool Customized Diffusion Models

10 citations · 14 across the 5 of their papers we have counts for

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cs.CV2026

Beyond Pixel Reconstruction: Retrieval-Guided Glyph-Aware Restoration for Low-Resource Manchu Historical Documents

Ting Huang, Dongdong Wang, Mingqiu Liang +1

Historical Manchu documents preserve invaluable linguistic and cultural heritage, yet their digitization is hindered by severe degradations and the scarcity of paired training data…

cs.CV2026

Think Before You Restore: Risk-Aware Manchu Manuscript Restoration with Stroke-Guided Attention

Mingqiu Liang, Dongdong Wang, Siyang Lu +2

Full-page blind restoration of historical Manchu manuscripts is challenging due to scarce annotations, unknown degradation regions, and fragile connected strokes. Generic restorati…

cs.CV2026

Can Attack Difficulty Be Characterized Before Optimization? A Study of Pre-optimization Difficulty in Person-Vanishing Attacks

Jingyao Xu, Dongdong Wang, Siyang Lu

Adversarial attacks against object detectors are traditionally studied from an optimization perspective, where attack difficulty is regarded as an outcome observed only after adver…

cs.CV2026

AWPD: Frequency Shield Network for Agnostic Watermark Presence Detection

Xiang Ao, Yilin Du, Zidan Wang +2

Invisible watermarks, as an essential technology for image copyright protection, have been widely deployed with the rapid development of social media and AIGC. However, existing in…

cs.CV2024★ 10 cited

Perturbing Attention Gives You More Bang for the Buck: Subtle Imaging Perturbations That Efficiently Fool Customized Diffusion Models

Jingyao Xu, Yuetong Lu, Yandong Li +3

Diffusion models (DMs) embark a new era of generative modeling and offer more opportunities for efficient generating high-quality and realistic data samples. However, their widespr…