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cs.CV2026

LINA: Linear Autoregressive Image Generative Models with Continuous Tokens

Jiahao Wang, Ting Pan, Haoge Deng +4

Autoregressive models with continuous tokens form a promising paradigm for visual generation, especially for text-to-image (T2I) synthesis, but they suffer from high computational…

cs.CV2025

FoMo4Wheat: Toward reliable crop vision foundation models with globally curated data

Bing Han, Chen Zhu, Dong Han +22

Vision-driven field monitoring is central to digital agriculture, yet models built on general-domain pretrained backbones often fail to generalize across tasks, owing to the intera…

cs.CV2024

KAN See Your Face

Dong Han, Yong Li, Joachim Denzler

With the advancement of face reconstruction (FR) systems, privacy-preserving face recognition (PPFR) has gained popularity for its secure face recognition, enhanced facial privacy…

cs.CV2024

ShieldDiff: Suppressing Sexual Content Generation from Diffusion Models through Reinforcement Learning

Dong Han, Salaheldin Mohamed, Yong Li

With the advance of generative AI, the text-to-image (T2I) model has the ability to generate various contents. However, the generated contents cannot be fully controlled. There is…

cs.CV2024

Fusion is all you need: Face Fusion for Customized Identity-Preserving Image Synthesis

Salaheldin Mohamed, Dong Han, Yong Li

Text-to-image (T2I) models have significantly advanced the development of artificial intelligence, enabling the generation of high-quality images in diverse contexts based on speci…

cs.CV2024

Robust Skin Color Driven Privacy Preserving Face Recognition via Function Secret Sharing

Dong Han, Yufan Jiang, Yong Li +2

In this work, we leverage the pure skin color patch from the face image as the additional information to train an auxiliary skin color feature extractor and face recognition model…