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cs.CV2026
AutoVQA-G: Self-Improving Agentic Framework for Automated Visual Question Answering and Grounding Annotation
Rongsheng Hu, Runwei Guan, Yicheng Di +2
Manual annotation of high-quality visual question answering with grounding (VQA-G) datasets, which pair visual questions with evidential grounding, is crucial for advancing vision-…
cs.CV2026
StyMam: A Mamba-Based Generator for Artistic Style Transfer
Zhou Hong, Ning Dong, Yicheng Di +8
Image style transfer aims to integrate the visual patterns of a specific artistic style into a content image while preserving its content structure. Existing methods mainly rely on…
cs.CV2025
OMUDA: Omni-level Masking for Unsupervised Domain Adaptation in Semantic Segmentation
Yang Ou, Xiongwei Zhao, Xinye Yang +5
Unsupervised domain adaptation (UDA) enables semantic segmentation models to generalize from a labeled source domain to an unlabeled target domain. However, existing UDA methods st…