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cs.CV2026
Uncertainty-Aware Pedestrian Attribute Recognition via Evidential Deep Learning
Zhuofan Lou, Shihang Zhang, Fangle Zhu +2
We propose UAPAR, an Uncertainty-Aware Pedestrian Attribute Recognition framework. To the best of our knowledge, this is the first EDL-based uncertainty-aware framework for pedestr…
cs.CV2019
Towards Document Image Quality Assessment: A Text Line Based Framework and A Synthetic Text Line Image Dataset
Hongyu Li, Fan Zhu, Junhua Qiu
Since the low quality of document images will greatly undermine the chances of success in automatic text recognition and analysis, it is necessary to assess the quality of document…
cs.CV2018★ 1 cited
CG-DIQA: No-reference Document Image Quality Assessment Based on Character Gradient
Hongyu Li, Fan Zhu, Junhua Qiu
Document image quality assessment (DIQA) is an important and challenging problem in real applications. In order to predict the quality scores of document images, this paper propose…