Caixia Zhou — accepted AI-conference papers

2024

MuGE: Multiple Granularity Edge Detection

Caixia Zhou, Yaping Huang, Mengyang Pu, Qingji Guan, Ruoxi Deng, Haibin Ling

CVPR 2024poster

Edge segmentation is well-known to be subjective due to personalized annotation styles and preferred granularity. However most existing deterministic edge detection methods produce only a single edge map for one input image. We argue that generating multiple edge maps is more reasonable than generat…

Cited by 15 Source ↗PDF ↗Scholar ↗

2023

The Treasure Beneath Multiple Annotations: An Uncertainty-Aware Edge Detector

Caixia Zhou, Yaping Huang, Mengyang Pu, Qingji Guan, Li Huang, Haibin Ling

CVPR 2023poster

Deep learning-based edge detectors heavily rely on pixel-wise labels which are often provided by multiple annotators. Existing methods fuse multiple annotations using a simple voting process, ignoring the inherent ambiguity of edges and labeling bias of annotators. In this paper, we propose a novel…

Cited by 57 Source ↗PDF ↗code ↗Scholar ↗