113 citations · 192 across the 6 of their papers we have counts for
6 papers · 1 filter
The Treasure Beneath Multiple Annotations: An Uncertainty-aware Edge Detector
Caixia Zhou, Yaping Huang, Mengyang Pu +3
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 voti…
EDTER: Edge Detection with Transformer
Mengyang Pu, Yaping Huang, Yuming Liu +2
Convolutional neural networks have made significant progresses in edge detection by progressively exploring the context and semantic features. However, local details are gradually…
RINDNet: Edge Detection for Discontinuity in Reflectance, Illumination, Normal and Depth
Mengyang Pu, Yaping Huang, Qingji Guan +1
As a fundamental building block in computer vision, edges can be categorised into four types according to the discontinuity in surface-Reflectance, Illumination, surface-Normal or…
Learning from Pixel-Level Label Noise: A New Perspective for Semi-Supervised Semantic Segmentation
Rumeng Yi, Yaping Huang, Qingji Guan +2
This paper addresses semi-supervised semantic segmentation by exploiting a small set of images with pixel-level annotations (strong supervisions) and a large set of images with onl…
Shadow Removal by a Lightness-Guided Network with Training on Unpaired Data
Zhihao Liu, Hui Yin, Yang Mi +2
Shadow removal can significantly improve the image visual quality and has many applications in computer vision. Deep learning methods based on CNNs have become the most effective a…
Object Discovery From a Single Unlabeled Image by Mining Frequent Itemset With Multi-scale Features
Runsheng Zhang, Yaping Huang, Mengyang Pu +4
TThe goal of our work is to discover dominant objects in a very general setting where only a single unlabeled image is given. This is far more challenge than typical co-localizatio…