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Mengyang Pu
Mengyang Pu
Verified email at ncepu.edu.cn
Title
Cited by
Cited by
Year
Edter: Edge detection with transformer
M Pu, Y Huang, Y Liu, Q Guan, H Ling
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022
982022
Shadow removal by a lightness-guided network with training on unpaired data
Z Liu, H Yin, Y Mi, M Pu, S Wang
IEEE Transactions on Image Processing 30, 1853-1865, 2021
622021
GraphNet: Learning image pseudo annotations for weakly-supervised semantic segmentation
M Pu, Y Huang, Q Guan, Q Zou
Proceedings of the 26th ACM international conference on Multimedia, 483-491, 2018
462018
Rindnet: Edge detection for discontinuity in reflectance, illumination, normal and depth
M Pu, Y Huang, Q Guan, H Ling
Proceedings of the IEEE/CVF international conference on computer vision …, 2021
332021
Object discovery from a single unlabeled image by mining frequent itemsets with multi-scale features
R Zhang, Y Huang, M Pu, J Zhang, Q Guan, Q Zou, H Ling
IEEE Transactions on Image Processing 29, 8606-8621, 2020
272020
Learning from pixel-level label noise: A new perspective for semi-supervised semantic segmentation
R Yi, Y Huang, Q Guan, M Pu, R Zhang
IEEE Transactions on Image Processing 31, 623-635, 2021
182021
The treasure beneath multiple annotations: An uncertainty-aware edge detector
C Zhou, Y Huang, M Pu, Q Guan, L Huang, H Ling
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023
122023
Detecting dense text in natural images
D Jiang, S Zhang, Y Huang, Q Zou, X Zhang, M Pu, J Liu
IET Computer Vision 14 (8), 597-604, 2020
22020
SSGAM-Net: A Hybrid Semi-Supervised and Supervised Network for Robust Semantic Segmentation Based on Drone LiDAR Data
H Wu, Z Huang, W Zheng, X Bai, L Sun, M Pu
Remote Sensing 16 (1), 92, 2023
2023
Swin Transformer Based Crack Detection
N Verma, M Pu, M Zhang, D Prokhorov, J Wei, H Ling
The Treasure Beneath Multiple Annotations: An Uncertainty-aware Edge Detector Supplementary Material
C Zhou, Y Huang, M Pu, Q Guan, L Huang, H Ling
EDTER: Edge Detection with Transformer Supplementary Material
M Pu, Y Huang, Y Liu, Q Guan, H Ling
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