50 citations · 89 across the 11 of their papers we have counts for
11 papers
Rethinking the Approximation Error in 3D Surface Fitting for Point Cloud Normal Estimation
Hang Du, Xuejun Yan, Jingjing Wang +2
Most existing approaches for point cloud normal estimation aim to locally fit a geometric surface and calculate the normal from the fitted surface. Recently, learning-based methods…
FBNet: Feedback Network for Point Cloud Completion
Xuejun Yan, Hongyu Yan, Jingjing Wang +5
The rapid development of point cloud learning has driven point cloud completion into a new era. However, the information flows of most existing completion methods are solely feedfo…
Point Cloud Upsampling via Cascaded Refinement Network
Hang Du, Xuejun Yan, Jingjing Wang +2
Point cloud upsampling focuses on generating a dense, uniform and proximity-to-surface point set. Most previous approaches accomplish these objectives by carefully designing a sing…
Scale Attention for Learning Deep Face Representation: A Study Against Visual Scale Variation
Hailin Shi, Hang Du, Yibo Hu +3
Human face images usually appear with wide range of visual scales. The existing face representations pursue the bandwidth of handling scale variation via multi-scale scheme that as…
Boosting Semi-Supervised Face Recognition with Noise Robustness
Yuchi Liu, Hailin Shi, Hang Du +4
Although deep face recognition benefits significantly from large-scale training data, a current bottleneck is the labelling cost. A feasible solution to this problem is semi-superv…
Multi-Agent Semi-Siamese Training for Long-tail and Shallow Face Learning
Hailin Shi, Dan Zeng, Yichun Tai +4
With the recent development of deep convolutional neural networks and large-scale datasets, deep face recognition has made remarkable progress and been widely used in various appli…