15 citations · 17 across the 5 of their papers we have counts for
5 papers
Recurrent Structure Attention Guidance for Depth Super-Resolution
Jiayi Yuan, Haobo Jiang, Xiang Li +3
Image guidance is an effective strategy for depth super-resolution. Generally, most existing methods employ hand-crafted operators to decompose the high-frequency (HF) and low-freq…
Structure Flow-Guided Network for Real Depth Super-Resolution
Jiayi Yuan, Haobo Jiang, Xiang Li +3
Real depth super-resolution (DSR), unlike synthetic settings, is a challenging task due to the structural distortion and the edge noise caused by the natural degradation in real-wo…
Unsupervised Domain Adaptation for Point Cloud Semantic Segmentation via Graph Matching
Yikai Bian, Le Hui, Jianjun Qian +1
Unsupervised domain adaptation for point cloud semantic segmentation has attracted great attention due to its effectiveness in learning with unlabeled data. Most of existing method…
Generative Subgraph Contrast for Self-Supervised Graph Representation Learning
Yuehui Han, Le Hui, Haobo Jiang +2
Contrastive learning has shown great promise in the field of graph representation learning. By manually constructing positive/negative samples, most graph contrastive learning meth…
Nuclear Norm based Matrix Regression with Applications to Face Recognition with Occlusion and Illumination Changes
Jian Yang, Jianjun Qian, Lei Luo +2
Recently regression analysis becomes a popular tool for face recognition. The existing regression methods all use the one-dimensional pixel-based error model, which characterizes t…