7 citations · 14 across the 5 of their papers we have counts for
5 papers
PFENet++: Boosting Few-shot Semantic Segmentation with the Noise-filtered Context-aware Prior Mask
Xiaoliu Luo, Zhuotao Tian, Taiping Zhang +3
In this work, we revisit the prior mask guidance proposed in ``Prior Guided Feature Enrichment Network for Few-Shot Segmentation''. The prior mask serves as an indicator that highl…
Low-Rank Matrix Recovery from Noise via an MDL Framework-based Atomic Norm
Anyong Qin, Lina Xian, Yongliang Yang +2
The recovery of the underlying low-rank structure of clean data corrupted with sparse noise/outliers is attracting increasing interest. However, in many low-level vision problems,…
Learning a Deep Part-based Representation by Preserving Data Distribution
Anyong Qin, Zhaowei Shang, Zhuolin Tan +2
Unsupervised dimensionality reduction is one of the commonly used techniques in the field of high dimensional data recognition problems. The deep autoencoder network which constrai…
Big-Data Clustering: K-Means or K-Indicators?
Feiyu Chen, Yuchen Yang, Liwei Xu +2
The K-means algorithm is arguably the most popular data clustering method, commonly applied to processed datasets in some "feature spaces", as is in spectral clustering. Highly sen…
Multi-view Common Component Discriminant Analysis for Cross-view Classification
Xinge You, Jiamiao Xu, Wei Yuan +3
Cross-view classification that means to classify samples from heterogeneous views is a significant yet challenging problem in computer vision. A promising approach to handle this p…