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Found 6 papers, 2 papers with code
Target-aware Bi-Transformer for Few-shot Segmentation
Traditional semantic segmentation tasks require a large number of labels and are difficult to identify unlearned categories.
PFENet++: Boosting Few-shot Semantic Segmentation with the Noise-filtered Context-aware Prior Mask
In this work, we revisit the prior mask guidance proposed in ``Prior Guided Feature Enrichment Network for Few-Shot Segmentation''.
Low-Rank Matrix Recovery from Noise via an MDL Framework-based Atomic Norm
The recovery of the underlying low-rank structure of clean data corrupted with sparse noise/outliers is attracting increasing interest.
Learning a Deep Part-based Representation by Preserving Data Distribution
Then one hopes to learn a new low dimensional representation which can preserve the intrinsic structure embedded in the original high dimensional data space perfectly.
Big-Data Clustering: K-Means or K-Indicators?
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.
Multi-view Common Component Discriminant Analysis for Cross-view Classification
Cross-view classification that means to classify samples from heterogeneous views is a significant yet challenging problem in computer vision.
