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Found 12 papers, 2 papers with code
Privileged Prior Information Distillation for Image Matting
Performance of trimap-free image matting methods is limited when trying to decouple the deterministic and undetermined regions, especially in the scenes where foregrounds are semantically ambiguous, chromaless, or high transmittance.
Label Mask AutoEncoder(L-MAE): A Pure Transformer Method to Augment Semantic Segmentation Datasets
Semantic segmentation models based on the conventional neural network can achieve remarkable performance in such tasks, while the dataset is crucial to the training model process.
Efficient Multi-view Clustering via Unified and Discrete Bipartite Graph Learning
By simultaneously formulating the view-specific bipartite graph learning, the view-consensus bipartite graph learning, and the discrete cluster structure learning into a unified objective function, an efficient minimization algorithm is then designed to tackle this optimization problem and directly achieve a discrete clustering solution without requiring additional partitioning, which notably has linear time complexity in data size.
Situational Perception Guided Image Matting
In this paper, we propose a Situational Perception Guided Image Matting (SPG-IM) method that mitigates subjective bias of matting annotations and captures sufficient situational perception information for better global saliency distilled from the visual-to-textual task.
Joint Multi-view Unsupervised Feature Selection and Graph Learning
Second, they often learn the similarity structure by either global structure learning or local structure learning, lacking the capability of graph learning with both global and local structural awareness.
Balanced and Hierarchical Relation Learning for One-Shot Object Detection
In this paper, we introduce the balanced and hierarchical learning for our detector.
GANet: Glyph-Attention Network for Few-Shot Font Generation
Font generation is a valuable but challenging task, it is time consuming and costly to design font libraries which cover all glyphs with various styles.
ExamGAN and Twin-ExamGAN for Exam Script Generation
There are opportunities to further improve the quality of generated exam scripts in various aspects.
Tripartite Information Mining and Integration for Image Matting
Regarding the nature of image matting, most researches have focused on solutions for transition regions.
Modal-aware Features for Multimodal Hashing
The modal-aware operation consists of a kernel network and an attention network.
An Interactive Insight Identification and Annotation Framework for Power Grid Pixel Maps using DenseU-Hierarchical VAE
Insights in power grid pixel maps (PGPMs) refer to important facility operating states and unexpected changes in the power grid.
Dense Adaptive Cascade Forest: A Self Adaptive Deep Ensemble for Classification Problems
Second, our model connects each layer to the subsequent ones in a feed-forward fashion, which enhances the capability of the model to resist performance degeneration.
