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Found 5 papers, 3 papers with code
Synergistic Deep Graph Clustering Network
Employing graph neural networks (GNNs) to learn cohesive and discriminative node representations for clustering has shown promising results in deep graph clustering.
TransMatting: Tri-token Equipped Transformer Model for Image Matting
However, existing methods perform poorly when faced with highly transparent foreground objects due to the large area of uncertainty to predict and the small receptive field of convolutional networks.
TransMatting: Enhancing Transparent Objects Matting with Transformers
Image matting refers to predicting the alpha values of unknown foreground areas from natural images.
When coding meets ranking: A joint framework based on local learning
In this paper, we try to answer these questions by developing the first joint sparse coding and ranking score learning algorithm.
Multi-tensor Completion for Estimating Missing Values in Video Data
Thus one question raised whether such the relationship can improve the performance of data completion or not?
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