Probabilistic Graph Attention Network With Conditional Kernels for Pixel-Wise Prediction

@article{Xu2022ProbabilisticGA,
  title={Probabilistic Graph Attention Network With Conditional Kernels for Pixel-Wise Prediction},
  author={Dan Xu and Xavier Alameda-Pineda and Wanli Ouyang and Elisa Ricci and Xiaogang Wang and N. Sebe},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2022},
  volume={44},
  pages={2673-2688}
}
Multi-scale representations deeply learned via convolutional neural networks have shown tremendous importance for various pixel-level prediction problems. In this paper we present a novel approach that advances the state of the art on pixel-level prediction in a fundamental aspect, i.e. structured multi-scale features learning and fusion. In contrast to previous works directly considering multi-scale feature maps obtained from the inner layers of a primary CNN architecture, and simply fusing… 

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