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Found 5 papers, 4 papers with code
Attentive Contextual Attention for Cloud Removal
By integrating the AC-Attention module into the DSen2-CR cloud removal framework, we significantly improve the model's ability to capture essential distant information, leading to more effective cloud removal.
Understanding the Overfitting of the Episodic Meta-training
Specifically, we select the teacher model as the one with the best validation accuracy during meta-training and restrict the symmetric Kullback-Leibler (SKL) divergence between the output distribution of the linear classifier of the teacher model and that of the student model.
T-former: An Efficient Transformer for Image Inpainting
And based on this attention, a network called $T$-former is designed for image inpainting.
Auxiliary Loss Reweighting for Image Inpainting
TPL and TSL are supersets of perceptual and style losses and release the auxiliary potential of standard perceptual and style losses.
Distributed Generative Adversarial Net
Recently the Generative Adversarial Network has become a hot topic.
