We address this problem with heuristic attention pixel-level contrastive loss for representation learning (HAPiCLR), a self-supervised joint embedding contrastive framework that operates at the pixel level and makes use of heuristic mask information. HAPiCLR leverages pixel-level information from the ...
We address this problem with heuristic attention pixel-level contrastive loss for representation learning (HAPiCLR), a self-supervised joint embedding contrastive framework that operates at the pixel level and makes use of heuristic mask information. HAPiCLR leverages pixel-level information from the ...
value of 2 distance_thres = 0.7, # ideal value is 0.7, as indicated in the paper, which makes the assumption of each feature map's pixel diagonal distance to be 1 (still unclear) similarity_temperature = 0.3, # temperature for the cosine similarity for the pixel contrastive loss alpha =...
如果 S1 和 S2 属于同一个类别,我们则建立 S1--> T --> S2 的关联,否则,关联不成立。 对于建立起关联的像素,我们 contrastively 增强他们之间(S1--> T 和 T--> S2)的联系。我们通过 minimize 如下 loss 来实现这一目的( i对应于 S1,j* 对应于T, i*对应于 S2): 其中, 表示建立起循环关联的起始...
The contrastive learning is introduced to enhance the contextual relationship between pixels in the dataset instead of just in an image. In addition, uncertainty is used to weight the segmentation loss to prompt the network focus on the learning of hard pixels. At the same time, uncertainty is ...