JianWang
JianWang
This is a great job, which unifies contrastive and generative method. And writting is also good. But my intuition tells me that this method seems sensitive to hyperparameters.
  你好,我发现你的代码和你的论文差异很大,框图右边的教师网络似乎并没有直接参与重建,而是与学生网络混合后重建,请问这是为什么?另外我想复现你论文中的方法,有一点不清楚:三个GO操作(全局池化加上两个全连接层,包括o/m/h)是权重不共享的吗?根据梯度更新?
In the function 'train_pcrl_2d', the variable 'n_data‘ was defined as 'len(train_loader)', but it was defined as 'len(train_dataset)' in C2L(MICCAI2020), as well as CMC(ECCV2020). Is this a mistake?