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(2022/05/10) Code of ResTV2 is released! ResTv2 simplifies the EMSA structure in ResTv1 (i.e., eliminating the multi-head interaction part) and employs an upsample operation to reconstruct the lost medium- and high-frequency information caused by the downsampling operation.
The table prvoides the models and results of various models on CIFAR100. Learning rate =0.1 and will be divided by 10 every 70 epochs. Total 300 epochs. Using SGD optimizer, momentum=0.9, weight_decay=5e-4. Loss is CrossEntropyLoss. Batch-size=512.
This is a PyTorch implementation of CoAtNet specified in "CoAtNet: Marrying Convolution and Attention for All Data Sizes", arXiv 2021.
The main features of chinhsuanwu/coatnet-pytorch are: Attention Mechanisms, Vision Transformers.
Projects with overlapping indexed features include: wofmanaf/rest — (2022/05/10) Code of ResTV2 is released! ResTv2 simplifies the EMSA structure in ResTv1 (i.e., eliminating the… afeng-x/smt. ailab-cvc/groupmixformer. alinlab/remixer. amazon-research/anti-aliasing-transformer. 13952522076/spanet — The table prvoides the models and results of various models on CIFAR100. Learning rate =0.1 and will be divided by 10…