Vision transformer architectures (ViTs) have achieved compelling performance across many computer vision tasks, often outperforming classical convolutional architectures. A question arises: Is the impressive performance of ViTs due to their powerful transformer architecture and attention mechanisms, or is there some other factor that gives ViTs their edge? In the paper Patches Are All You Need…
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