Deep Learning, Artificial Intelligence, Image Classification, Vision Transformer, Transformers.
FLOPs and parameters without any improvement in accuracy. Stack more cross-attention modules (L) or stack more multi-scale Transformer encoders (K) is also tested as Model (D and E). Too frequent fusion of branches does not provide any performance improvement but more FLOPs and parameters.