Deep Learning, Artificial Intelligence, Image Classification, Vision Transformer, Transformers.
Comparisons with recent (Left) Transformer-based models and (Right) CNN models on ImageNet1K. Left: When compared with ViT-B, CrossViT-18† significantly outperforms it by 4.9% (77.9% vs 82.8%) in accuracy while requiring 50% less FLOPs and parameters. Furthermore, CrossViT-18† performs as well as