How do Vision Transformers and Convolutional Neural Networks differ in handling computer vision tasks? How do CNNs extract features using convolutional filters compared to the self-attention mechanism in Transformers? What are the advantages of Transformers over CNNs in image recognition and large-scale datasets? In what scenarios do CNNs still perform better than Transformers? What are the current challenges and future trends when comparing Transformers and CNNs in computer vision applications?