# Hierarchical feature extraction

The first hybrid computer vision model combining the strengths of Mamba and Transformer, enhancing visual feature modeling efficiency by reconstructing the Mamba formula, and introducing self-attention modules in the final layers of the Mamba architecture to improve long-range spatial dependency modeling.

MambaVision is the first hybrid computer vision model combining the strengths of Mamba and Transformer. It enhances visual feature modeling by reconstructing the Mamba formulation and incorporates self-attention modules in the final layers of the Mamba architecture to improve long-range spatial dependency modeling.

Swin Transformer v2 is a vision Transformer model that achieves efficient image processing through hierarchical feature maps and local window self-attention mechanisms.