Vision Transformers with Hierarchical Attention

arXiv:2106.03180v5 Announce Type: replace
Abstract: This paper tackles the high computational/space complexity associated with Multi-Head Self-Attention (MHSA) in vanilla vision transformers. To this end, we propose Hierarchical MHSA (H-MHSA), a novel approach that computes self-attention in a hierarchical fashion. Specifically, we first divide the input image into patches as commonly done, and each patch is viewed as a token. Then, the proposed H-MHSA learns token relationships within local patches, serving as local relationship modeling. Then, the small patches are merged …

arxiv attention cs.cv hierarchical transformers type vision vision transformers