VMambaCC: A Visual State Space Model for Crowd Counting

arXiv:2405.03978v1 Announce Type: new
Abstract: As a deep learning model, Visual Mamba (VMamba) has a low computational complexity and a global receptive field, which has been successful applied to image classification and detection. To extend its applications, we apply VMamba to crowd counting and propose a novel VMambaCC (VMamba Crowd Counting) model. Naturally, VMambaCC inherits the merits of VMamba, or global modeling for images and low computational cost. Additionally, we design a Multi-head High-level Feature (MHF) attention mechanism for VMambaCC. …

abstract applications apply arxiv classification complexity computational cs.cv deep learning detection global image low mamba novel space state state space model type visual