MambaNext: An Enhanced Backbone Network with Focus Linear Attention

Abstract

In response to the limitations of current linear attention models, such as Vision Mamba, which fail to mimic the human visual system’s ability to focus on objects and then shift attention to the surrounding context when ambiguity arises, we introduce the MambaNext model. This novel backbone network incorporates two key innovations: the Focus Linear Attention Module (FLAM) and the Star Fusion strategy. FLAM is designed to enhance object recognition by emulating the human visual system’s focused center, thereby reducing the interference from background elements. On the other hand, Star Fusion acts as a unique operation that utilizes global information as an attention map to guide local information toward more relevant features. Additionally, it also implicitly increases the feature dimensions to improve linear separability. The experimental results demonstrate that our MambaNext has achieved state-of-the-art performance across multiple computer vision tasks including classification, detection, and segmentation, outperforming existing Vision Mamba methods.