VMamba: Visual State Space Model

Understand

Designing computationally efficient network architectures remains an ongoing necessity in computer vision.

• In this paper, we adapt Mamba, a state-space language model, into VMamba, a vision backbone with linear time complexity.
• At the core of VMamba is a stack of Visual State-Space (VSS) blocks with the 2D Selective Scan (SS2D) module.
• By traversing along four scanning routes, SS2D bridges the gap between the ordered nature of 1D selective scan and the non-sequential structure of 2D vision data, which facilitates the collection of contextual information from various sources and perspectives.