Vision Mamba: Like a Vision Transformer but Better

Computer vision is advancing rapidly, with Transformers playing a key role. However, Transformers face limitations when processing high-resolution images due to their computational complexity. VisionMamba, a new model using selective state space techniques, offers significant improvements. It operates 2.8 times faster than DeiT (a popular Vision Transformer variant) and uses 86.8% less GPU memory when processing 1248x1248 pixel images. This development could enable more efficient processing of high-resolution images in various applications.