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VMamba: Visual State Space Model
April 11, 2024, 4:45 a.m. | Yue Liu, Yunjie Tian, Yuzhong Zhao, Hongtian Yu, Lingxi Xie, Yaowei Wang, Qixiang Ye, Yunfan Liu
cs.CV updates on arXiv.org arxiv.org
Abstract: Convolutional Neural Networks (CNNs) and Vision Transformers (ViTs) have long been the predominant backbone networks for visual representation learning. While ViTs have recently gained prominence over CNNs due to their superior fitting capabilities, their scalability is largely constrained by the quadratic complexity of attention computation. Inspired by the capability of Mamba in efficiently modeling long sequences, we propose VMamba, a generic vision backbone model aiming to reduce the computational complexity to linear while retaining ViTs' …
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