AI RESEARCH
MicroViTv2: Beyond the FLOPS for Edge Energy-Friendly Vision Transformers
arXiv CS.CV
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ArXi:2605.10148v1 Announce Type: new The Vision Transformer (ViT) achieves remarkable accuracy across visual tasks but remains computationally expensive for edge deployment. This paper presents MicroViTv2, a lightweight Vision Transformer optimized for real-device efficiency. Built upon the original MicroViT, the proposed model is designed based on reparameterized design, specifically Reparameterized Patch Embedding (RepEmbed) and Reparameterized Depth-Wise convolution mixer (RepDW) for faster inference, and.