AI RESEARCH
Deformba: Vision State Space Model with Adaptive State Fusion
arXiv CS.CV
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ArXi:2605.21308v1 Announce Type: new State Space Models (SSMs) have emerged as a powerful and efficient alternative to Transformers, nstrating linear-time complexity and exceptional sequence modeling capabilities. However, their application to vision tasks remains challenging. First, existing vision SSMs largely depend on manually designed fixed scanning methods to flatten image patches into sequences, which imposes predefined geometric structures and increases the complexity.