AI RESEARCH

Rotation Equivariant Mamba for Vision Tasks

arXiv CS.CV

ArXi:2603.09138v1 Announce Type: new Rotation equivariance constitutes one of the most general and crucial structural priors for visual data, yet it remains notably absent from current Mamba-based vision architectures. Despite the success of Mamba in natural language processing and its growing adoption in computer vision, existing visual Mamba models fail to account for rotational symmetry in their design. This omission renders them inherently sensitive to image rotations, thereby cons