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Aggregates feature in different directions to enhance the communication of orientation features before computing window self-attention. We propose the equivariant-group relation module for evaluating the similarity of the equivariant-group and calculating the aggregation weights. Our network architecture for multi-level receptive field structure can expand the local receptive field to enhance the detection of small objects. The experiments validate that our model achieves state-of-the-art performance on fisheye image datasets MW-R, HABBOF, and CEPDOF. 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We declare that we do not have any commercial or associative interest that represents a conflict of interest in connection with the work submitted.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}