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ReMamber: Referring Image Segmentation with Mamba Twister
March 27, 2024, 4:46 a.m. | Yuhuan Yang, Chaofan Ma, Jiangchao Yao, Zhun Zhong, Ya Zhang, Yanfeng Wang
cs.CV updates on arXiv.org arxiv.org
Abstract: Referring Image Segmentation (RIS) leveraging transformers has achieved great success on the interpretation of complex visual-language tasks. However, the quadratic computation cost makes it resource-consuming in capturing long-range visual-language dependencies. Fortunately, Mamba addresses this with efficient linear complexity in processing. However, directly applying Mamba to multi-modal interactions presents challenges, primarily due to inadequate channel interactions for the effective fusion of multi-modal data. In this paper, we propose ReMamber, a novel RIS architecture that integrates the …
abstract arxiv complexity computation cost cs.ai cs.cv dependencies however image interactions interpretation language linear mamba modal multi-modal processing segmentation success tasks transformers type visual
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