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English(EN) FIRM: Fine-Grained Intra-Token Representation of Masks for Remote Sensing Reasoning Segmentation

新的FIRM方法改进了遥感分割的掩码表示

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了FIRM，一种用于遥感推理分割中掩码细粒度令牌内表示的新颖方法。该方法通过预测视觉令牌内的子单元模式，而不是单一的二元标签，来解决当前多模态大语言模型（MLLMs）的局限性。FIRM增强了小型目标、细长结构和相邻实例的表示，从而提高了物体边界的精度。该方法通过有效恢复每个子单元内的细粒度细节，在EarthReason和LaSeRS等多个基准测试中取得了最先进的结果。 AI

影响 增强了MLLM在遥感应用中精确图像分割的能力。

排序理由 这是一篇详细介绍图像分割新方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

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新的FIRM方法改进了遥感分割的掩码表示

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这是一篇详细介绍图像分割新方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Weidong Tang, Kaiyu Li, Yikai Wang, Yanan Wu, Haotian Gan, Shihong Wang, Xiangyong Cao ·

    FIRM：用于遥感推理分割的细粒度令牌内掩码表示

    arXiv:2608.13980v1 Announce Type: new Abstract: Reasoning segmentation requires multimodal large language models (MLLMs) to translate implicit instructions into precise pixel-level masks. MLLMs encode an image as visual tokens, each of which merges a group of image patches. In re…

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