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English(EN) MSRNet: A Multi-Scale Recursive Network for Camouflaged Object Detection

MSRNet 通过多尺度递归网络推进伪装目标检测

研究人员开发了 MSRNet,一种新颖的多尺度递归网络,专为具有挑战性的伪装目标检测任务而设计。该网络利用金字塔视觉 Transformer 主干跨多个尺度提取特征,并使用专门的基于注意力的尺度集成单元进行集成。解码器通过多粒度融合单元和递归反馈策略递归地精炼这些特征,以提高全局上下文理解能力。MSRNet 在基准数据集上展示了最先进的性能,尤其在处理小型和多个伪装目标方面表现出色。 AI

影响 这种新的网络架构可以提高复杂视觉环境中目标检测的准确性和效率,在监控、自主系统和图像分析等领域具有潜在应用。

排序理由 该集群描述了一篇详细介绍用于特定计算机视觉任务的新颖网络架构的新学术论文。 [lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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MSRNet 通过多尺度递归网络推进伪装目标检测

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该集群描述了一篇详细介绍用于特定计算机视觉任务的新颖网络架构的新学术论文。 [lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Leena Alghamdi, Muhammad Usman, Hafeez Anwar, Abdul Bais, Saeed Anwar ·

    MSRNet:一种用于伪装目标检测的多尺度递归网络

    arXiv:2511.12810v2 Announce Type: replace-cross Abstract: Camouflaged object detection is an emerging and challenging computer vision task that requires identifying and segmenting objects that blend seamlessly into their environments due to high similarity in color, texture, and …