动态MDETR:用于视觉接地的动态多模式变压器解码器
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Updated: Jul 12, 2025

13:51
Cross-Modal Multivariate Pattern Analysis
Published on: November 9, 2011
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IEEE transactions on pattern analysis and machine intelligence
|October 27, 2023
概括
我们介绍了Dynamic MDETR,这是一款用于高效视觉接地的新型多式联络变压器. 这种新型号通过动态采样图像特征来显著减少计算,以更少的处理能力实现更高的准确性.
科学领域:
- 计算机视觉 计算机视觉
- 机器学习 机器学习
- 人工智能的人工智能
背景情况:
- 多式变压器是有效的视觉接地,对准图像和文本数据.
- 现有的仅为编码器的框架,如TransVG,由于自我注意的二次时间复杂性,面临着计算挑战.
- 图像中的高空间冗余性为优化提供了机会.
研究的目的:
- 开发一个计算效率高的多式变压器,用于视觉接地.
- 通过减少计算开销来解决现有的仅编码器框架的局限性.
- 为了提高视觉接地任务的准确性和效率权衡.
主要方法:
- 提出了一个动态多模式检测变压器 (动态MDETR) 架构,将接地解成编码和解码阶段.
- 设计了一个动态多模式变压器解码器,使用2D自适应采样模块和文本引导解码模块.
- 解码器自适应地取样信息图像补丁,并通过图像和文本特征之间的交叉注意力来改进对象本地化.
主要成果:
- 动态MDETR实现了具有竞争力的精度-精度权衡,将计算成本降低了约44%的GFLOP,解码器中的特征点仅为9%.
- 性能优于TransVG (ResNet-101),使用较少的参数 (ResNet-50),额外的边际计算成本.
- 开发了第一个单阶段的CLIP授权的视觉接地框架,实现了最先进的性能并展示了强大的概括性.
结论:
- 拟议的动态MDETR可显著提高视觉接地计算效率,而不会牺牲准确性.
- 动态解码器有效地利用图像稀疏性来加速接地过程.
- 该框架显示出有希望的可扩展性和通用化能力,设置了一个新的最先进的状态.
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