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English(EN) Multi-Modal Guided Multi-Source Domain Adaptation for Object Detection

新的MS-DePro方法通过深度和文本提示改进目标检测

研究人员开发了一种名为MS-DePro的新方法,以改进跨不同域的目标检测。该方法使用深度图和文本提示来创建更鲁棒、域无关的特征。通过整合这些多模态输入,MS-DePro增强了定位和分类能力,在多源域自适应基准测试中取得了最先进的成果。 AI

影响 引入了一种新颖的方法来提高跨不同数据分布的目标检测准确性。

排序理由 该集群描述了一篇详细介绍目标检测新方法的学术论文。

在 Hugging Face Daily Papers 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

新的MS-DePro方法通过深度和文本提示改进目标检测

报道来源 [2]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    Multi-Modal Guided Multi-Source Domain Adaptation for Object Detection

    General object detection (OD) struggles to detect objects in the target domain that differ from the training distribution. To address this, recent studies demonstrate that training from multiple source domains and explicitly processing them separately for multi-source domain adap…

  2. arXiv cs.CV TIER_1 English(EN) · Yukyung Choi ·

    Multi-Modal Guided Multi-Source Domain Adaptation for Object Detection

    General object detection (OD) struggles to detect objects in the target domain that differ from the training distribution. To address this, recent studies demonstrate that training from multiple source domains and explicitly processing them separately for multi-source domain adap…