高分辨率的开放词汇对象6D姿势估计
IEEE transactions on pattern analysis and machine intelligence
|October 23, 2025
概括
霍里恩是一种新的视觉语言模型 (VLM) 架构,通过使用文本提示,增强了对未见对象的6D姿势估计. 这种方法在多个数据集中实现了最先进的结果,显著提高了对象姿势确定的准确性.
科学领域:
- 计算机视觉 计算机视觉
- 机器人技术 机器人技术 机器人技术
- 人工智能的人工智能
背景情况:
- 对看不见的物体进行6D姿势估计仍然是一个重大挑战.
- 现有的视觉语言模型 (VLM) 显示出有希望的结果,但与传统基于模型的方法相比,其表现不佳.
- 自然语言提供了一种灵活的方法来描述和识别物体以估计姿势.
研究的目的:
- 介绍Horyon,一个基于VLM的开放词汇架构,用于对一个看不见的对象的两个场景之间的相对姿势估计.
- 为了利用文字提示进行对象识别和特征提取在姿势估计中.
- 建立一个新的先进的基于VLM的6D对象估计,对看不见的物体.
主要方法:
- 开发了Horyon,一个开放词汇的VLM架构,利用文本提示来理解场景.
- 实施了一种方法,使用文本提示来识别看不见的对象,并提取高分辨率,多尺度的特征.
- 利用提取的特征进行跨场景匹配和注册以确定相对位置.
主要成果:
- 在四个不同的数据集 (REAL275,Toyota-Light,Linemod,YCB-Video) 中,Horyon实现了最先进的性能.
- 拟议的方法在6D姿势估计中显示出卓越的结果,用于看不见的物体.
- 在平均回忆中超过了以前的最佳方法12.6,显示出显著的进步.
结论:
- 霍里昂代表了基于VLM的6D姿势估计对看不见的物体的重大进步.
- 该架构有效地利用自然语言进行准确的对象识别和姿势确定.
- 这项工作为开放词汇的姿势估计任务设定了新的基准.
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