语言嵌入式3D高斯对开放的词汇场景查询
IEEE transactions on pattern analysis and machine intelligence
|December 26, 2025
概括
我们介绍了Language Embedded 3D Gaussians,这是一个用于开放词汇查询的新型场景表示. 这种方法显著提高了视觉质量和语言查询准确性,同时保持了实时染速度.
科学领域:
- 计算机视觉 计算机视觉
- 3D场景理解 3D场景理解
- 自然语言处理自然语言处理.
背景情况:
- 在3D中开放的词汇查询对于场景理解至关重要,但在资源密集型神经网络中面临挑战.
- 现有的语言嵌入式3D表示在使用3D高斯时与内存使用和性能作斗争.
- 3D高斯人的高维语义特征导致了极高的记忆成本和效率的下降.
研究的目的:
- 开发一种新的场景表示,以便在3D中高效准确地进行开放词汇查询.
- 解决当前语言嵌入式3D表示的内存和性能限制.
- 在3D环境中实现高质量的视觉查询和场景理解.
主要方法:
- 引入语言 嵌入3D高斯,一个新的场景表示.
- 提出了一种量子化方案,以显著减少内存需求.
- 开发了一种新的嵌入程序,以实现更流,更高准确度的查询,并应对多视图不一致.
主要成果:
- 与现有方法相比,实现了优越的视觉质量和语言查询准确性.
- 在单个桌面GPU上演示实时染率.
- 通过专门的量子化方案,成功地减轻了内存需求.
结论:
- 语言嵌入式3D高斯为开放词汇的3D场景查询提供了高效和有效的解决方案.
- 提出的方法平衡了高精度与实时性能和减少内存足迹.
- 这种表示可以推进3D场景理解和对象本地化任务.
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