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LangSurf: Language-Embedded Surface Gaussians for 3D Scene Understanding
Summary
LangSurf accurately aligns 3D language fields with object surfaces for precise 3D scene understanding and segmentation. This advancement enhances 3D object recognition, removal, and editing tasks.
Area of Science:
- Computer Vision
- 3D Scene Understanding
- Artificial Intelligence
Background:
- Gaussian Splatting is popular for 3D scene perception.
- Current methods struggle with precise 3D language field alignment, limiting downstream tasks.
- Existing approaches often produce imprecise language fields with outliers.
Purpose of the Study:
- To propose LangSurf, a novel method for accurate 3D language field alignment with object surfaces.
- To enable precise 2D and 3D segmentation using text queries.
- To expand downstream applications like object removal and editing in 3D scenes.
Main Methods:
- LangSurf utilizes a joint training strategy with geometry supervision and contrastive losses.
- Language Gaussians are flattened onto object surfaces for accurate feature assignment.
- A Hierarchical-Context Awareness Module extracts image-level features and uses SAM-segmented masks for fine-grained language features.
Main Results:
- LangSurf achieves precise 2D and 3D segmentation with text queries.
- The method demonstrates superior performance compared to state-of-the-art methods like LangSplat.
- Experiments show effectiveness in instance recognition, removal, and editing tasks.
Conclusions:
- LangSurf significantly improves 3D language field alignment and segmentation accuracy.
- The proposed method enhances capabilities for various 3D scene understanding tasks.
- LangSurf offers a robust solution for precise object manipulation and recognition in 3D environments.
