Summary of Opengraph: Open-vocabulary Hierarchical 3d Graph Representation in Large-scale Outdoor Environments, by Yinan Deng et al.
OpenGraph: Open-Vocabulary Hierarchical 3D Graph Representation in Large-Scale Outdoor Environments
by Yinan Deng, Jiahui Wang, Jingyu Zhao, Xinyu Tian, Guangyan Chen, Yi Yang, Yufeng Yue
First submitted to arxiv on: 14 Mar 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Robotics (cs.RO)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper proposes a novel open-vocabulary hierarchical graph representation, called OpenGraph, designed for large-scale outdoor environments. Existing visual-language models (VLMs) are typically used for small-scale indoor tasks, such as robotic navigation or manipulation. However, these models struggle to generalize to outdoor environments due to limitations in understanding level and map structure. OpenGraph initially extracts instances and captions from visual images, enhancing textual reasoning by encoding them. It then achieves 3D incremental object-centric mapping with feature embedding by projecting images onto LiDAR point clouds. Finally, the environment is segmented based on lane graph connectivity to construct a hierarchical graph. The proposed model is validated using public dataset SemanticKITTI, achieving the highest segmentation and query accuracy. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This research paper introduces a new way for robots and humans to understand outdoor environments. Currently, there are limitations in how well computers can translate images into language. This new system, called OpenGraph, is designed to overcome these limitations by creating a more detailed and organized representation of the environment. It does this by breaking down the environment into smaller parts, like objects and lanes, and then connecting them to form a graph. The results show that OpenGraph performs better than other systems in understanding and navigating outdoor environments. |
Keywords
» Artificial intelligence » Embedding
