Language guided 3D object detection in point clouds for MEP scenes Article Swipe
YOU?
·
· 2023
· Open Access
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· DOI: https://doi.org/10.1049/cvi2.12261
In recent years, contrastive language‐image pre‐training (CLIP) has gained popularity for processing 2D data. However, the application of cross‐modal transferable learning to 3D data remains a relatively unexplored area. In addition, high‐quality, labelled point cloud data for Mechanical, Electrical, and Plumbing (MEP) scenarios are in short supply. To address this issue, the authors introduce a novel object detection system that employs 3D point clouds and 2D camera images, as well as text descriptions as input, using image‐text matching knowledge to guide dense detection models for 3D point clouds in MEP environments. Specifically, the authors put forth the proposition of a language‐guided point cloud modelling (PCM) module, which leverages the shared image weights inherent in the CLIP backbone. This is done with the aim of generating pertinent category information for the target, thereby augmenting the efficacy of 3D point cloud target detection. After sufficient experiments, the proposed point cloud detection system with the PCM module is proven to have a comparable performance with current state‐of‐the‐art networks. The approach has 5.64% and 2.9% improvement in KITTI and SUN‐RGBD, respectively. In addition, the same good detection results are obtained in their proposed MEP scene dataset.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1049/cvi2.12261
- https://onlinelibrary.wiley.com/doi/pdfdirect/10.1049/cvi2.12261
- OA Status
- gold
- Cited By
- 1
- References
- 66
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4389684412
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4389684412Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1049/cvi2.12261Digital Object Identifier
- Title
-
Language guided 3D object detection in point clouds for MEP scenesWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-12-12Full publication date if available
- Authors
-
Junjie Li, Shengli Du, Jianfeng Liu, Weibiao Chen, Manfu Tang, Lei Zheng, Lianfa Wang, Chunle Ji, Xiao Yu, Wanli YuList of authors in order
- Landing page
-
https://doi.org/10.1049/cvi2.12261Publisher landing page
- PDF URL
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https://onlinelibrary.wiley.com/doi/pdfdirect/10.1049/cvi2.12261Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://onlinelibrary.wiley.com/doi/pdfdirect/10.1049/cvi2.12261Direct OA link when available
- Concepts
-
Point cloud, Computer science, Artificial intelligence, Object detection, Point (geometry), Computer vision, Matching (statistics), Object (grammar), Change detection, Segmentation, Geometry, Mathematics, StatisticsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1Per-year citation counts (last 5 years)
- References (count)
-
66Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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