Attention-Enhanced Cross-Modal Localization Between Spherical Images and Point Clouds
Author:
Affiliation:
1. Electronic Information School, Wuhan University, Wuhan, China
2. Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, USA
Funder
Natural Science Foundation of Hubei Province, China
Basic and Applied Basic Research Foundation of Guangdong Province
Fundamental Research Funds for the Central Universities
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Instrumentation
Link
http://xplorestaging.ieee.org/ielx7/7361/10269339/10227896.pdf?arnumber=10227896
Reference51 articles.
1. Point-Cloud-Based Place Recognition Using CNN Feature Extraction
2. High Accuracy and Low Complexity LiDAR Place Recognition using Unitary Invariant Frobenius Norm
3. 2D3D-Matchnet: Learning To Match Keypoints Across 2D Image And 3D Point Cloud
4. Deep Multimodal Representation Learning: A Survey
5. MinkLoc3D: Point Cloud Based Large-Scale Place Recognition
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1. LIP-Loc: LiDAR Image Pretraining for Cross-Modal Localization;2024 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW);2024-01-01
2. Poses as Queries: End-to-End Image-to-LiDAR Map Localization With Transformers;IEEE Robotics and Automation Letters;2024-01
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