Object-Plane Co-Represented and Graph Propagation-Based Semantic Descriptor for Relocalization
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Robotics and Automation Letters"
DOI: 10.1109/lra.2022.3191056
Abstract: Relocalization is a critical component of robotics applications, it poses challenges due to changes in lighting conditions, weather, and viewing point. Image feature-based approaches are appearance-sensitive, high-level semantic landmark-based methods are ambiguous, and topological map… read more here.
Keywords: relocalization; object plane; graph; graph propagation ... See more keywords
GPENs: Graph Data Learning With Graph Propagation-Embedding Networks.
Sign Up to like & getrecommendations! Published in 2021 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2021.3120100
Abstract: Compact representation of graph data is a fundamental problem in pattern recognition and machine learning area. Recently, graph neural networks (GNNs) have been widely studied for graph-structured data representation and learning tasks, such as graph… read more here.
Keywords: representation; propagation; graph propagation; propagation embedding ... See more keywords