May 12, 2022 · This paper proposes a learning-based approach, named Sparse Spatial Scene Embedding with Graph Neural Networks (S3E-GNN), as an end-to-end framework for ...

This work proposes two multitask relocalization networks called MMLNet and MML net+ for obtaining the 6-DoF camera pose in static, variable and dynamic scenes.

Co-authors ; S3E-GNN: Sparse Spatial Scene Embedding with Graph Neural Networks for Camera Relocalization. R Cheng, X Jiang, Y Chen, L Liu, T Sun. arXiv preprint ...

S3E-GNN: Sparse Spatial Scene Embedding with Graph Neural Networks for Camera Relocalization https://deepai.org/publication/s3e-gnn-sparse-spatial-scene ...

In the GNN query module, the pose graph is transformed to form a embedding-aggregated reference graph for camera relocalization. Paper

In the GNN query module, the pose graph is transformed to form a embedding-aggregated reference graph for camera relocalization. Camera Relocalization ...

This paper proposes a learning-based approach, named Sparse Spatial Scene Embedding with Graph Neural Networks (S3E-GNN), as an end-to-end framework for ...

This paper proposes a learning-based approach, named Sparse Spatial Scene Embedding with Graph Neural Networks (S3E-GNN), as an end-to-end framework for ...

This work harnesses GNNs to model the graph, allowing even non-consecutive frames to exchange information with each other, and redefine the nodes, edges, ...

S3E-GNN: Sparse Spatial Scene Embedding with Graph Neural Networks for Camera Relocalization, Ran Cheng et.al. 2205.05861, null. 2022-05-14, Multi-modal ...