Camera Localization
38 papers with code • 2 benchmarks • 4 datasets
Latest papers
SPVLoc: Semantic Panoramic Viewport Matching for 6D Camera Localization in Unseen Environments
In this paper, we present SPVLoc, a global indoor localization method that accurately determines the six-dimensional (6D) camera pose of a query image and requires minimal scene-specific prior knowledge and no scene-specific training.
Improved Scene Landmark Detection for Camera Localization
To mitigate the capacity issue, we propose to split the landmarks into subgroups and train a separate network for each subgroup.
SemanticSLAM: Learning based Semantic Map Construction and Robust Camera Localization
This approach enables the creation of a semantic map of the environment and ensures reliable camera localization.
Boosting 3-DoF Ground-to-Satellite Camera Localization Accuracy via Geometry-Guided Cross-View Transformer
In this paper, we propose a method to increase the accuracy of a ground camera's location and orientation by estimating the relative rotation and translation between the ground-level image and its matched/retrieved satellite image.
Synfeal: A Data-Driven Simulator for End-to-End Camera Localization
Our results also suggest that when a large localization dataset with high quality is available, training from scratch leads to better performances.
Region contrastive camera localization
The proposed approach maps image features from different camera views of the same 3D region to nearby points in the learned feature space.
Shared Coupling-bridge for Weakly Supervised Local Feature Learning
Sparse local feature extraction is usually believed to be of important significance in typical vision tasks such as simultaneous localization and mapping, image matching and 3D reconstruction.
Fast and Lightweight Scene Regressor for Camera Relocalization
The proposed approach uses sparse descriptors to regress the scene coordinates, instead of a dense RGB image.
ESLAM: Efficient Dense SLAM System Based on Hybrid Representation of Signed Distance Fields
We present ESLAM, an efficient implicit neural representation method for Simultaneous Localization and Mapping (SLAM).
NeuMap: Neural Coordinate Mapping by Auto-Transdecoder for Camera Localization
State-of-the-art feature matching methods require each scene to be stored as a 3D point cloud with per-point features, consuming several gigabytes of storage per scene.