InLoc is a dataset with reference 6DoF poses for large-scale indoor localization. Query photographs are captured by mobile phones at a different time than the reference 3D map, thus presenting a realistic indoor localization scenario.
Source: InLoc: Indoor Visual Localization with Dense Matching and View Synthesis
Variants: InLoc
This dataset is used in 1 benchmark:
Task | Model | Paper | Date |
---|---|---|---|
Pose Estimation | GIM-DKM | GIM: Learning Generalizable Image Matcher … | 2024-02-16 |
Pose Estimation | GIM-LoFTR | GIM: Learning Generalizable Image Matcher … | 2024-02-16 |
Pose Estimation | GIM-SuperGlue | GIM: Learning Generalizable Image Matcher … | 2024-02-16 |
Pose Estimation | DKM | DKM: Dense Kernelized Feature Matching … | 2022-02-01 |
Pose Estimation | LoFTR | LoFTR: Detector-Free Local Feature Matching … | 2021-04-01 |
Pose Estimation | SuperGlue | SuperGlue: Learning Feature Matching with … | 2019-11-26 |
Recent papers with results on this dataset: