SIR-Net: Scene-Independent End-to-End Trainable Visual Relocalizer
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- Type
- article
- Published
- 2019-09-01
- Cited by
- 2
- References
- 45
- OpenAlex
- https://openalex.org/W2982572434
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:207757611
Keywords
End-to-end principle, Computer science, End-user development, Computer vision, End user
References
- Minimal Scene Descriptions from Structure from Motion Models
- Scene Coordinate Regression Forests for Camera Relocalization in RGB-D Images
- Image Retrieval for Image-Based Localization Revisited
- Fast relocalisation and loop closing in keyframe-based SLAM
- From structure-from-motion point clouds to fast location recognition
- Building Rome in a day
- Multidimensional binary search trees used for associative searching
- PoseNet: A Convolutional Network for Real-Time 6-DOF Camera Relocalization
- Hyperpoints and Fine Vocabularies for Large-Scale Location Recognition
- Camera Pose Voting for Large-Scale Image-Based Localization
- Modelling uncertainty in deep learning for camera relocalization
- Visual Place Recognition: A Survey
- Structure-from-Motion Revisited
- Fast and scalable structure-from-motion based localization for high-precision mobile augmented reality systems
- City-Scale Localization for Cameras with Known Vertical Direction
- On Differentiating Parameterized Argmin and Argmax Problems with Application to Bi-level Optimization
- Efficient & Effective Prioritized Matching for Large-Scale Image-Based Localization
- Optical Flow Estimation Using a Spatial Pyramid Network
- DSAC — Differentiable RANSAC for Camera Localization
- Deep learning features at scale for visual place recognition
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