The DOI matches its Crossref record; 41 of the 41 references it cites were found in a registry or an index.
TILDE: A Temporally Invariant Learned DEtector
Open accessAbstract
We introduce a learning-based approach to detect repeatable keypoints under drastic imaging changes of weather and lighting conditions to which state-of-the-art keypoint detectors are surprisingly sensitive. We first identify good keypoint candidates in multiple training images taken from the same viewpoint. We then train a regressor to predict a score map whose maxima are those points so that they can be found by simple non-maximum suppression. As there are no standard datasets to test the influence of these kinds of changes, we created our own, which we will make publicly available. We will show that our method significantly outperforms the state-of-the-art methods in such challenging conditions, while still achieving state-of-the-art performance on untrained standard datasets.
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Cites
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SURF: Speeded Up Robust Features
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Speeded-Up Robust Features (SURF)
Bay, H., Ess, A., Tuytelaars, T., & Van Gool, L. (2008) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2007.09.014 · Cited by 13,557
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Machine Learning for High-Speed Corner Detection
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BRIEF: Binary Robust Independent Elementary Features
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Self-citationBRISK: Binary Robust invariant scalable keypoints
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Self-citationGrounding Image Matching in 3D with MASt3R
Leroy, V., Cabon, Y., & Revaud, J. (2024) · arXiv · doi:10.48550/arxiv.2406.09756 · Cited by 309
HPatches: A benchmark and evaluation of handcrafted and learned local descriptors
Balntas, V., Lenc, K., Vedaldi, A., Tuytelaars, T., Matas, J., & Mikolajczyk, K. (2019) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2019.2915233 · Cited by 132
A Review of Keypoints’ Detection and Feature Description in Image Registration
Liu, C., Xu, J., & Wang, F. (2021) · Scientific Programming · doi:10.1155/2021/8509164 · Cited by 47
Triple Robustness Augmentation Local Features for multi-source image registration
Wang, C., Xu, L., Xu, R., Xu, S., Meng, W., Wang, R., & Zhang, X. (2023) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2023.03.023 · Cited by 22
Metadata
- Authors
- Verdie, Y., Yi, K. M., Fua, P., & Lepetit, V.
- Venue
- 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
- Publisher
- IEEE
- Published
- 2015-06
- Pages
- 5279-5288
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W1945298332
- Cited by
- 332
- References
- 41
- FWCI
- 6.93
- Type
- conference paper
- Language
- en
- Open access
- green
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- Verdie, Y., Yi, K. M., Fua, P., & Lepetit, V. (2015). TILDE: A Temporally Invariant Learned DEtector. 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). https://doi.org/10.1109/cvpr.2015.7299165
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