A paced multi-stage block-wise approach for object detection in thermal images
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Graphics and Computer-Aided Design,Computer Vision and Pattern Recognition,Software
Link
https://link.springer.com/content/pdf/10.1007/s00371-022-02445-x.pdf
Reference51 articles.
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2. Benenson R., Omran, M., Hosang J., Schiele, B.: Ten years of pedestrian detection, what have we learned? In: Agapito, L., Bronstein, M., Rother, C. (eds.) Computer Vision–ECCV 2014 Workshops. ECCV 2014. Lecture Notes in Computer Science, vol. 8926. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-16181-5_47
3. Berg, A., Ahlberg, J., Felsberg, M.: A thermal object tracking benchmark. In: 2015 12th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS) (2015). https://doi.org/10.1109/AVSS.2015.7301772
4. Bochkovskiy, A., Wang, C.Y., Liao, H.Y.M.: Yolov4: Optimal speed and accuracy of object detection (2020). arXiv:2004.10934
5. Braun, M., Krebs, S., Flohr, F.B., Gavrila, D.M.: Eurocity persons: a novel benchmark for person detection in traffic scenes. IEEE Trans. Pattern Anal. Mach. Intell. 41, 1844–1861 (2019). https://doi.org/10.1109/TPAMI.2019.2897684
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