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Learning Multi-Object Tracking and Segmentation From Automatic Annotations.

, , , , , and . CVPR, page 6845-6854. Computer Vision Foundation / IEEE, (2020)

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Hierarchical Novelty Detection for Traffic Sign Recognition., and . Sensors, 22 (12): 4389 (2022)Learning Multi-Object Tracking and Segmentation From Automatic Annotations., , , , , and . CVPR, page 6845-6854. Computer Vision Foundation / IEEE, (2020)Optimizing speed/accuracy trade-off for person re-identification via knowledge distillation., , , and . Eng. Appl. Artif. Intell., (2020)Weakly Supervised Multi-Object Tracking and Segmentation., , , , and . WACV (Workshops), page 125-133. IEEE, (2021)Learning Multi-Object Tracking and Segmentation from Automatic Annotations., , , , , and . CoRR, (2019)Deep Metric Learning for re-identification, tracking and hierarchical novelty detection. Autonomous University of Barcelona, Spain, (2023)Metric Learning for Novelty and Anomaly Detection., , , , and . BMVC, page 64. BMVA Press, (2018)Rank-based ordinal classification., and . ICPR, page 8069-8076. IEEE, (2020)Optimizing Speed/Accuracy Trade-Off for Person Re-identification via Knowledge Distillation., , , and . CoRR, (2018)Time series data mining for the Gaia variability analysis., , , , , , , , , and . CoRR, (2014)