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CVPR19 Tracking and Detection Challenge: How crowded can it get?, , , , , , , , and . CoRR, (2019)MOTChallenge: A Benchmark for Single-Camera Multiple Target Tracking., , , , , , , and . Int. J. Comput. Vis., 129 (4): 845-881 (2021)Joint Learning of Set Cardinality and State Distribution., , , , and . AAAI, page 3968-3975. AAAI Press, (2018)MOT20: A benchmark for multi object tracking in crowded scenes., , , , , , , , and . CoRR, (2020)Learn to Predict Sets Using Feed-Forward Neural Networks., , , , , , , , and . IEEE Trans. Pattern Anal. Mach. Intell., 44 (12): 9011-9025 (2022)MOTChallenge: A Benchmark for Single-camera Multiple Target Tracking., , , , , , , and . CoRR, (2020)Multiple object tracking: A literature review., , , , , and . Artif. Intell., (2021)Learn to Predict Sets Using Feed-Forward Neural Networks., , , , , , , and . CoRR, (2020)RefineNet: Multi-Path Refinement Networks for Dense Prediction., , , , and . IEEE Trans. Pattern Anal. Mach. Intell., 42 (5): 1228-1242 (2020)DeepSetNet: Predicting Sets with Deep Neural Networks., , , , , and . ICCV, page 5257-5266. IEEE Computer Society, (2017)