Abstract: While significant developments have been made in cell tracking algorithms, current datasets are still limited in size and diversity, especially for data-hungry generalized deep learning models. We introduce a new larger and more diverse cell tracking dataset in terms of number of sequences, length of sequences, and cell lines, accompanied with a public evaluation server and leaderboard to accelerate progress on this new challenging dataset. Our benchmarking of four top performing tracking algorithms highlights new challenges and opportunities to improve the state-of-the-art in cell tracking.
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