Bayesian Loss for Crowd Count Estimation With Point Supervision

Short summary

A novel Bayesian loss function improves crowd counting by directly supervising count expectation at annotated points, outperforming Gaussian kernel-based density map methods on multiple datasets, including achieving state-of-the-art on UCF-QNRF.

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