Bi-level Alignment for Cross-Domain Crowd Counting. (arXiv:2205.05844v1 [cs.CV])

Web: http://arxiv.org/abs/2205.05844

Recently, crowd density estimation has received increasing attention. The
main challenge for this task is to achieve high-quality manual annotations on a
large amount of training data. To avoid reliance on such annotations, previous
works apply unsupervised domain adaptation (UDA) techniques by transferring
knowledge learned from easily accessible synthetic data to real-world datasets.
However, current state-of-the-art methods either rely on external data for
training an auxiliary task or apply an expensive coarse-to-fine estimation. In
this work, we aim to develop …

arxiv bi cross cv