CFC-DAOD (Caltech Fish Counting – Domain Adaptive Object Detection)

Introduced by Kay et al. in Align and Distill: Unifying and Improving Domain Adaptive Object Detection

CFC-DAOD is a domain adaptation extension to the Caltech Fish Counting domain generalization benchmark.

The goal is cross-domain object detection of a single class, "fish", in sonar videos. The source domain consists of data from one river, Kenai, and the target domain consists of data from another out-of-domain river, Channel. CFC-DAOD introduces new data from the target domain to be used for unsupervised domain adaptive object detection: 168k bounding box annotations in 29k frames sampled from 150 new videos captured over two days from 3 different sensors on the Channel river.

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