CrowdHuman is a large and rich-annotated human detection dataset, which contains 15,000, 4,370 and 5,000 images collected from the Internet for training, validation and testing respectively. The number is more than 10× boosted compared with previous challenging pedestrian detection dataset like CityPersons. The total number of persons is also noticeably larger than the others with ∼340k person and ∼99k ignore region annotations in the CrowdHuman training subset.
Source: SADet: Learning An Efficient and Accurate Pedestrian Detector
Image Source: http://www.crowdhuman.org/
Variants: CrowdHuman (full body), CrowdHuman
This dataset is used in 1 benchmark:
| Task | Model | Paper | Date |
|---|---|---|---|
| Object Detection | S-RCNN+Ours | Progressive End-to-End Object Detection in … | 2022-03-15 |
Recent papers with results on this dataset: