For Pedestrian Detection:
- CityPersons - High-quality pedestrian detection dataset with diverse urban scenes from multiple European cities
- Caltech Pedestrian Dataset - Contains approximately 250,000 frames with 350,000 bounding boxes and 2,300 unique pedestrians
- INRIA Person Dataset - Includes full-body pedestrians in various poses and backgrounds
- MOT (Multiple Object Tracking) Dataset - Contains pedestrians in crowded scenes
For Human Attribute Analysis:
- RAP (Richly Annotated Pedestrian) Dataset - Over 40 attributes including clothing types, colors, and accessories
- PETA Dataset - Large-scale surveillance person attribute dataset with 19,000 images
- Market-1501 Attribute Dataset - Contains 27 attributes for clothing and personal items
- DeepFashion Dataset - Focuses on clothing items with detailed annotations
Some considerations when choosing a dataset:
- Make sure to check the license terms for each dataset
- Consider the image quality and diversity needed for your specific use case
- Check if the annotations match your requirements (bounding boxes, attributes, etc.)
- Verify that the dataset size is sufficient for your model training needs
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