Multi-Person Human Parsing Track
1. Metrics
For this task, we use two metrics for multi-human parsing evaluation. Mean IoU(%) for semantic part segmentation, reported by the FCN paper. And APr for instance-level human parsing, first introduced in Simultaneous Detection and Segmentation. The details show APr at various IoU thresholds.
2. Submit format
A parent folder named mp_results.zip(Click to download a template file) contains 2 sub-folders in it:
1. global_parsing
A folder of png images, named as "global_parsing". The content of id.png is the global human parsing results (instance-agnostic) for the image with exactly the same size.
2. instance_parsing
Named as "instance_parsing", this folder consist of two things: 1) An indexed-png image with the segmentation. Here, each number belongs to a unique part. 0 is always assumed to be the background label. 2) A text file. Each line is of the format < class_id score >. The first line of this file corresponds to 1 in the indexed png, the second line corresponds to 2 in the indexed png and so on.
3. Class Definition
- Background
- Hat
- Hair
- Glove
- Sunglasses
- Upper-clothes
- Dress
- Coat
- Socks
- Pants
- tosor-skin
- Scarf
- Skirt
- Face
- Left-arm
- Right-arm
- Left-leg
- Right-leg
- Left-shoe
- Right-shoe
4. Dataset Examples
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