This task aims to conduct the video instance human parsing.
VIP(Video instance-level Parsing) dataset, the first video multi-person human parsing benchmark, consists of 404 videos covering various scenarios. For every 25 consecutive frames in each video, one frame is annotated densely with pixel-wise semantic part categories and instance-level identification. There are 21247 densely annotated images in total. We divide these 404 sequences into 304 train sequences, 50 validation sequences and 50 test sequences.
For video instance-level human parsing, we use three metrics for multi-human parsing evaluation. The final score is the average of the results of these three metrics.
The results should be pack into a single zip file. Example zip file is available in vp_results.zip.
Specifically, the zip file contains 50 sub-folders in it. Each sub-folder represents a video result of test set video. Each video folder contains 3 sub-folders in it:
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.
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.
Named as "instance_segmentation", this folder consists of two things:
1) The content of id.png is the instance segmentation index image with exactly the same size. Each human instance belongs a unique human index id. 0 is always assumed to be the background label.
2) A text file id.txt. Each line is of the format . The first line of this file corresponds to human instance index 1 in instance segmentation indexed image. The second line corresponds to 2 in indexed png and so on.
After uploading you results, please wait for about 2 hours and refrash your page to see the scores.
The datasets are released for academic research only and it is free to researchers from educational or research institutions for non-commercial purposes. When downloading the dataset you agree not to reproduce, duplicate, copy, sell, trade, resell or exploit for any commercial purposes, any portion of the images and any portion of derived data.
For more information, please concate us at email@example.com or firstname.lastname@example.org.
Start: Feb. 20, 2020, midnight
Sept. 30, 2020, midnight
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