Competition

The system evaluates the following error measures for both tracks:

• AVG: average joint error (in mm)
• SEEN: average joint error over 'seen' subjects.
• UNSEEN: average joint error over 'unseen' subjects.

The challenge winner will be the one who achieves the lowest AVG error. 

Important note: these error measures will remain unchanged during the challenge period, however the best result per team will be analysed in more depth for dissemination of results. Please refer to the website for more evaluation details.

The download and use of the challenge dataset is released for academic research only and it is free to researchers from educational or research institutes for non-commercial purposes. When downloading the dataset you agree to (unless with expressed permission of ICVL lab): not redistribute, modificate, or commercial usage of this dataset in any way or form, either partially or entirely.

If this challenge or dataset helps you in your research, please cite the following references:

• [1] S. Yuan, Q. Ye, G. Garcia-Hernando, T.-K. Kim. The 2017 Hands in the Million Challenge on 3D Hand Pose Estimation. arXiv:1707.02237.
• [2] S. Yuan, Q. Ye, B. Stenger, S. Jain, T.-K. Kim. BigHand2. 2M Benchmark: Hand Pose Dataset and State of the Art Analysis. CVPR 2017.
• [3] G. Garcia-Hernando, S. Yuan, S. Baek, T.-K. Kim. First-Person Hand Action Benchmark with RGB-D Videos and 3D Hand Pose Annotations. arXiv:1704.02463.

For more information, please refer to challenge webpage.