ChaLearn looking at people: A review of events and resources
By Sergio Escalera, Xavier Baró, Hugo Jair Escalante, Isabelle M Guyon. 2017
41 citations recorded by the source corpus.
This paper reviews the historic of ChaLearn Looking at People (LAP) events. We started in 2011 (with the release of the first Kinect device) to run challenges related to human action/activity and gesture recognition. Since then we have regularly organized events in a series of competitions covering all aspects of visual analysis of humans. So far we have organized more than 10 international challenges and events in this field. This paper reviews associated events, and introduces the ChaLearn LAP platform where public resources (including code, data and preprints of papers) related to the organized events are available. We also provide a discussion on our main findings and perspectives of ChaLearn LAP activities.
Subfields: Computer Vision and Pattern Recognition, Human-Computer Interaction
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In Computer Vision and Pattern Recognition
- Rogério Schmidt Feris
- Luc Van Gool
- Kristen Grauman
- Trevor Darrell
- Xiaogang Wang
- Chunhua Shen
- Dacheng Tao
- Yi Yang
In Human-Computer Interaction
Citations in the corpus
- Diversity in Faces (2019, methodology): “Many other data sets have been proposed for different facial analysis tasks, such as age and gender classification [24, 27, 31, 54–56], facial expression analysis [55], memorability [57], attributes [35] and aging [58].”
- Improving Smiling Detection with Race and Gender Diversity (2017, methodology): “Our model’s performance on gender classification in the FotW [15] and CelebA [22] datasets are 93.”