10 Questions
What is the main motivation for self-supervised learning?
To reduce the expense of producing a new dataset for each new task
What is one area that is mentioned as being 'supervision-starved'?
Medical data
What can strong supervision enable features to be used for in visual tasks?
Object detection and segmentation
What are the potential advantages of self-supervised learning in relation to unlabelled images/videos?
It can tap into the enormous availability of unlabelled images/videos
What is the approach suggested to solve any visual task to some extent?
Construct a large-scale dataset labelled for that task
What is self-supervision in the context of unsupervised learning?
Withholding some part of the data and asking the network to predict it
In the context of self-supervised learning, what is exemplar networks?
A specific type of network introduced by Dosovitskiy et al. in 2014
What is one of the examples given for self-supervised learning from images?
Relatively positioning two regions in the same image
How is self-supervision evaluated in the context of PASCAL VOC Detection?
By pre-training CNN using self-supervision without labels
What is the key characteristic of self-supervised learning to avoid trivial shortcuts?
Including a gap while jittering patch locations
This quiz covers the topic of self-supervised learning and discusses the ImageNet Challenge, strong supervision, and its outcomes. It also explores the use of features from networks trained on ImageNet for other visual tasks such as detection and segmentation.
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