Neural algebra of classifiers
The world is fundamentally compositional, so it is natural to think of visual recognition as the recognition of basic visually primitives that are composed according to well-defined rules. This strategy allows us to recognize unseen complex concepts from simple visual primitives. However, the current trend in visual recognition follows a data greedy approach where huge amounts of data are required to learn models for any desired visual concept. In this paper, we build on the compositionality...[Show more]
|Collections||ANU Research Publications|
|Source:||Proceedings - 2018 IEEE Winter Conference on Applications of Computer Vision, WACV 2018|
|01_Santa+Cruz_Neural_algebra_of_classifiers_2018.pdf||737.3 kB||Adobe PDF||Request a copy|
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