Director of Research (if dissertation) or Advisor (if thesis)
Adve, Vikram
Department of Study
Computer Science
Discipline
Computer Science
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
Open world
Semi supervised learning
Object Detection
Abstract
Traditional object detection networks work with large amounts of labeled data and under the assumption of a closed set, such that the test data only contains instances of classes already seen in the training set. These assumptions are challenged when deploying these methods in the wild. In this work we introduce Open World Semi Supervised Object Detection (OWSSD), a semi supervised learning framework that works in the open world setup. OWSSD effectively captures the novelty of unseen data compared to seen data and updates the detection framework to discover new classes on the fly.
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