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title
The Lottery Ticket Hypothesis for Object Recognition
description
We study the application of Lottery ticket Hypothesis on various object recognition models.
site name
author
updated
2026-03-09 19:03:41
raw text
The Lottery Ticket Hypothesis for Object Recognition The Lottery Ticket Hypothesis for Object Recognition CVPR 2021 Sharath Girish Shishira R Maiya Kamal Gupta Hao Chen Larry Davis Abhinav Shrivastava [Paper] [GitHub] [Poster] Abstract Recognition tasks, such as object recognition and keypoint estimation, have seen widespread adoption in recent years. Most state-of-the-art methods for these tasks use deep networks that are computationally expensive and have huge memory footprints. This makes it exceedingly difficult to deploy these systems on low power embedded devices. Hence, the importance of decreasing the storage requirements and the amount of computation in such models is paramount. The recently proposed Lottery Ticket Hypothesis (LTH) states that deep neural networks trained on large datasets contain smaller subnetworks that achieve on par performance as the dense networks. In this work, we perform the first empirical study investigating LTH for mode...
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