"Self-supervised research improved greatly over the past half decade, with much of the growth being driven by objectives that are hard to quantitatively compare."
Read SPC Alumni @cinjoncin's research here
https://arxiv.org/abs/1912.00215
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"Our first contribution is to show that this test is insufficient and that models which perform poorly (strongly) on linear classification can perform strongly (weakly) on more involved tasks like temporal activity localization."
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"Our second contribution is to analyze the capabilities of five different representations. And our third contribution is a much needed new dataset for temporal activity localization."
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