Learning Deep Features for Discriminative Localization

arXiv:0706.3639v1 [cs.AI] 25 Jun 2007

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For all the following models, the training complexity is proportional to O = E T Q; (1) where E is number of the training epochs, T is the number of …

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where 1 <x t <1 and = 255. This non-linear quantization produces a significantly better reconstruction than a simple linear quantization scheme. …

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Learning Deep Features for Discriminative Localization

localize the discriminative regions for action classification as the objects that the humans are interacting with rather than the humans themselves. Despite the apparent simplicity of our approach, for the weakly supervised object localization on ILSVRC bench-mark [21], our best network achieves 37.1% top-5 test er-

  Action, Object, Supervised, Localization, Supervised object localization