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Found 2 papers, 2 papers with code
Perceptual Gradient Networks
The use of perceptual loss however incurs repeated forward-backward passes in a large image classification network as well as a considerable memory overhead required to store the activations of this network.
Free-Lunch Saliency via Attention in Atari Agents
We show experimentally that a network with an FLS module exhibits performance similar to the baseline (i. e., it is "free", with no performance cost) and can be used as a drop-in replacement for reinforcement learning agents.
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