A GAN-based adversarial training method distills knowledge from teacher to student networks by treating their feature maps as real and fake samples to boost one-stage object detector performance.
Shufflenet: An extremely efficient convolutional neural net- work for mobile devices
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GAN-Knowledge Distillation for one-stage Object Detection
A GAN-based adversarial training method distills knowledge from teacher to student networks by treating their feature maps as real and fake samples to boost one-stage object detector performance.