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.
A gift from knowledge distillation: Fast optimization, network minimization and transfer learning
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2019 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
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.