Auxiliary loss applied to the encoder in learned ICM models produces 27.7% and 20.3% BD-rate improvements for object detection and semantic segmentation versus standard training.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2024 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Improving Image Coding for Machines through Optimizing Encoder via Auxiliary Loss
Auxiliary loss applied to the encoder in learned ICM models produces 27.7% and 20.3% BD-rate improvements for object detection and semantic segmentation versus standard training.