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Learning To Exploit the Sequence-Specific Prior Knowledge for Image Processing Pipelines Optimization
The ISP is less programmable and consists of a series of processing modules.
Dual Domain-Adversarial Learning for Audio-Visual Saliency Prediction
The domain discrepancy induces to performance degradation on target testing data for CNN models.
Pixel Distillation: A New Knowledge Distillation Scheme for Low-Resolution Image Recognition
To this end, we make a pioneering effort to distill helpful knowledge from a heavy network model learned from high-resolution (HR) images to a compact network model that will handle LR images, thus advancing the current knowledge distillation technique with the novel pixel distillation.
Soft-Margin Mixture of Regressions
However, existing divide-and-conquer approaches fail to deal with discontinuities between partitions (e. g., Gaussian mixture of regressions) and they cannot guarantee that the partitioned input space will be homogeneously modeled by local regressors (e. g., ordinal regression).
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