White balance (WB) algorithms in many commercial cameras assume single and uniform illumination, leading to undesirable results when multiple lighting sources with different chromaticities exist in the scene.
To the best of our knowledge, we are the first to explore Domain Matching-based RefSR in remote sensing image processing.
Images in our dataset are mostly captured with illuminants existing in the scene, and the ground truth illumination is computed by taking the difference between the images with different illumination combination.
Text localization from the digital image is the first step for the optical character recognition task.
When there is a mismatch between the target identity and the driver identity, face reenactment suffers severe degradation in the quality of the result, especially in a few-shot setting.
In addition, we release the implementation of the proposed and the baseline models including an end-to-end pipeline for training models and evaluating them on mobile devices.
Ranked #14 on Keyword Spotting on Google Speech Commands (Google Speech Commands V2 12 metric)
We also report that the proposed method significantly outperforms the existing method in the 2-bit quantization of an LSTM for language modeling.