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Bias-Aware Heapified Policy for Active Learning
Last but not least, we investigate the generalization of the HAL policy learned on MNIST dataset by directly applying it on MNIST-M. We show that the agent can generalize and outperform directly-learned policy under constrained labeled sets.
360-Indoor: Towards Learning Real-World Objects in 360° Indoor Equirectangular Images
In this paper, our goal is to provide a standard dataset to facilitate the vision and machine learning communities in 360{\deg} domain.
Leveraging Motion Priors in Videos for Improving Human Segmentation
Recently, a few domain adaptation and active learning approaches have been proposed to mitigate the performance drop.
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