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RL Boosting via Weak Supervised Learning
The dataset used in the paper is a reinforcement learning dataset, where the goal is to learn a policy that maximizes the expected return in a Markov decision process. -
Feature weighting and boosting for few-shot segmentation
This paper proposes a framework to address the issue of requiring precise masks for existing FSS tasks, which address weakly-supervised few-shot segmentation tasks with only...
