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Found 3 papers, 2 papers with code
An EM Framework for Online Incremental Learning of Semantic Segmentation
Incremental learning of semantic segmentation has emerged as a promising strategy for visual scene interpretation in the open- world setting.
Learning Implicit Temporal Alignment for Few-shot Video Classification
Few-shot video classification aims to learn new video categories with only a few labeled examples, alleviating the burden of costly annotation in real-world applications.
Learning Context-aware Task Reasoning for Efficient Meta-reinforcement Learning
Despite recent success of deep network-based Reinforcement Learning (RL), it remains elusive to achieve human-level efficiency in learning novel tasks.
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