Segment new objects without forgetting old ones by replaying most informative samples with Zhu
- morrislee
- Apr 12, 2023
- 1 min read
Segment new objects without forgetting old ones by replaying most informative samples with Zhu
Continual Semantic Segmentation with Automatic Memory Sample Selection
arXiv paper abstract https://arxiv.org/abs/2304.05015
arXiv PDF paper https://arxiv.org/pdf/2304.05015.pdf
Continual Semantic Segmentation (CSS) extends static semantic segmentation by incrementally introducing new classes for training.
To alleviate the catastrophic forgetting issue in CSS, a memory buffer that stores a small number of samples from the previous classes is constructed for replay.
However, existing methods select the memory samples either randomly or based on a single-factor-driven handcrafted strategy, which has no guarantee to be optimal.
... propose a novel memory sample selection mechanism that selects informative samples for effective replay in a fully automatic way by considering comprehensive factors including sample diversity and class performance.
... mechanism regards the selection operation as a decision-making process and learns an optimal selection policy that directly maximizes the validation performance on a reward set.
... demonstrate the effectiveness of ... approach with state-of-the-art (SOTA) performance achieved ...
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