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DenseDINO: Boosting Dense Self-Supervised Learning with Token-Based Point-Level Consistency
In this paper, we propose a simple yet effective transformer framework for self-supervised learning called DenseDINO to learn dense visual representations.
RBC: Rectifying the Biased Context in Continual Semantic Segmentation
In practice, new images are usually made available in a consecutive manner, leading to a problem called Continual Semantic Segmentation (CSS).
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