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Escaping the big data paradigm in self-supervised representation learning

delete2026-02-28
delete0
PRE
AI
C
Carlos García *
M
Miguel Cazorla
J
Jorge Pomares
DOI：10.1016/j.cviu.2026.104698delete
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摘要

摘要

En 中文
• SCOTT：与MIM兼容的卷积分词器，通过稀疏架构将CNN偏差注入ViTs。 • MIM-JEPA：基于掩码图像建模的JEPA，用于样本高效视觉表示学习。 • 高效数据ViTs：SCOTT+MIM-JEPA在有限数据条件下优于先前方法。 • 低资源SSL：在适度的计算预算下匹配大型基础SSL模型。
Keyword:
SCOTT
MIM-JEPA
Data-efficient ViTs
Low-resource SSL
Self-supervised representation learning

期刊

Computer Vision and Image Understanding 封面图
Computer Vision and Image Understanding
IF:
3.5
论文数:
555
被引数:
7.3K

机构

U
university of alicante
学者数:
545
论文数: 224
被引数: 0
A
automation and robotics
学者数:
1
论文数: 1
被引数: 0
引用论文

引用论文

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