DINOv2: Learning Robust Visual Features without Supervision
- 类型:arxiv
- 标识:2304.07193
- 链接:https://arxiv.org/abs/2304.07193
- 主题:rag
- 主分类:multimodal
- 形态:method
- 被引:9976
- 被引来源:Semantic Scholar
- S2被引:9976
- OpenAlex被引:1067
- 影响力被引:1445
- TLDR:This work revisits existing approaches and combines different techniques to scale the pretraining in terms of data and model size, and proposes an automatic pipeline to build a dedicated, diverse, and curated image dataset instead of uncurated data, as typically done in the self-supervised literature.
- OpenAlex ID:W4366208220
- OpenAlex DOI:10.48550/arxiv.2304.07193
- DOI:10.48550/arxiv.2304.07193
- DOI来源:OpenAlex
- 开放获取:green
- 开放获取链接:https://arxiv.org/pdf/2304.07193
- OpenAlex更新:2026-08-22
- 待LLM分类:否
- 标题中文:DINOv2:无监督学习鲁棒的视觉特征
- TLDR中文:本文回顾现有方法,并融合多种技术从数据与模型规模两方面扩展预训练,提出一条自动化流水线以构建专用、多样且经过筛选的图像数据集,替代自监督文献中常用的未筛选数据。
- 来源文件:
- [OpenAlex discover]
- [S2 enrich]