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Found 3 papers, 3 papers with code
Automatic Data Curation for Self-Supervised Learning: A Clustering-Based Approach
In this work, we consider the problem of automatic curation of high-quality datasets for self-supervised pre-training.
Vision Transformers Need Registers
Transformers have recently emerged as a powerful tool for learning visual representations.
DINOv2: Learning Robust Visual Features without Supervision
The recent breakthroughs in natural language processing for model pretraining on large quantities of data have opened the way for similar foundation models in computer vision.
Ranked #1 on
Image Classification
on CIFAR-10
(using extra training data)
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