Self-supervised image retrieval 通过从未整理的数据池中检索与精选数据源中的图像接近的图像来构建预训练数据集。对任意两张图像,使用在ImageNet22k上预训练的自监督ViT-H/16网络计算图像嵌入,并使用余弦相似度作为图像之间的距离度量。 m(s,r)=cosine\_similarity(f(s),f(r))=\frac {f(s),f(r)} {|...
DINOv2, created by Meta Research, is a new method of training computer vision models that uses self-supervised learning. This approach of training does not require labels. Labeling images is one of the most time consuming parts of training a computer vision model: each object you want to iden...
建议设置和使用虚拟环境: #Start by setting up a virtual environmentvirtualenv venv-similaritysource venv-similarity/bin/activate#Install required packagespip install transformers Pillow torch 接下来,继续计算图像相似度: import torchfrom PIL import Imagefrom transformers import AutoProcessor, CLIPModelimport...
DINO这个名字,来自于它的题目self distillation with no labels,也就是无标签的自蒸馏方法(学生网络预测教师网络的输出)。本文和MoCov3一样,也是一种自监督训练Vision Transformer的方式,但作者使用另一种操作——centering,使ViT可以稳定训练。另外本文发现自监督训练为 Vision Transformer features提供了一些新的特性。