[2010.11929] An Image is Worth 16x16 Words: Transformers for …
2020年10月22日 · When pre-trained on large amounts of data and transferred to multiple mid-sized or small image recognition benchmarks (ImageNet, CIFAR-100, VTAB, etc.), Vision …
【ICLR2021】ViT : Vision Transformer解读（论文+源码） - 知乎
具体来说，Vit的思想是把图片分割成小块，然后将这些小块作为一个线性的embedding作为transformer的输入，处理方式与NLP中的token相同，用监督训练的方式进行图像分类。
CrossViT: Cross-Attention Multi-Scale Vision Transformer for …
2021年3月27日 · The recently developed vision transformer (ViT) has achieved promising results on image classification compared to convolutional neural networks. Inspired by this, in this …
GitHub - google-research/vision_transformer
In this repository we release models from the papers. How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers. The models were pre-trained on the ImageNet and …
Title: Your ViT is Secretly an Image Segmentation Model - arXiv.org
2025年3月24日 · In this paper, we show that the inductive biases introduced by these task-specific components can instead be learned by the ViT itself, given sufficiently large models …
CVPR 2021 Visual Transformer 论文合集（附20篇推荐必读ViT论文）
2021年6月7日 · 最近，Visual Transformer 的研究热点达到了前所未有的高峰，仅 CVPR 2021 就发表了 40 多篇， 应用涉及： 图像分类、目标检测、实例分割、语义分割、行为识别、自动 …
VITEEE Previous Year Question Papers - Free Download PDF
6 天之前 · The VITEEE last year question papers are a precious tool for candidates who are preparing for the VIT Engineering Entrance Exam. The VITEEE previous year question papers …
A Novel ViT Model with Wavelet Convolution and SLAttention
2025年3月22日 · Underwater acoustic target recognition (UATR) technology plays a significant role in marine exploration, resource development, and national defense security. To address …
【PAPER MEMO】 Vision Transformer（ViT） - 知乎专栏
本文提出了一种基于Transformer的 图像分类 模型Vision Transformer (ViT)。 ViT通过将 图像分割 成patch序列，利用Transformer的自注意力机制进行编码，并在多个数据集上取得了SOTA表 …
『论文精读』Vision Transformer(VIT)论文解读 - CSDN博客
2023年6月16日 · ViT是2020年Google团队提出的将Transformer应用在图像分类的模型，虽然不是第一篇将transformer应用在视觉任务的论文，但是因为其模型 “简单”且效果好，可扩展性 …