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 Transformer (ViT) attains excellent results compared to state-of-the-art convolutional networks while requiring substantially fewer computational resources to train.

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。

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 paper, we study how to...

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 ImageNet-21k datasets. We provide the code for fine-tuning the released models in JAX / Flax.

6 天之前 · 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 and extensive pre-training. Based on these findings, we introduce the Encoder-only Mask Transformer (EoMT), which repurposes the plain ViT architecture to conduct image segmentation.

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、自动驾驶、关键点匹配、目标跟踪、NAS、low-level视觉、HoI、可解释性、布局生成、检索、文本检测 等方向。 引爆CV圈 Transformer 热潮的有两篇最具代表性论文，即 ECCV 2020的 DETR（目标检测） 和 ICLR 2021的 ViT（图像分类）。 1. End-to-End Human Pose and Mesh Reconstruction …

5 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 give a clear idea of the VITEEE exam, pattern, most asked questions, and topic-wise weightage, enabling students to plan their preparation accordingly.Solving VITEEE past year papers helps candidates enhance their speed ...

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 the limitations of existing methods in computational efficiency and recognition performance, this paper proposes an improved WS-ViT model based on Vision Transformers (ViTs). By introducing the Wavelet Transform Convolution ...

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表现。 此外，ViT在训练时需要的计算资源更少，证明了标准Transformer模型可以应用于图像识别任务，并且与当前的最先进的 卷积网络 相媲美。 论文基本内容大纲. 根据文档内容，我总结了以下大纲： 一、 引言. 研究背景：Transformer在NLP领域表现出色，但在 计算机视觉 中的应用相对有 …

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，可扩展性强（scalable，模型越大效果越好），成为了transformer在CV领域应用的里程碑著作，也引爆了后续 …