2022年1月10日 · Constructed entirely from standard ConvNet modules, ConvNeXts compete favorably with Transformers in terms of accuracy and scalability, achieving 87.8% ImageNet …

2025年2月27日 · However, modern ConvNets remain confined to a pyramid structure that successively downsamples the feature map for receptive field expansion, neglecting this …

2023年11月15日 · In this work, we conduct an in-depth comparative analysis of model behaviors beyond ImageNet accuracy, for both ConvNet and Vision Transformer architectures, each …

In this work, we reexamine the design spaces and test the limits of what a pure ConvNet can achieve. We gradually “modernize” a standard ResNet toward the design of a vision …

In this work, we reexamine the design spaces and test the limits of what a pure ConvNet can achieve. We gradually “modernize” a standard ResNet toward the design of a vision …

In this paper, we take a deep look at the internal structure of self-attention and present a simple Transformer style convolutional neural network (ConvNet) for visual recognition. By comparing …

6 天之前 · 卷积神经网络 (Convolutional Neural Network, ConvNet) 是目前用于图像处理、语音识别、自然语言处理等领域的主流深度学习模型之一。在 2020 年代，ConvNet 将继续发挥重要 …

摘要： 视觉识别在2020年井喷式发展，始于Vision transformer (ViTs)的引入，它很快取代了 卷积神经网络 (ConvNets)成为最先进的图像分类模型。 另一方面，普通的ViT在应用于一般的计算 …

Modernizing a ConvNet: a Roadmap 作者从ResNet-50开始，研究了一系列“network modernization”操作，通过FLOPs和在ImageNet-1K上的Acc这两个指标来验证改进操作是否 …

2022年1月10日 · We demonstrate that a standard ConvNet model can achieve the same level of scalability as hierarchical vision Transformers while being much simpler in design. We …