Training a State-of-the-Art ImageNet-1K Visual Transformer Model using NVIDIA DGX SuperPOD – NVIDIA Technical Blog News and tutorials for developers, data scientists, and IT admins 2025-04-06T02:18:37Z http://www.open-lab.net/blog/feed/ Terry Yin <![CDATA[Training a State-of-the-Art ImageNet-1K Visual Transformer Model using NVIDIA DGX SuperPOD]]> http://www.open-lab.net/blog/?p=48136 2023-06-12T09:34:30Z 2022-05-25T16:00:00Z Recent work has demonstrated that large transformer models can achieve or advance the SOTA in computer vision tasks such as semantic segmentation and object...]]> Recent work has demonstrated that large transformer models can achieve or advance the SOTA in computer vision tasks such as semantic segmentation and object...

Recent work has demonstrated that large transformer models can achieve or advance the SOTA in computer vision tasks such as semantic segmentation and object detection. However, unlike convolutional network models that can do it only with the standard public dataset, it takes a proprietary dataset that is magnitudes larger. The recent project VOLO (Vision Outlooker) from SEA AI Lab��

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