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# swinv2-tiny-patch4
# swinv2-tiny-patch4-window16-256
2021年获得 ICCV 最佳论文奖的 Swin Transformer通过在广泛的视觉问题上证明 Transformer 架构的有效性加速了计算机视觉领域基本模型架构的变革。2021年末微软亚洲研究院的研究员们又进一步提出了 Swin Transformer v2.0 版本,新版本训练了迄今为止最大的稠密视觉模型,并在多个主流视觉任务上大大刷新了记录,相关论文也已被 CVPR 2022 接收。

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{
"do_normalize": true,
"do_resize": true,
"feature_extractor_type": "ViTFeatureExtractor",
"image_mean": [
0.485,
0.456,
0.406
],
"image_std": [
0.229,
0.224,
0.225
],
"resample": 3,
"size": 256
}

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