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# swinv2-tiny-patch4
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# swinv2-tiny-patch4-window16-256
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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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{
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"do_normalize": true,
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"do_resize": true,
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"feature_extractor_type": "ViTFeatureExtractor",
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"image_mean": [
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0.485,
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0.456,
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0.406
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],
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"image_std": [
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0.229,
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0.224,
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0.225
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],
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"resample": 3,
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"size": 256
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}
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