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# DenoisingGait (CVPR'25)
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### For `00-DenoisingFea_96x48.pkl`
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For the data, we preserved the diffusion features and fed them into the subsequent recognition network.
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In our initial configuration, we adopted **Stable Diffusion v1.5**, set the inference loop to **1**, and fixed \( t = 700 \) to extract the denoised features.
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The input resolution was \((3, 768, 384)\) \((C, H, W)\), and the resulting feature map had the shape \((4, 96, 48)\).
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These features, together with the silhouette inputs, were then passed to the downstream **DenoisingGait** network.
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```
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data_for_DenoisingGait
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├── 0000 # Identity
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│ ├── 00-nm # sequence_number - sequence_covariates
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│ │ ├── 000 # viewpoint_angle
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│ │ │ ├── 00-DenoisingFea_96x48.pkl
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│ │ │ └── 01-Sils_96x48.pkl
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......
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......
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......
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......
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```
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