Comments (1)
Royalvice
commented on May 9, 2024
预测噪声的方法，在参数量比较大，T取1000以上效果是可以的。本文预测x_0的办法，T取的是200。文中也写了，直接预测x_0对于 channel-wise concatenation conditioning 可以通过条件进行预测。而不是只能通过x_t进行预测。这样会使得扩散模型在采样的前几步就采样出很高质量的样本。但牺牲了生成多样性。
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Related Issues (20)
- 关于预训练模型 HOT 2
- 推理时长？ HOT 4
- 关于图片的输入大小 HOT 3
- 请教一下训练时长 HOT 7
- License HOT 2
- License
- Inference on variable image size HOT 2
- 去印章的预训练模型 HOT 3
- Code for the synthetic dataset HOT 2
- watermark removal HOT 2
- 训练集规模以及学习率 HOT 2
- 有关梯度回传的问题 HOT 2
- Questions about data HOT 1
- 增加有更多噪声的数据集 HOT 5
- About config.PRE_ORI HOT 5
- 图片降噪问题 HOT 6
- Model deployment issue HOT 1
- 您好，火眼OCR APP的redirect_uri参数错误
- 您好，看到文档里没有提及印章去除模型的推理，若想使用该功能该如何修改源代码
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