在作者的实验中,作者使用一个通用的 Prompt 如 "face"作为,但可以替换为一个更细粒度的 Prompt 。 3.2.2. CLIP-conditioned discriminator loss 为了在域自适应过程中保持样本质量,作者引入了一种对抗损失 ,该损失依赖于CLIP嵌入的判别器。这种判别器借鉴了(Kang等人,2023年;Kumari等人,2022年)的设计,使用了一个...
而Discriminator则是Patch-based。总体来说这样可以支持大小不同的图片,同时也能提高计算效率。在效果上,实验发现合理的patch-size不会损失效果。这里我对泛化稍微有点存疑,如果看不到全局信息,在少数情况是不容易“辨明真伪”的。 在loss的设计上,文中除了cGAN的loss,还加入了L1 loss,并且进行了充分实验。单纯用L1...
在噪声的作用上，Pix2Pix提供了一种更直观的理解，即它帮助生成器捕捉到输入图像的细节信息，这对于图像转换至关重要。实验结果也证实了在Pix2Pix模型中，使用U-Net结构，尤其是带有残差连接的结构，对于捕捉图像细节信息至关重要。Discriminator部分采用了Patch-based设计，这不仅支持不同大小的图像输入，而...
Get the odataType property: The discriminator for derived types. Overrides: UtcClipTime.odataType() Returns: the odataType value.time public OffsetDateTime time() Get the time property: The time position on the timeline of the input media based on Utc time. Returns: the time value.to...
题目:Image-based CLIP-Guided Essence Transfer 题目:CLIPasso: Semantically-Aware Object Sketching 题目:CLIP-GEN: Language-Free Training of a Text-to-Image Generator with CLIP 题目:CLIPstyler: Image Style Transfer with a Single Text Condition ...
Polymorphic discriminator, which specifies the different types this object can be TypeScript Copier odataType: "#Microsoft.Media.UtcClipTime" Property Value "#Microsoft.Media.UtcClipTime" time The time position on the timeline of the input media based on Utc time. TypeScript Copier time: ...
Get the odataType property: The discriminator for derived types. Overrides: UtcClipTime.odataType() Returns: the odataType value.time public OffsetDateTime time() Get the time property: The time position on the timeline of the input media based on Utc time. Returns: the time value.to...
Polymorphic discriminator, which specifies the different types this object can be TypeScript Copy odataType: "#Microsoft.Media.UtcClipTime" Property Value "#Microsoft.Media.UtcClipTime" time The time position on the timeline of the input media based on Utc time. TypeScript Copy time: Date...
Texture Generator:We use StyleGAN2 generator with adaptive discriminatorStyleGAN-ADAto generate UV maps due to its faster convergence. To train, run the following command: python -m trainer.trainer_stylegan.train_stylegan_ada_texture_patch Text-guided Manipulation:We perform text-guided manipulation on...
A new approach for audio classification and segmentation using Gabor wavelets and Fisher Linear Discriminator Rapid increase in the amount of audio data demands an efficient method to automatically segment or classify audio stream based on its content. In this pape... RS Lin,LH Chen - 《Internati...