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这部分的代码其实有点复杂,入口在consistory_run.py里面,在跑完第一阶段后,会进行判断是否进行perform_injection: out=story_pipeline(prompt=prompts,generator=g,latents=latents,attention_store_kwargs=default_attention_store_kwargs,extended_attn_kwargs=extended_attn_kwargs,share_queries=share_queries,query_...
使用可学习的 MLP 将图像嵌入投影到隐式文本嵌入中,之后将图像及其隐式文本嵌入作为输入给Diffusinon Unet用来提取特征,使用这些提取的特征和所给出的mask annotation,我们训练一个mask Generator来生成图像中所有的mask prediction, 然后和annotation算binary mask loss. 同时通过pooling得到mask embedding,使用来自CLIP的...
data ocr text fake dataset text-recognition synthetic training-set-generator Updated Jul 18, 2024 Python Tencent / Hunyuan3D-1 Star 3.3k Code Issues Pull requests Tencent Hunyuan3D-1.0: A Unified Framework for Text-to-3D and Image-to-3D Generation text generation 3d 3dgen Updated Jan...
providing object labels as an additional input to both the generator and discriminator. Conditional models have been studied extensively, and various approaches have been suggested to address it; however, many of them [12,36,38] focus on a single sentence to generate a single image. Other approa...
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●Stack-I GAN:文本编码器(text encoder),条件增强网络(Conditioning Augmentation network),生成网络(generator network),鉴别网络(discriminator network),嵌入压缩网络(embedding compressor network) ●Stack-II GAN:文本编码器,条件增强网络,生成网络,鉴别网络,嵌入压缩网络 ...
See, A., Liu, P.J., Manning, C.D.: Get to the point: summarization with pointer- generator networks. CoRR abs/1704.04368 (2017). http://arxiv.org/abs/1704. 04368 24. Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. arXiv preprint ...
Therefore we modify the cross-entropy loss function slightly by requiring it to give an output of 0.9 when sentence-image pair is correct and 0.1 otherwise. This technique has been called “Level-Smoothing”. The losses used for the generator network include the obvious binary cross entropy loss...