image和video的tokenizer使用的是MAGVIT-v2 Lijun Yu, Jose ́ Lezama, Nitesh B Gundavarapu, Luca Ver- sari, Kihyuk Sohn, David Minnen, Yong Cheng, Agrim Gupta, Xiuye Gu, Alexander G Hauptmann, et al. Language model beats diffusion–tokenizer is key to visual generation.arXiv preprint arX...
今天给大家推荐的论文和“文本生成图像”相关。 通用领域中的“基于文本生成图像”一直是一个开放的问题,它需要生成模型和跨模态理解。 KEG实验室在“CogView: Mastering Text-to-Image Generation via Transformers”一文中,提出了 CogView——基于60亿参数的文图预训练模型做出来的一个结果。文中还展示了各种下游任务...
ReadPaper是深圳学海云帆科技有限公司推出的专业论文阅读平台和学术交流社区,收录近2亿篇论文、近2.7亿位科研论文作者、近3万所高校及研究机构,包括nature、science、cell、pnas、pubmed、arxiv、acl、cvpr等知名期刊会议,涵盖了数学、物理、化学、材料、金融、计算机科
论文:《StructGPT: A General Framework for Large Language Model to Reason over Structured Data》 结构化数据以标准化… CLIP相关论文 戈上 欢迎交流 CLIP 一句话就是,基于图像和文本的对比学习策略,使用text encoder提取出文本的特征,使用image encoder提取出图像的特征,若文本和图片为正样本则使他们使对应的在...
3.1. Synthetic Data Generation 在本节中，我们概述了用于生成所提出的合成视觉概念 (SyViC) 合成 VL...
2) The largest improvement was achieved by retrieval augmented generation. The fact that these prompts allow our top runs to rank within the top two runs of BioASQ 11b demonstrate the power of using adequate prompts for Large Language Models in general, and GPT-3.5 in particular, for query-fo...
2) The largest improvement was achieved by retrieval augmented generation. The fact that these prompts allow our top runs to rank within the top two runs of BioASQ 11b demonstrate the power of using adequate prompts for Large Language Models in general, and GPT-3.5 in particular, for query-fo...
2) The largest improvement was achieved by retrieval augmented generation. The fact that these prompts allow our top runs to rank within the top two runs of BioASQ 11b demonstrate the power of using adequate prompts for Large Language Models in general, and GPT-3.5 in particular, for query-fo...
Alpha-CLIP in Image Variation Alpha-CLIP 可用于大多数使用 CLIP 图像编码器的图像变化模型。例如，...