方法 1. T-ICL with additional image-to-text models(T-ICL-Img):为了将大型语言模型(LLMs)从自然语言处理(NLP)任务适配到多模态任务,一个常见的策略是将相应的图像转换成文本描述。 2. Visual-text interleaved in-context learning(VT-ICL):尽管 T-ICL-Img 取得了显著的效果,但在将视觉输入转换为文本描述...
并且,它将三个任务所需的text encoder和text decoder进行了合并,相同的结构层之间共享参数,比起ALBEF的模型结构简洁很多,模态交互也更加充分。 BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models (ICML 2023) 模型介绍:随着大语言模型LLM的兴起,各种与NLP...
其在text-to-image diffusion models上的应用,证明了text-to-image diffusion models中,文本编码的能力并不一定需要CLIP中所携带的image-text alignment,即纯language models也可以用于编码文本信息。 T5的技术流程图 前文说到,LLMs的上下文学习能力决定了其对文本信息的强大表征能力,结合我们在T5-XXL中得出的结论,不...
CoMat, a groundbreaking method, addresses the challenge of aligning text-to-image diffusion models with the creation of high-fidelity and diverse images. This paper introduces CoMat, an end-to-end fine-tuning strategy for diffusion models that incorporates image-to-text concept matching....
Visual instruction tuning is a technique that helps large language models (LLMs) understand and follow instructions based on visual inputs. This approach connects language and vision, enabling AI systems to understand and respond to human instructions that involve both text and images. For example,...
Imagen: Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding 时间:22/05 机构:Google TL;DR 发现使用LLM(T5)可以作为text2image任务的text encoder,并且提升LLM模型size相对于提升image DM模型size性价比更高,生成的图像保真度更高,内容也更符合文本的描述。在COCO上FID score达到7.27。另外...
.Build();// Gets the ImageToText Servicevarservice =this._kernel.GetRequiredService<IImageToTextService>();// Get the binary content of a JPEG image:varimageBinary = File.ReadAllBytes("path/to/file.jpg");// Prepare the image to be sent to the LLMvarimageContent =newImageContent(imageBi...
VideoTuna: VideoTuna is the first repo that integrates multiple AI video generation models for text-to-video, image-to-video, text-to-image generation. ConsisID: An identity-preserving text-to-video generation model, bases on CogVideoX-5B, which keep the face consistent in the generated video...
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We developed a cyclical generation process that begins with generating initial narratives using either VLMs or large language models (LLMs), which are then visualized by a T2I model. This initiates a feedback loop where each generated image inspires a new narrative, creating a rich sequence of...