最直观的办法是让VLMs先生成图像的文本描述,然后利用扩散模型(Diffusion Model)将这些描述转化为图像。然而,如果VLMs与扩散模型之间没有经过联合训练,生成效果可能会受到很大限制。 近一年也有不少相关工作。基于输出图像的形式,大致可以分为两类。 【方式一:输出连续embedding】 相关工作有EMU2(2312), DreamLLM(...
《Meta最新Vision-Language Model研究综述(一)——VLMs的分类》在开头部分提到有多种训练VLM的方法。一些方法使用简单的对比训练标准,另一些使用掩码策略来预测缺失的文本或图像块,还有一些模型使用生成范式,如自回归或扩散。此外,还可以利用预训练的视觉或文本主干网络,如Llama或GPT。在这种情况下,构建VLM模型只需学习...
Lingpeng Kong 老师关注于探索新一代(Text Diffusion Model, DiffSeq)/更高效(Linear Attention)的语言...
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Here, to address this challenge and improve the performance of cardiac imaging models, we developed EchoCLIP, a vision–language foundation model for echocardiography, that learns the relationship between cardiac ultrasound images and the interpretations of expert cardiologists across a wide range of ...
Vision-Language Model Transfer Learning Methods Transfer with Prompt Tuning Transfer with Text Prompt Tuning Transfer with Visual Prompt Tuning Transfer with Text and Visual Prompt Tuning Transfer with Feature Adapter Transfer with Other Methods Vision-Language Model Knowledge Distillation Methods Knowledg...
本文受到前人对抗训练方法的启发,将其用到 vision-language model 的预训练中。 该方法的核心部分有如下三点: 对抗的预训练和微调机制; 在映射空间添加干扰; 增强的对抗训练方法; 1. 对抗预训练与微调: Pre-training: 给定预训练数据集,包含 image-text pairs,训练的目标就是在这个大型数据集上学习一些与任务无...
Vision-Language Model (VLM) Tuning:Recent years have witnessed the prosperity of research in VLMs, e.g., CLIP [46], ALIGN [25], CoCa [70], Florence [73], BLIP [31], CLIPPO [54], and Flamingo [1]. These models are pre-trained on vast amounts of images and texts, achieving a...
Microsoft will release the VinVL model and the source code to the public. Please refer to the research paper and GitHub repository. In addition, VinVL is being integrated into the Azure Cognitive Services, powering a wide range of multimodal scenarios (such as Seeing AI, Image Captioni...
To address this issue, in this paper, we develop a new method called cross-model concept learning and inference (CCLI). Using the powerful text-image correlation capability of CLIP, our method automatically learns a large set of distinctive visual concepts from images using a set of semantic ...