Contrastive Language-Image Pre-training(CLIP)[1] 技术由 OpenAI 团队在 ICML 2021 提出,这是一个非常符合 Open AI 大力出奇迹的工作风格。根据谢赛宁教授在智源大会上的分享 [2],目前大多数多模态大模型都采用了 CLIP 预训练的视觉编码器,足见 CLIP 的广泛影响力。本篇博文对 CLIP 的核心技术原理进行梳理和...
简介:Contrastive Language-Image Pretraining(CLIP)是一种基于对比学习的多模态模型,它通过对比语言和图像信息进行预训练,从而在各种图像和文本对上训练神经网络。本文将深入探讨CLIP的基本原理、主要特点以及实际应用。 即刻调用文心一言能力 开通百度智能云千帆大模型平台服务自动获取1000000+免费tokens 立即体验 CLIP(Contr...
文章信息标题:Learning Transferable Visual Models From Natural Language Supervision也被叫做 CLIP ( Contrastive Language Image Pretraining)作者:OpenAI 发表:ICML 2021 文章地址: Learning Transferabl…
图数据上的Deep Graph Infomax[3]:最大化节点的局部表示和 k-跳邻域内的上下文表示之间的互信息。 多模态数据上的Contrastive Language-Image Pre-training (CLIP) [4]:最大化图像和相应文本之间的互信息。在使用来自 Internet 的大规模图像-文本对数据集进行预训练后,CLIP在下游任务上具有了非常不错的零样本学习...
Contrastive Language-Image Pre-training (CLIP), consisting of a simplified version of ConVIRT trained from scratch, is an efficient method of image representation learning from natural language supervision. , CLIP jointly trains an image encoder and a text encoder to predict the correct pairings of ...
SUPERVISION EXISTS EVERYWHERE: A DATA EFFICIENT CONTRASTIVE LANGUAGE-IMAGE PRE-TRAINING PARADIGM 近年来,大规模对比语言图像预训练(CLIP)因其令人印象深刻的zero-shot识别能力和良好的下游任务转移能力而引起了前所未有的关注。然而,CLIP非常需要数据,需要400M图像-文本对进行预训练。这项工作提出了一种新的训练范式...
contrastive languageimage pre-training Contrastive Language-Image Pre-training (CLIP) is a significant advancement in the field of artificial intelligence, particularly in the area of multimodal learning, where models learn to understand and relate information across different modalities, such as text and...
多模态数据上的Contrastive Language-Image Pre-training (CLIP)[4]:最大化图像和相应文本之间的互信息。在使用来自 Internet 的大规模图像-文本对数据集进行预训练后,CLIP在下游任务上具有了非常不错的零样本学习能力 相对位置预测 Relative Position Prediction ...
CLIP (Contrastive Language-Image Pre-Training) is a neural network trained on a variety of (image, text) pairs. It can be instructed in natural language to predict the most relevant text snippet, given an image, without directly optimizing for the task, similarly to the zero-shot capabilities...
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