作者证明了从头开始训练的 ConVIRT 的简化版本,称之为CLIP,用于对比语言-图像预训练(Contrastive Language-Image Pre-training),是一种从自然语言监督中学习的有效且可扩展的方法。作者发现 CLIP 在预训练期间学会了执行一系列广泛的任务,包括 OCR、地理定位和动作识别,并且优于公开可用的最佳 ImageNet 模型,同时计算效...
也被叫做 CLIP (Contrastive Language Image Pretraining) 作者:OpenAI 发表:ICML 2021 文章地址:Learning Transferable Visual Models From Natural Language Supervision 代码地址:github.com/OpenAI/CLIP 视频解读:CLIP 论文逐段精读【论文精读】_哔哩哔哩_bilibili 1 标题、摘要、结论、简介重点 一句话总结: 文章提出...
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...
temporal structure of the sequence of frames as well as the sequence model of the generated sentences, i.e. a language model. We evaluate several variants of our model that exploit different visual features on a standard set of YouTube videos and two movie description datasets (M-VAD and ...
Zeng, Yihan, et al. "CLIP2: Contrastive Language-Image-Point Pretraining from Real-World Point Cloud Data." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2023. 作者单位:华为诺亚方舟实验室 香港科技大学 香港中文大学 中山大学 ...
CLIP(Contrastive Language-Image Pretraining)是一种深度学习模型,它结合了语言和图像信息,通过对比学习的方式进行预训练。这种模型的目标是学习图像和文本之间的内在联系,以便能够理解和生成各种语言的文本描述。CLIP主要通过对比语言和图像的表示学习来实现其目标。具体来说,CLIP包含两个主要部分:文本编码器和图像编码器...
内容提示: PMC-CLIP: Contrastive Language-ImagePre-training using Biomedical DocumentsWeixiong Lin 1,∗ , Ziheng Zhao 1,∗ , Xiaoman Zhang 1,2 , Chaoyi Wu 1,2 , YaZhang 1,2 , Yanfeng Wang 1,2 , and Weidi Xie 1,2,†1Cooperative Medianet Innovation Center, Shanghai Jiao Tong ...
code : https://github.com/taesungp/contrastive-unpaired-translation 文章目录 背景梳理 主要贡献 背景梳理 本文处理的任务是经典的非成对的自然图像转化问题(Unpair Pix2Pix)。训练数据中不同域的图像并不具有成对的匹配性(如fig1所示)。该方面最为经典的工作...
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...
Natural Language Supervision for Visual Models The idea is to learn more about the image using supervision from Natural Language Processing. However, its hard to find high quality large datasets that have crowd-labeled images with text. The paper introduces a new dataset of 400 million...