In this paper, we propose BLIP, a new VLP framework which transfers flexibly to both vision-language understanding and generation tasks. BLIP effectively utilizes the noisy web data by bootstrapping the captions, where a captioner generates synthetic …

Announcement: BLIP is now officially integrated into LAVIS - a one-stop library for language-and-vision research and applications! This is the PyTorch code of the BLIP paper [blog]. The code has been tested on PyTorch 1.10. To install the dependencies, run. Catalog: Run our interactive demo using Colab notebook (no GPU needed).

2023年12月25日 · blip是一种基于vlp的新框架，统一并灵活地应用于视觉-语言理解任务和生成任务。blip通过引导生成图像描述来有效利用噪声网络数据，从而在多个下游任务上取得了最先进的性能。

2022年1月28日 · In this paper, we propose BLIP, a new VLP framework which transfers flexibly to both vision-language understanding and generation tasks. BLIP effectively utilizes the noisy web data by bootstrapping the captions, where a captioner generates synthetic captions and a filter removes the noisy ones.

In this paper, we propose BLIP, a new VLP framework which transfers flexibly to both vision-language understanding and generation tasks. BLIP effectively utilizes the noisy web data by bootstrapping the captions, where a captioner generates synthetic …

BLIP (Bootstrapping Language-Image Pretraining)是 salesforce 在2022年提出的多模态框架，是理解和生成的统一，引入了跨模态的编码器和解码器，实现了跨模态信息流动，在多项视觉和语言任务取得SOTA。 在AIGC中通常用来给图像生成prompt，好的prompt对交叉注意力的微调非常关键，例如ControlNet中的Automatic Prompt就是BLIP生成的。 为什么叫Bootstrapping，是因为训练数据来自网络图文对，包含大量噪声，所以 增加了一个在线数据打标签和清理的任务，把处 …

BLIP-2, OPT-2.7b, pre-trained only BLIP-2 model, leveraging OPT-2.7b (a large language model with 2.7 billion parameters). It was introduced in the paper BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models by Li et al. and first released in this repository .

BLIP 的模型结构看上图，会涉及4个结构（Image-grounded Text Decoder 、 Image-grounded Text Encoder 、Image-grounded Text Decoder）和3种损失（ITC 、 ITM 、LM）。 Image Encoder (ViT) ：首先进行图像特征的提取； Text Encoder (BERT) ：这是一个标准的 BERT，提取文本的特征； Image-grounded Text Encoder (变种 BERT)：在标准 BERT 的结构里，于 Bi Self-Att 和 Feed Forward 之间插入 Cross Attention 模块，以引入视觉特征；

2023年6月4日 · 本文为《深入浅出多模态》系列多模态经典模型blip，首先从整体介绍多模态模型发展，对其中经典blip模型进行详述，从具体论文、数据集、代码、模型结构、结果等角度分析，本专栏适合从事多模态小白及爱好者学习，欢迎大家关注，如有侵权请联系删除！

2023年1月30日 · This paper proposes BLIP-2, a generic and efficient pre-training strategy that bootstraps vision-language pre-training from off-the-shelf frozen pre-trained image encoders and frozen large language models. BLIP-2 bridges the modality gap with a lightweight Querying Transformer, which is pre-trained in two stages.