One important aspect of captioning is the notion of attention: how to decide what to describe and in which order. Inspired by the successes in text analysis and translation, previous works have proposed the transformer architecture for image captioning. However, the structure between the semantic ...
Image Captioning through Image Transformer This repository includes the implementation forImage Captioning through Image Transformer(to appear in ACCV 2020). This repo is not completely. Requirements Python 3.6 Java 1.8.0 PyTorch 1.0 cider (already been added as a submodule) ...
1 图像字幕是什么图像字幕(Image Captioning)是计算机视觉的主要目标之一,旨在自动生成图像的自然描述。 它不仅需要识别图像中的显著对象,理解它们的相互作用,还需要使用自然语言来表达它们,这使得它非常具…
1. 论文和代码地址 Variational Transformer: A Framework Beyond the Trade-off between Accuracy and Diversity for Image Captioning 论文地址：https://arxiv.org/abs/2205.14458[1]代码地址：未开源 2. Motivation 在图像字幕中，生成多样化和准确的字幕是一项具有挑战性的任务，尽管付出了最大努力，但尚未完成。
Transformer网络写起来比CNN要复杂一些,现在做Image Captioning,Transformer based 的模型在这个领域展现了优秀的成绩,花了点时间弄清transformer网络的细节。 代码来自:ruotianluo/ImageCaptioning.pytorch 网络是原版的transformer[1],为Image Captioning作了微调,数据是MSCOCO Image Captioning[2]. ...
Variational Transformer: A Framework Beyond the Trade-off between Accuracy and Diversity for Image Captioning 论文地址:https://arxiv.org/abs/2205.14458[1] 代码地址:未开源 2. Motivation 在图像字幕中,生成多样化和准确的字幕是一项具有挑战性的任务,尽管付出了最大努力,但尚未完成。虽然目前的captioning最新...
数据处理部分主要有两个模块,captioning(用于生成给定图像的文字描述)和filtering(用于去除噪声图像文本对),两者均以MED进行初始化,并在数据集COCO上微调。最后合并两者的数据集,以新的数据集预训练一个新的模型。 import requests from PIL import Image from transformers import BlipProcessor, BlipForConditionalGenerati...
用于Image Captioning的变分Transformer模型! 【摘要】 在生成自然且语义正确的字幕时,准确度和多样性是两个基本的可度量表现。目前已经做出了许多努力,以加强其中一个,而另一个由于权衡差距而衰退。然而,妥协并没有取得进展。衰减的多样性使captioner成为一个重复机器,衰减的准确性使其成为一个假的描述机器。在这项...
Image Captioning Through Image Transformer Automatic captioning of images is a task that combines the challenges of image analysis and text generation. One important aspect of captioning is the notion of attention: how to decide what to describe and in which order. Inspired by th... S He,W Li...
Meshed-Memory Transformer for Image Captioning 一句话复盘:我们提出了对self-attention增加记忆槽以引入高层信息的特征向量结构,和基于两重cross-attention作权重的encoder和decoder全连接结构。 还是边看边写的,这文章文法很舒服 科普 一些名词解释及其关系