模型生成字幕时,在文本前添加 “a picture of” 作为初始输入,通过语言建模损失进行训练,生成过程中使用束搜索(beam search),评估指标采用 CIDEr(Consensus - based Image Description Evaluation)和 SPICE(Semantic Propositional Image Caption Evaluation)等,用于衡量生成字幕的质量和与图像内容的相关性。 视觉问答任务:...
通过在隐空间对跨模态特征对齐的方式来获得image-text alignment。但是，值得注意的是，CLIP训练中采用的...
写在前面 在本文中,作者总结了针对视频和语言理解评估(VALUE)挑战的方法。作者提出了一种CLIP增强方法,将图像文本预训练知识融入到下游视频文本任务中。结合其他几项改进的设计,本文的方法在VALUE基准上的Meta Ave得分相比于之前的SOTA水平提高了2.4%。 1. 论文和代码地址 A CLIP-Enhanced Method for Video-Language ...
它将被用于生成支持集中的图像部分。 3.1.2. Image Generation 作者使用了文本到图像模型——稳定扩散(_Stable Diffusion_)来实现图像生成。对于第k类,作者随机抽取其基于描述的提示(_caption-based prompt_) 作为稳定扩散(_Stable Diffusion_)的输入,生成一系列张图像。由于这个提示是从中随机选择的,当时会出现提示...
For video captioning, "pre-training and fine-tuning" has become a de facto paradigm, where ImageNet Pre-training (INP) is usually used to encode the video content, then a task-oriented network is fine-tuned from scratch to cope with caption generation. This paper first investigates the ...
部分:一个单模态解码器unimodal text decoder和一个多模态解码器multimodal text decoder,然后增加一个cls token在文本的最后(CoCa相比CLIP额外增加了一个Multimodel Text Encoder来生成caption,如此,它训练的损失包含了CLIP的对比损失和captioing的交叉熵损失,所以CoCa不仅可以像CLIP那样进行多模态检索,也可以用于caption...
This allows them to expand on caption information during training, increasing the efficiency of the learning process. In this paper, we propose LLM2CLIP, a novel approach that embraces the power of LLMs to unlock CLIP’s potential. By fine-tuning the LLM in the caption ...
最近NLP领域提出了Prompt新范式,企图革新原先的Fine-tuning方法,而在CV领域中,Prompt其实可以理解为图像label的设计,从这个角度看,Prompt(预测文本中mask的字符,类似完形填空)其实是介于Image caption(迭代预测出每一个字符)和one-hot label(one-hot可以认...
which have demonstrated state-of-the-art performance in image caption generation. Our LSTM model is trained on video-sentence pairs and learns to associate a sequence of video frames to a sequence of words in order to generate a description of the event in the video clip. Our model naturally...
To bridge this gap, in this paper, we propose a CLIP4Caption framework that improves video captioning based on a CLIP-enhanced video-text matching network (VTM). This framework is taking full advantage of the information from both vision and language and enforcing the model to learn strongly ...