最近NLP领域提出了Prompt范新式,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可以认为是prompt的特例,单字符通过text encoder成one-hot)之间的任务。
This research is also motivated by recent successes of prompt learning in many downstream multi-modal tasks, including image-text retrieval and vision question answering. In this work, a semantic prompt is introduced and aggregated with visual features for more accurate caption prediction under the ...
通常来讲，一般的跨模态表示首先以自监督的方式在大规模 image-caption 数据上进行预训练，然后进行微调以适应下游任务。VL-PTM 这种先预训练再微调的范式使得很多跨模态任务的 SOTA 被不断刷新。但尽管如此，清华大学、新加坡国立大学的研究者还是注意到，VL-PTM 的预训练与微调的 objective form 之间存在显著差异。...
下游任务&prompt设计:7个多模态任务的benchmark,包括VQA,GQA,COCO Caption, NLVR2,VCR, MMT,REF-COCOg。 如上图所示,在所有任务的输入加上文本前缀(e.g.”vqa:”, “image text match:”)用于区分不同任务,输出都统一成text label的形式。对于visual grounding任务,图片特征输入时就加了类似<vis_n>的region...
The optimal prompt format for a VLM depends on the model’s architecture and the nature of the caption pairs used during training. Different training datasets influence how a VLM interprets the prompt. Conclusion This post walked through how VLMs have evolved from supporting only single...
Learning Object-Language Alignments for Open-Vocabulary Object Detection 提出原因:现有的大多数开放词汇表对象检测工作(全部或部分依赖于接ground-truth数据,然而,这是不可扩展的,因为注释接地数据甚至比注释对象检测数据更昂贵。为了降低开放词汇表对象检测的注释成本,最近的一些工作转而通过裁剪图像从面向分类的模型中...
[linest] [Task Identifier][/INST] 其中[INST]和[/INST]分别代表用户角色和聊天助手。在训练期间,将<Image Feature>替换为视觉嵌入,将<Prompt Feature>替换为文本提示嵌入。根据具体情况替换_[Task Identifier](例如,[vqa]和[caption]_),使作者的模型更擅长理解多个任务。
This directional decomposition is crucial for capturing edges and linear features across various directions and scales, which is a capability often lacking in traditional CNNs. The DFB operation enhances the representation of directional information within the image. The high-pass subbands undergo this ...
It lets you input an image, which it then turns into a prompt you can use to generate more images. You can also use the prompt as an image caption or alt text. Here, we’ve put together five of the best image to prompt generators and tell you how to choose the right one for ...
multi-modal tasks, including image-text retrieval and vision question answering. In this work, a semantic prompt is introduced and aggregated with visual features for more accurate caption prediction under the adversarial learning framework. In addition, a metric prompt is designed to select high-...