Incorporating external knowledge to Visual Question Answering (VQA) has become a vital practical need. Existing methods mostly adopt pipeline approaches with different components for knowledge matching and extraction, feature learning, etc.However, such pipeline approaches suffer when some component does ...
Zero-Shot Visual Question Answering 17 Nov 2016 · Damien Teney, Anton Van Den Hengel · Edit social preview Part of the appeal of Visual Question Answering (VQA) is its promise to answer new questions about previously unseen images. Most current methods demand training questions that illustrate...
关于Visual Question Answering Eval 文章目录 一些重要的链接 VQA 1.0 VQA 2.0 VQA-CP 一些重要的链接 vqa_eval官方API链接:http://www.visualqa.org/evaluation.html VQA 官网的链接:https://visualqa.org/ VQA CP数据集及论文链接:https://www.cc.gatech.edu/~aagrawal307/vqa-cp/ VQA 1...论文总结之...
[CVPR 2024 CVinW] This is the official implementation of the paper "Multi-Agent VQA: Exploring Multi-Agent Foundation Models in Zero-Shot Visual Question Answering" in Pytorch. Key idea: What if a large foundation model fails at VQA? Shall we finetune it on our VQA dataset or object detec...
PNP-VQA : Plug-and-Play VQA: Zero-shot VQA by Conjoining Large Pre-trained Models with Zero Training Yiliiiii import * as end2end 1 人赞同了该文章 目录 收起 Related Works Method Matching Image Patches and Questions Informative Image Captioning Answering the Question ExperimentPlug...
and Lei Zhang.Bottom-up and top-down attention for image captioning and visual question answering....
Recently, zero shot learning has been gaining increasing attention for a number of other computer vision tasks such as im- age tagging [25, 53], visual question answering [29, 33, 45] etc. To the best of our knowledge, the zero-shot framework has not been previously explored in the...
Inspired by the recent success of training-free approaches for image captioning, we propose ZS-A2T, a zero-shot framework that translates the transformer attention of a given model into natural language without requiring any training. We consider this in the context of Visual Question Answering (...
This task present the results of Zeroshot Question Answer results on TGIF-QA dataset for LLM powered Video Conversational Models.
State-of-the-art methods for zero-shot visual recognition formulate learning as a joint embedding problem of images and side information. In these formulat... S Reed,Z Akata,H Lee,... - IEEE 被引量: 178发表: 2016年 Video Retrieval Using High Level Features: Exploiting Query Matching and...