Kanan. Visual question answering: Datasets, algorithms, and future challenges. arXiv preprint arXiv:1610.01465, 2016. 1, 2Kafle, K., Kanan, C.: Visual question answering: Datasets, algo- rithms, and future challenges. arXiv preprint arXiv:1610.01465 (2016) 2...
Lastly, it can be concluded that there are no datasets or research for VQA in Arabic, so far. The following section describes an automatic generation procedure for the first VQA dataset in Arabic. Section 4 proposes the first Arabic-VQA system, where several algorithms of text pre-processing ...
Visual Question Answering: Datasets, Algorithms, and Future Challenges心得体会 Visual7W用了Flickr100M数据集做了补充。一个好的数据集需要有图像,问题,以及现实世界中的概念。 (1)DAQUAR(DAtasetforQUestionAnsweringon...准确性。 (1)VQA中的视觉和语言: 图像和文本是VQA中两个截然不同的数据流,根据一些简化...
(2016a). Answer-type prediction for visual question answering. In CVPR. Kafle, K., & Kanan, C. (2016b). Visual question answering: Datasets, algorithms, and future challenges. arXiv preprint arXiv:1610.01465. Kafle, K., & Kanan, C. (2017). An analysis of visual question answering ...
In this section, we are going to describe some common algorithms that perform VQA. Pix2Struct Pix2Struct is a deep learning model that tackles visual question answering (VQA) by leveraging the power of image-to-text translation. Pix2Struct is an encoder-decoder transformer model. The encoder ...
Visual question answering: Datasets, algorithms, and future challenges- Kushal Kafle et al,CVIU 2017. Visual question answering: A survey of methods and datasets- Qi Wu et al,CVIU 2017. 2019 Combining Multiple Cues for Visual Madlibs Question Answering- Tatiana Tommasi et al,IJCV 2019. [code]...
Kushal Kafle, and Christopher Kanan.Visual question answering: Datasets, algorithms, and future challenges.Computer Vision and Image Understanding (2017).[Paper] Qi Wu, Damien Teney, Peng Wang, Chunhua Shen, Anthony Dick, and Anton van den Hengel.Visual question answering: A survey of methods an...
We sus- pect algorithms will be able to take advantage of these dif- ferences to learn predictive cues for grounding answers. We also observe that the characteristics of answer groundings for the same question are considerably different across the different datasets....
IntJComputVis DOI10.1007/s11263-016-0966-6 VQA:VisualQuestionAnswering .visualqa AishwaryaAgrawal 1 ·JiasenLu 1 ·StanislawAntol 1 ·MargaretMitchell 2 · C.LawrenceZitnick 3 ·DeviParikh 4 ·DhruvBatra 4 Received:4April2016/Accepted:7October2016 ©SpringerScience+BusinessMediaNewYork2016 Abstract...
In visual question answering (VQA), an algorithm must answer text-based questions about images. While multiple datasets for VQA have been created since late 2014, they all have flaws in both their content and the way algorithms are evalu... WL Chao,H Hu,S Fei - Conference of the North ...