16 citations · 29 across the 2 of their papers we have counts for
3 papers
cs.CV2018★ 16 cited
VQA-E: Explaining, Elaborating, and Enhancing Your Answers for Visual Questions
Qing Li, Qingyi Tao, Shafiq Joty +2
Most existing works in visual question answering (VQA) are dedicated to improving the accuracy of predicted answers, while disregarding the explanations. We argue that the explanat…
cs.CV2018
VizWiz Grand Challenge: Answering Visual Questions from Blind People
Danna Gurari, Qing Li, Abigale J. Stangl +5
The study of algorithms to automatically answer visual questions currently is motivated by visual question answering (VQA) datasets constructed in artificial VQA settings. We propo…
cs.CV2018★ 13 cited
Tell-and-Answer: Towards Explainable Visual Question Answering using Attributes and Captions
Qing Li, Jianlong Fu, Dongfei Yu +2
Visual Question Answering (VQA) has attracted attention from both computer vision and natural language processing communities. Most existing approaches adopt the pipeline of repres…