On the General Value of Evidence, and Bilingual Scene-Text Visual Question Answering

CVPR 2020 • Xinyu Wang • Yuliang Liu • Chunhua Shen • Chun Chet Ng • Canjie Luo • Lianwen Jin • Chee Seng Chan • Anton Van Den Hengel • Liangwei Wang

Visual Question Answering (VQA) methods have made incredible progress, but suffer from a failure to generalize. This is visible in the fact that they are vulnerable to learning coincidental correlations in the data rather than deeper relations between image content and ideas expressed in language... (read more)

PDF Abstract CVPR 2020 PDF CVPR 2020 Abstract

Results from the Paper

Edit

Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

METHOD	TYPE
🤖 No Methods Found	Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet

On the General Value of Evidence, and Bilingual Scene-Text Visual Question Answering

Code

Add Remove Mark official

Tasks

Add Remove

Results from the Paper

Edit

Methods used in the Paper

Add Remove

On the General Value of Evidence, and Bilingual Scene-Text Visual Question Answering

Code Edit Add Remove Mark official

Tasks Edit Add Remove

Results from the Paper Edit

Methods used in the Paper Edit Add Remove

Code

Add Remove Mark official

Tasks

Add Remove

Results from the Paper

Edit

Methods used in the Paper

Add Remove