44 citations · 62 across the 4 of their papers we have counts for
Showing 2016Show all
3 papers · 1 filter
cs.CV2016★ 2 cited
The VQA-Machine: Learning How to Use Existing Vision Algorithms to Answer New Questions
Peng Wang, Qi Wu, Chunhua Shen +1
One of the most intriguing features of the Visual Question Answering (VQA) challenge is the unpredictability of the questions. Extracting the information required to answer them de…
cs.CV2016★ 16 cited
Multi-Label Image Classification with Regional Latent Semantic Dependencies
Junjie Zhang, Qi Wu, Chunhua Shen +2
Deep convolution neural networks (CNN) have demonstrated advanced performance on single-label image classification, and various progress also have been made to apply CNN methods on…
cs.CV2016★ 44 cited
Visual Question Answering: A Survey of Methods and Datasets
Qi Wu, Damien Teney, Peng Wang +3
Visual Question Answering (VQA) is a challenging task that has received increasing attention from both the computer vision and the natural language processing communities. Given an…