activity
20162019
most citedVisual Question Answering: A Survey of Methods and Datasets

44 citations · 63 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV20191 cited

You Only Look & Listen Once: Towards Fast and Accurate Visual Grounding

Chaorui Deng, Qi Wu, Guanghui Xu +4

Visual Grounding (VG) aims to locate the most relevant region in an image, based on a flexible natural language query but not a pre-defined label, thus it can be a more useful tech…

cs.CV2018

Neighbourhood Watch: Referring Expression Comprehension via Language-guided Graph Attention Networks

Peng Wang, Qi Wu, Jiewei Cao +3

The task in referring expression comprehension is to localise the object instance in an image described by a referring expression phrased in natural language. As a language-to-visi…

cs.CV20162 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.CV201616 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.CV201644 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…