research
∙
01/15/2021
Reasoning over Vision and Language: Exploring the Benefits of Supplemental Knowledge
The limits of applicability of vision-and-language models are defined by...
share
research
∙
05/04/2020
Visual Question Answering with Prior Class Semantics
We present a novel mechanism to embed prior knowledge in a model for vis...
research
∙
09/13/2017
Joint Learning of Set Cardinality and State Distribution
We present a novel approach for learning to predict sets using deep lear...
research
∙
07/17/2017
Visual Question Answering with Memory-Augmented Networks
This paper exploits a memory-augmented neural network to predict accurat...
research
∙
06/17/2017
Bayesian Conditional Generative Adverserial Networks
Traditional GANs use a deterministic generator function (typically a neu...
research
∙
11/28/2016
DeepSetNet: Predicting Sets with Deep Neural Networks
This paper addresses the task of set prediction using deep learning. Thi...
research
∙
06/17/2016
FVQA: Fact-based Visual Question Answering
Visual Question Answering (VQA) has attracted a lot of attention in both...
research
∙
04/13/2016
Online Multi-Target Tracking Using Recurrent Neural Networks
We present a novel approach to online multi-target tracking based on rec...
research
∙
03/09/2016
Image Captioning and Visual Question Answering Based on Attributes and External Knowledge
Much recent progress in Vision-to-Language problems has been achieved th...
research
∙
11/09/2015
Explicit Knowledge-based Reasoning for Visual Question Answering
We describe a method for visual question answering which is capable of r...
research
∙
07/21/2015
Online Metric-Weighted Linear Representations for Robust Visual Tracking
In this paper, we propose a visual tracker based on a metric-weighted li...
research
∙
06/03/2015
What value do explicit high level concepts have in vision to language problems?
Much of the recent progress in Vision-to-Language (V2L) problems has bee...
research
∙
01/04/2014
Context-Aware Hypergraph Construction for Robust Spectral Clustering
Spectral clustering is a powerful tool for unsupervised data analysis. I...
research
∙
10/22/2013
Contextual Hypergraph Modelling for Salient Object Detection
Salient object detection aims to locate objects that capture human atten...
research
∙
07/14/2012
