Exploring Models and Data for Image Question Answering

This work aims to address the problem of image-based question-answering (QA) with new models and datasets. In our work, we propose to use neural networks and visual semantic embeddings, without intermediate stages such as object detection and image segmentation, to predict answers to simple questions about images... (read more)

PDF Abstract NeurIPS 2015 PDF NeurIPS 2015 Abstract

Datasets


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT BENCHMARK
Video Question Answering SUTD-TrafficQA VIS+LST 1/4 29.91 # 4
1/2 54.25 # 4

Methods used in the Paper


METHOD TYPE
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