A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2016; you can also visit the original URL.
The file type is application/pdf
.
Multimodal Learning in Loosely-Organized Web Images
2014
2014 IEEE Conference on Computer Vision and Pattern Recognition
Photo-sharing websites have become very popular in the last few years, leading to huge collections of online images. In addition to image data, these websites collect a variety of multimodal metadata about photos including text tags, captions, GPS coordinates, camera metadata, user profiles, etc. However, this metadata is not well constrained and is often noisy, sparse, or missing altogether. In this paper, we propose a framework to model these "loosely organized" multimodal datasets, and show
doi:10.1109/cvpr.2014.316
dblp:conf/cvpr/DuanCB14
fatcat:ddg2rdsvqjdzjcjf7qsr4prhui