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
.
CNN-RNN: A Unified Framework for Multi-label Image Classification
2016
2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
While deep convolutional neural networks (CNNs) have shown a great success in single-label image classification, it is important to note that real world images generally contain multiple labels, which could correspond to different objects, scenes, actions and attributes in an image. Traditional approaches to multi-label image classification learn independent classifiers for each category and employ ranking or thresholding on the classification results. These techniques, although working well,
doi:10.1109/cvpr.2016.251
dblp:conf/cvpr/WangYMHHX16
fatcat:s2tgck7esbbl5nmfxluycs6cea