Aspect-based relevance learning is a relevance feedback scheme based on a natural model of relevance in terms of image aspects. In this paper we propose a number of active learning...
We present a novel similarity measure for bag-of-words type large scale image retrieval. The similarity function is learned in an unsupervised manner, requires no extra space over ...
—Web-scale image search engines (e.g. Google Image Search, Bing Image Search) mostly rely on surrounding text features. It is difficult for them to interpret users’ search int...
Xiaoou Tang, Ke Liu, Jingyu Cui, Fang Wen, Xiaogan...
: Despite the efforts to reduce the semantic gap between user perception of similarity and featurebased representation of images, user interaction is essential to improve retrieval...
This paper addresses the problem of similar image retrieval, especially in the setting of large-scale datasets with millions to billions of images. The core novel contribution is ...