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» Learning Similarity for Texture Image Retrieval
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132
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MM
2006
ACM
158views Multimedia» more  MM 2006»
15 years 8 months ago
Extreme video retrieval: joint maximization of human and computer performance
We present an efficient system for video search that maximizes the use of human bandwidth, while at the same time exploiting the machine’s ability to learn in real-time from use...
Alexander G. Hauptmann, Wei-Hao Lin, Rong Yan, Jun...
128
Voted
ETVC
2008
15 years 4 months ago
Sparse Multiscale Patches for Image Processing
Abstract. This paper presents a framework to define an objective measure of the similarity (or dissimilarity) between two images for image processing. The problem is twofold: 1) de...
Paolo Piro, Sandrine Anthoine, Eric Debreuve, Mich...
152
Voted
PAMI
2012
13 years 5 months ago
IntentSearch: Capturing User Intention for One-Click Internet Image Search
—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...
151
Voted
WWW
2011
ACM
14 years 9 months ago
Learning to re-rank: query-dependent image re-ranking using click data
Our objective is to improve the performance of keyword based image search engines by re-ranking their baseline results. To this end, we address three limitations of existing searc...
Vidit Jain, Manik Varma
147
Voted
CVPR
2010
IEEE
15 years 11 months ago
Tag-based Web Photo Retrieval Improved by Batch Mode Re-Tagging
Web photos in social media sharing websites such as Flickr are generally accompanied by rich but noisy textual descriptions (tags, captions, categories, etc.). In this paper, we p...
Lin Chen, Dong Xu, Wai-Hung Tsang, Jiebo Luo