This paper investigates the level of metadata accuracy required for image filters to be valuable to users. Access to large digital image and video collections is hampered by ambig...
We study the problem of learning to rank images for image retrieval. For a noisy set of images indexed or tagged by the same keyword, we learn a ranking model from some training e...
The state-of-the art in visual object retrieval from large
databases allows to search millions of images on the object
level. Recently, complementary works have proposed systems
...
Stephan Gammeter, Lukas Bossard, Till Quack, Luc V...
This paper presents an efficient, personalizable and yet completely automatic algorithm for enhancing the brightness, tonal balance, and contrast of faces in thumbnails of online...
This paper describes Gallery, which is our under developing experimental system for supporting the management of personal digital knowledge repositories and which enables its users...