The explosive increase and ubiquitous accessibility of visual data on the Web have led to
the prosperity of research activity in image search or retrieval. With the ignorance of visual …

The rapid growth of video on the internet has made searching for video content using natural
language queries a significant challenge. Human-generated queries for video datasetsin the …

We present a novel latent embedding model for learning a compatibility function between
image and class embeddings, in the context of zero-shot classification. The proposed …

Attributes act as intermediate representations that enable parameter sharing between
classes, a must when training data is scarce. We propose to view attribute-based image …

Image classification has advanced significantly in recent years with the availability of large-
scale image sets. However, fine-grained classification remains a major challenge due to the …

Deep convolutional neural networks have been successfully applied to image classification
tasks. When these same networks have been applied to image retrieval, the assumption has …

Recent research has explored the possibility of extracting ancillary information from primary
biometric traits viz., face, fingerprints, hand geometry, and iris. This ancillary information …

Attributes are an intermediate representation, which enables parameter sharing between
classes, a must when training data is scarce. We propose to view attribute-based image …

We introduce the use of describable visual attributes for face verification and image search.
Describable visual attributes are labels that can be given to an image to describe its …

We propose a novel mode of feedback for image search, where a user describes which
properties of exemplar images should be adjusted in order to more closely match his/her …