Recognizing fine-grained sub-categories such as birds and dogs is extremely challenging
due to the highly localized and subtle differences in some specific parts. Most previous …

Part models of object categories are essential for challenging recognition tasks, where
differences in categories are subtle and only reflected in appearances of small parts of the …

The continuous monitoring of animals is crucial for the well-being of both humans and
animals. A comprehensive animal monitoring system must incorporate animal detection …

Fine-grained image classification methods often suffer from the challenge that the
subordinate categories within an entry-level category can only be distinguished by subtle …

To distinguish the subtle differences among fine-grained categories, a large amount of well-
labeled images are typically required. However, manual annotations for fine-grained …

Fine-grained categorisation has been a challenging problem due to small inter-class
variation, large intra-class variation and low number of training images. We propose a …

Visual patterns represent the discernible regularity in the visual world. They capture the
essential nature of visual objects or scenes. Understanding and modeling visual patterns is …

Manually labeling fine-grained datasetsis laborious and typically requires domain-specific
expert knowledge. Conversely, a vast amount of web data is relatively easy to obtain with …

In this paper, we tackle a valuable yet very challenging visual recognition task, where the
instances are within a subordinate category, and the target domain undergoes a shift with …

The current paper presents a fine-grained image recognition problem, one of multi-class
classification, namely determining the breed of a dog in a given image. The presented …