Large repositories of 3D shapes provide valuable input for data-driven analysis and
modeling tools. They are especially powerful once annotated with semantic information such …

The modern image search system requires semantic understanding of image, and a key yet
under-addressed problem is to learn a good metric for measuring the similarity between …

Attention-based learning for fine-grained image recognition remains a challenging task,
where most of the existing methods treat each object part in isolation, while neglecting the …

In the context of fine-grained visual categorization, the ability to interpret models as human-
understandable visual manuals is sometimes as important as achieving high classification …

Scaling up fine-grained recognition to all domains of fine-grained objects is a challenge the
computer vision community will need to face in order to realize its goal of recognizing all …

Current approaches for fine-grained recognition do the following: First, recruit experts to
annotate a dataset of images, optionally also collecting more structured data in the form of …

We propose an architecture for fine-grained visual categorization that approaches expert
human performance in the classification of bird species. Our architecture first computes an …

We address the problem of large-scale fine-grained visual categorization, describing new
methods we have used to produce an online field guide to 500 North American bird species …

The Internet is an important focus of attention for those concerned with issues of extended
cognition. In particular, the application of active externalist theorizing to the Internet gives …

Cameras are being used everywhere for the safety and security of citizens in different
countries. Using a machine to detect humans in a photo or a video frame is a very …