A multi-camera system combines features from different cameras to exploit a scene of an
event to increase the output image quality. The combination of two or more cameras …

Technology has an important part to play in wildlife and ecosystem conservation, and can
vastly reduce time and effort spent in the associated tasks. Deep learning methods for …

Drastic variations in illumination across surveillance cameras make the person re-
identification problem extremely challenging. Current large scale re-identification datasets …

Machine learning datasets have elicited concerns about privacy, bias, and unethical
applications, leading to the retraction of prominent datasets such as DukeMTMC, MS-Celeb …

Most existing person re-identification (re-id) methods rely on supervised model learning on
per-camera-pair manually labelled pairwise training data. This leads to poor scalability in a …

Person re-identification (re-id) is a critical problem in video analytics applications such as
security and surveillance. The public release of several datasets and code for vision …

Person re-identification, a branch of image retrieval, is an increasingly important public
safety application. When monitoring larger areas, it is crucial to correctly match the same …

This work introduces a multi-camera tracking dataset consisting of 234 hours of video data
recorded concurrently from 234 overlapping HD cameras covering a 4.2 mile stretch of 8-10 …

Face recognition (FR) is one of the most extensively investigated problems in computer
vision. Significant progress in FR has been made due to the recent introduction of the larger …

In real-world applications, eg law enforcement and video retrieval, one often needs to
search a certain person in long videos with just one portrait. This is much more challenging …