Abstract Person Re-Identification (Re-ID) is a critical aspect of visual surveillance systems,
which aims to automatically recognize and locate individuals across a multi-camera network …

Brain-inspired algorithms have become a new trend in next-generation artificial intelligence.
Through research on brain science, the intelligence of remote sensing algorithms can be …

Visible infrared person re-identification (VI-REID) aims to match pedestrian images between
the daytime visible and nighttime infrared camera views. The large cross-modality …

The performance of person re-identification (re-ID) is easily affected by illumination
variations caused by different shooting times, places and cameras. Existing illumination …

Video person re-identification (V-ReID) can leverage rich spatial-temporal information
embedded in sequence data to achieve better accuracy. However, it is vulnerable to the …

Person re-identification (re-ID) aims to match the same person across different cameras.
However, most existing re-ID methods assume that people wear the same clothes in …

Video-based person re-identification (Re-ID) aims to match identical person sequences
captured across non-overlapping surveillance areas. It is an essential yet challenging task to …

Heterogeneous pedestrian images are captured by visible and infrared cameras with
different spectrums, which play an important role in night-time video surveillance. However …

Most video-based person re-identification (re-id) methods only focus on appearance
features but neglect motion features. In fact, motion features can help to distinguish the …

Video-based person re-identification (Re-ID) aims to match the same pedestrian from the
video sequences captured by non-overlapping cameras. It is the key to fully extracting …