Unsupervised Person Re Identification
Unsupervised person re-identification (re-ID) is an important research direction in the field of computer vision, aiming to automatically extract and match features of the same pedestrian captured by different cameras without the need for labeled data, to achieve cross-camera pedestrian identity recognition. This technology can significantly reduce the annotation costs of large-scale surveillance systems, improve the efficiency and accuracy of pedestrian retrieval, and has broad application prospects, especially in intelligent security, urban management, and business intelligence fields.
ClonedPerson
DukeMTMC-reID
TMGF
DukeMTMC-reID->Market-1501
MMT-ResNet50
DukeMTMC-reID->MSMT17
CORE-ReID
DukeMTMC-VideoReID
uPMnet
DukeMTMCreID
IICS
iLIDS-VID
uPMnet
LTCC
Market-1501
TransReID-SSL (ViTi-S)
Market-1501->DukeMTMC-reID
MMT-ResNet50
Market-1501->MSMT17
MMT-ResNet50
MARS
AuxUSLReID
MSMT17
Group Sampling
MSMT17->DukeMTMC-reID
OSNet-AIN
MSMT17->Market-1501
OSNet-AIN
PersonX
Cluster Contrast
PRCC
SiCL
PRID2011
uPMnet
VC-Clothes