The QMUL underGround Re-IDentification (GRID) dataset contains 250 pedestrian image pairs. Each pair contains two images of the same individual seen from different camera views. All images are captured from 8 disjoint camera views installed in a busy underground station. The dataset is challenging due to variations of pose, colours, lighting changes; as well as poor image quality caused by low spatial resolution.Related publications:C. C. Loy, T. Xiang, and S. Gong, Time-Delayed Correlation Analysis for Multi-Camera Activity Understanding, International Journal of Computer Vision, vol. 90(1), pp. 106-129, October 2010(IJCV 2010)(PDF)C. C. Loy, T. Xiang, and S. Gong, Multi-Camera Activity Correlation Analysis, IEEE Conference on Computer Vision and Pattern Recognition, pp. 1988-1995, Miami, USA, June 2009(CVPR 2009)(PDF)