Description
The Mall dataset (Loy, Chen, Gong, Xiang) is a video-based crowd-counting benchmark captured from a single fixed surveillance camera in a shopping mall. It contains 2000 frames with per-pedestrian annotations and is one of the standard low-to-medium-density crowd-counting datasets, alongside UCSD. Together with UCSD it is regularly criticised in the literature for low scene-perspective variation, since both come from a single continuous video sequence.
Modality / size
- Modality: RGB video frames from a fixed surveillance camera.
- Subjects / scenarios: shopping mall, single viewpoint.
- Labels: head annotations per frame, 2000 frames.
Used by (papers)
- Standard CNN crowd-counting baseline alongside
ShanghaiTech,UCF_CC_50,WorldExpo '10, andUCSD. - Used as the video baseline in vault papers comparing CSI / RF crowd counting against camera-based counting.
Notes
- Public dataset; mirror at the original Loy et al. project page.
- Disambiguation:
Mallextracted from claims is noisy because the literal word "mall" matches many unrelated phrases; only treat as the dataset when context is crowd counting.