22 datasets found

A roadside LiDAR-based detection and tracking approach for pedestrians and vehicles

CityPersons and CrowdHuman are two benchmark datasets for pedestrian detection. CityPersons contains 35k person and 13k ignore region annotations, while CrowdHuman contains 340k...

Pedestrian detection in top-view fisheye images using composite images of perspective views

Pedestrian detection in top-view fisheye images using composite images of perspective views

Pedestrian detection in top-view fisheye images using composite images of perspective views

The Caltech dataset is a benchmark for pedestrian detection, consisting of approximately 10 hours of video taken from a vehicle driving through Los Angeles.

Pedestrian detection: An evaluation of the state of the art.

KAIST Multispectral Dataset is a multispectral dataset for pedestrian detection.

Image fusion aims to combine information from different source images to create a comprehensively representative image. Existing fusion methods are typically helpless in dealing...

Person search unifies person detection and person re-identification (Re-ID) to locate query persons from the panoramic gallery images. One major challenge comes from the...

CUHK-SYSU is a large-scale dataset designed for person search, which contains 18,184 scene images captured from street nap and movie screenshot.

Multi-Camera Multi-Object Tracking (MC-MOT) dataset for reconfigurable spatial-temporal graph model

The Caltech Pedestrian Dataset contains pedestrian images taken at a busy street in Pasadena, California.

Pedestrian detection plays an important role in many applications such as autonomous driving. We propose a method that explores semantic segmentation results as self-attention...

Three datasets: training, calibration, and evaluation datasets for pedestrian detection task.

The dataset used in the paper for object detection, featuring images from PASCAL VOC, COCO, TJU-DHD, and ImageNet.

TUD-Brussels pedestrian dataset

ETH pedestrian dataset

The dataset used in the paper is the KITTI dataset, which is a benchmark for monocular depth estimation. The dataset consists of a large collection of images and corresponding...

A benchmark for anomaly detection in crowded scenes. It contains 19600 frames captured using two different cameras.