The CityPersons dataset is a subset of Cityscapes which only consists of person annotations. There are 2975 images for training, 500 and 1575 images for validation and testing. The average of the number of pedestrians in an image is 7. The visible-region and full-body annotations are provided.
78 PAPERS • 1 BENCHMARK
PRW is a large-scale dataset for end-to-end pedestrian detection and person recognition in raw video frames. PRW is introduced to evaluate Person Re-identification in the Wild, using videos acquired through six synchronized cameras. It contains 932 identities and 11,816 frames in which pedestrians are annotated with their bounding box positions and identities.
41 PAPERS • NO BENCHMARKS YET
ETH is a dataset for pedestrian detection. The testing set contains 1,804 images in three video clips. The dataset is captured from a stereo rig mounted on car, with a resolution of 640 x 480 (bayered), and a framerate of 13--14 FPS.
39 PAPERS • 4 BENCHMARKS
The INRIA Person dataset is a dataset of images of persons used for pedestrian detection. It consists of 614 person detections for training and 288 for testing.
15 PAPERS • NO BENCHMARKS YET
TJU-DHD is a high-resolution dataset for object detection and pedestrian detection. The dataset contains 115,354 high-resolution images (52% images have a resolution of 1624×1200 pixels and 48% images have a resolution of at least 2,560×1,440 pixels) and 709,330 labelled objects in total with a large variance in scale and appearance.
7 PAPERS • 2 BENCHMARKS
The EuroCity Persons dataset provides a large number of highly diverse, accurate and detailed annotations of pedestrians, cyclists and other riders in urban traffic scenes. The images for this dataset were collected on-board a moving vehicle in 31 cities of 12 European countries. With over 238,200 person instances manually labeled in over 47,300 images, EuroCity Persons is nearly one order of magnitude larger than person datasets used previously for benchmarking. The dataset furthermore contains a large number of person orientation annotations (over 211,200).
4 PAPERS • NO BENCHMARKS YET
This recently released multispectral (multi-)object detection dataset contains around 10k manually-annotated thermal images with their corresponding reference visible images, collected during daytime and nighttime. We only kept the 3 more frequent classes which are “bicycle”, “car” and “per- son”. We manually removed the misaligned visible-thermal image pairs and ended with 4,129 well-aligned image pairs for training and 1,013 image pairs for test. This new aligned dataset can be downloaded here: http:// shorturl.at/ahAY4
3 PAPERS • 2 BENCHMARKS
Visible-infrared Paired Dataset for Low-light Vision 30976 images (15488 pairs) 24 dark scenes, 2 daytime scenes Support for image-to-image translation (visible to infrared, or infrared to visible), visible and infrared image fusion, low-light pedestrian detection, and infrared pedestrian detection
3 PAPERS • 4 BENCHMARKS
UofTPed50 is an object detection and tracking dataset which uses GPS to ground truth the position and velocity of a pedestrian.
2 PAPERS • NO BENCHMARKS YET
A dataset to encourage research in these environments. It consists of labeled stereo video of people in orange and apple orchards taken from two perception platforms (a tractor and a pickup truck), along with vehicle position data from RTK GPS.
1 PAPER • NO BENCHMARKS YET
The RailEye3D dataset, a collection of train-platform scenarios for applications targeting passenger safety and automation of train dispatching, consists of 10 image sequences captured at 6 railway stations in Austria. Annotations for multi-object tracking are provided in both an unified format as well as the ground-truth format used in the MOTChallenge.
1 PAPER • NO BENCHMARKS YET