Skip to content


Switch branches/tags

Name already in use

A tag already exists with the provided branch name. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. Are you sure you want to create this branch?

Latest commit


Git stats


Failed to load latest commit information.
Latest commit message
Commit time


This repo contains information on the Warwick-NTU Multi-camera Forecasting database (WNMF) and baseline multi-camera trajectory forecasting (MCTF) experiments. This repo acompanies the following paper:

Olly Styles, Tanaya Guha, Victor Sanchez, Alex C. Kot, “Multi-Camera Trajectory Forecasting: Pedestrian Trajectory Prediction in a Network of Cameras”, IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2020

Paper link:


2020.05.01 - Initial dataset release

2021.08.11 - Cleaned annotations, preprocessing new MCTF problems, more MCTF models, multi-target MCTF preprocessing. Updated annotations are avaiable upon dataset request, and new code is available in the our new repositry, [Trajectory Tensors].

Accessing WNMF

If you are interested in downloading the WNMF dataset, please download a copy of our [Release Agreement]. After reading the terms, fill in the information and send the completed agreement to the email address shown in the document. We will then send you the link and password to access the dataset.

Dataset details

The data download contains the following:


Videos are paired into entrances and departures. A departure is defined as the 4 seconds before tracking infromation is lost (and the person is therefore assumed to have left the camera view. An entrance is the next camera of re-apperance for this individual. Entrance video clips last for 12 seconds, starting from the moment the individual departed from the other camera view. Each video is processed using [RetinaFace] using an open-source [Pytorch implementation] to mask faces.

Bounding boxes

Bouding boxes are obtained using an [open-source implementation] of [Mask-RCNN], pre-trained on [MS-COCO]. Individuals are then tracked using an [open-source implementation] of the [DeepSORT] tracking algorithm.

Entrances and departures

Each track is labelled as as entrance (first frame of the track) or departure (last frame of the track)

RE-ID features

RE-ID features are computed using an [open-source implementation] of the [bag-of-tricks] RE-ID model pretrained on [Market-1501].

Cross-camera matches

Cross-camera matches are found using the labelling procedure described in our paper.


Pre-trained weights for each model in our paper.

Camera topology

The camera topology is shown in the figure below.


Repo for the paper 'Multi-Camera Trajectory Forecasting: Pedestrian Trajectory Prediction in a Network of Cameras'. CVPRW 2020






No releases published


No packages published