JackRabbot Dataset and Benchmark (JRDB)
Visual Perception for Navigation in Human Environments
Visual Perception for Navigation in Human Environments
JRDB is a novel dataset collected from our social mobile manipulator, JackRabbot. Our goal is to provide training and benchmarking data for research in the areas of autonomous robot navigation and all perceptual tasks related to social robotics in human environments.
Please note that you are required to log in before downloading JRDB. If you don't have an account, you can sign up for one here.
See DownloadsThe JackRabbot social mobile manipulator.
Jun. 27, 2022
As a part of our ECCV22 workshop, we have released JRDB2022 new annotations including 2D human skeleton pose & head bounding boxes and the improved 2&3D bounding box, action & social grouping. New JRDB22 leaderboards will be launched soon.
March 30, 2022
We will organise a new JRDB workshop in conjunction with ECCV22. Click here for more information
March 2, 2022
The JRDB-ACT paper has been accepted and will presented in CVPR22. Find the paper here
November 26, 2021
JRDB dataset and benchmark has offically moved to Monash University! The previous server at Stanford will shut down soon. All previous submissions have been uploaded by the dataset admins. Please register a new account to make submissions.
Roberto Martín-Martín*, Mihir Patel*, Hamid
Rezatofighi*, Abhijeet Shenoi, JunYoung Gwak, Eric Frankel, Amir Sadeghian, Silvio
Savarese.
IEEE Transactions on Pattern Analysis and Machine
Intelligence (TPAMI), 2021.
Citation:
@article{martin2021jrdb, title={Jrdb: A dataset and benchmark of egocentric robot visual perception of humans in built environments}, author={Martin-Martin, Roberto and Patel, Mihir and Rezatofighi, Hamid and Shenoi, Abhijeet and Gwak, JunYoung and Frankel, Eric and Sadeghian, Amir and Savarese, Silvio}, journal={IEEE transactions on pattern analysis and machine intelligence}, year={2021}, publisher={IEEE} }
Mahsa Ehsanpour, Fatemeh Saleh, Silvio Savarese,
Ian Reid, Hamid Rezatofighi.
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR),
2022.
Citation:
@inproceedings{ehsanpour2022jrdb, title={JRDB-Act: A Large-Scale Dataset for Spatio-Temporal Action, Social Group and Activity Detection}, author={Ehsanpour, Mahsa and Saleh, Fatemeh and Savarese, Silvio and Reid, Ian and Rezatofighi, Hamid}, booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition}, year={2022} }