Leaderboard

Instructions

This page display the submited results for Activity Leaderboards. For each submission, we display several main metrics in main table. For detailed information, more metrics, per-sequence results and visualisation (coming soon), please click submission name. For all tables, you can click headers to sort the results. Note you can download the submission zip file as well. Legends, metrics descriptions and reference are displayed after leaderboards table.

Social Activity Submissions

Name mAP1 mAP2

4.7% 3.4%
Mahsa Ehsanpour, Fatemeh Saleh, Silvio Savarese, Ian Reid, Hamid Rezatofighi JRDB-Act: A Large-scale Dataset for Spatio-temporal Action, Social Group and Activity Detection in arXiv

3.5% 1.2%
Mahsa Ehsanpour, Alireza Abedin, Fatemeh Saleh, Javen Shi, Ian Reid, Hamid Rezatofighi Joint Learning of Social Groups, Individuals Action and Sub-group Activities in Videos in ECCV2020

Additional Information Used

Symbol Description
Individual Image Method uses individual images from each camera
Stitched Image Method uses stitched images combined from the individual cameras
Pointcloud Method uses 3D pointcloud data
Online Tracking Method does frame-by-frame processing with no lookahead
Offline Tracking Method does not do in-order frame processing
Public Detections Method uses publicly available detections
Private Detections Method uses its own private detections

Evaluation Measures[1]

Measure Better Perfect Description
mAP1/AP1 higher 100% takes into account the social activity label as well as the group membership for each box. This metric is used as the main metric for the social activity detection challenge.
mAP2/AP2 higher 100% mAP2/AP2 is calculated similar to the individual action detection task.

Reference

  1. The style and content of the Evaluation Measures section is reference from MOT Challenges.