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Mahsa Ehsanpour

3 accepted papers

2022

JRDB-Act: A Large-Scale Dataset for Spatio-Temporal Action, Social Group and Activity Detection

CVPR 2022poster

The availability of large-scale video action understanding datasets has facilitated advances in the interpretation of visual scenes containing people. However, learning to recognise human actions and their social interactions in an unconstrained real-world environment comprising numerous people, wit…

Cited by 46PDFScholar
2021

TRiPOD: Human Trajectory and Pose Dynamics Forecasting in the Wild

ICCV 2021poster

Joint forecasting of human trajectory and pose dynamics is a fundamental building block of various applications ranging from robotics and autonomous driving to surveillance systems. Predicting body dynamics requires capturing subtle information embedded in the humans' interactions with each other an…

Cited by 64PDFScholar
2020

Joint Learning of Social Groups, Individuals Action and Sub-group Activities in Videos

ECCV 2020poster

Individuals Action and Sub-group Activities in Videos","The state-of-the art solutions for human activity understanding from a video stream formulate the task as a spatio-temporal problem which requires joint localization of all individuals in the scene and classification of their actions or group a…