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Photo of Vida Adeli MosabedVida Adeli

PhD Candidate

Computer Science (University of Toronto)




Research Interest

  • Computer Vision
  • Machine Learning
  • Video Understanding
  • Human Activity Recognition
  • Event Understanding
  • Human Pose/Motion Estimation and Forecasting
  • Rehabilitative Technology


Vida is a Ph.D. student at the University of Toronto (U of T) under Dr. Babak Taati's supervision. She is working on the AMBIENT project in which she applies computer vision and machine learning techniques in the development of intelligent health monitoring and rehabilitation technologies for older adults. She has received her MSc in artificial intelligence and robotics with a focus on computer vision and machine learning from Ferdowsi University of Mashhad (FUM). Vida has recently led a joint research project at the Stanford Vision and Learning (SVL) Lab and Monash University's Vision & Learning for Autonomous AI (VL4AI) Lab on Human Pose Dynamics and Trajectory Forecasting. She organized the ICCV21 workshop on Human Trajectory and Pose Dynamics Forecasting and created a standard benchmark for Social Motion Forecasting (SoMoF). She was also a Research Associate at Machine Vision Lab at FUM for three years. Her work has focused on applying machine learning and computer vision to different industrial projects.



V. Adeli, N. Korhani, B. Taati, A. Iaboni, A. Sabo, S. Mehdizadeh, A. Flint, A. Mansfield, “Vision-based Ambient Monitoring of Gait for Dynamic and Short-Term Falls Risk Assessment in People With Dementia,”, IEEE Journal Of Biomedical And Health Informatics (JBHI 2023).

V. Adeli, E. Adeli, I., Reid, J. C. Niebles and H. Rezatofighi. (2020) “Socially and Contextually Aware Human Motion and Pose Forecasting,” IEEE Robotics and Automation Letters (RA-L), 5(4), pp.6033-6040.

V. Adeli, E. Fazl-Ersi, and A. Harati. (2019) “A component-based video content representation for action recognition,” Image and Vision Computing, 90, p.103805.


V. Adeli, S. Mehraban, I. Campose, Y. Zarghami, A. Sabo, A. Iaboni, and B. Taati “Benchmarking Skeleton-based Motion Encoder Models for Clinical Applications: Estimating Parkinson’s Disease Severity in Walking Sequences,”, IEEE International Conference on Automatic Face and Gesture Recognition (FG2024).

S. Mehraban, V. Adeli, and B. Taati “MotionAGFormer: Enhancing 3D Human Pose Estimation with a Transformer-GCNFormer Network,”, Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV2024).

C. Malin-Mayor, V. Adeli, A. Sabo, S. Noritsyn, C. Gorodetsky, C. Fasano, A. Iaboni and B. Taati “Pose2Gait: Extracting Gait Features from Monocular Video of Individuals with Dementia,”,Ambient Intelligence For Healthcare (AmI4HC) International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI2023)

V. Adeli, M. Ehsanpour, J. C. Niebles, I. Reid, S. Savarese, E. Adeli and H. Rezatofighi. (2021) “TRiPOD: Human Trajectory and Pose Dynamics Forecasting in the Wild,”, IEEE International Conference on Computer Vision (ICCV21).

V. Adeli, E. Adeli, I., Reid, J. C. Niebles and H. Rezatofighi. (2020) “Socially and Contextually Aware Human Motion and Pose Forecasting,” International Conference on Intelligent Robots and Systems (IROS20).

V. Adeli, E. Fazl-Ersi, and A. Harati. (2018) “Enhancing Human Action Recognition through Temporal Saliency,” International Conference on Pattern Recognition and Artificial Intelligence (ICPRAI 2018), Canada.


1st Workshop, Benchmark and Challenge on Human Trajectory and Pose Dynamics Forecasting in the Wild (ICCV 2021). Organizers: Andrew Sharp, Vida Adeli, Juan Carlos Niebles, Ehsan Adeli, Silvio Savarese, and Hamid Rezatofighi. “SoMoF: SOcial MOtion Forecasting Benchmark and Challenge”.