About
I'm a Masters student in the Probabilistic Vision Group at McGill University under the supervision of Professor Tal Arbel.
You can find my complete CV here, and my personal portfolio here.
Research Interests
- Deep Learning
- Generative Modeling
- Diffusion Models
- Representation learning
- Computer vision
Education
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M.Sc. Electrical Engineering
McGill University, Montreal, Canada
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B.Sc Computer Engineering
Sharif University of Technology, Tehran, Iran
Experience
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Research Intern
ETH, Zurich
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Research Intern
EPFL, Lausanne
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Undergraduate Researcher
UCI, California
Publications & Conferences
Toward reliable human pose forecasting with uncertainty
In our IEEE RA-L paper, we address the challenge of predicting future 3D human poses from past observations. We introduce an open-source library for human pose forecasting, offering multiple models, standardized evaluation metrics, and support for various datasets. Our methods improve forecasting accuracy by modeling both aleatoric and epistemic uncertainty. Experiments on Human3.6M, AMSS, and 3DPW datasets show up to 25% improvement in short-term forecasting without compromising long-term performance. Our code is available online to facilitate further research.
Reconstruction of 3D Interaction Models from Images using Shape Prior
In our ICCV workshop paper, we explore the reconstruction of 3D human-object interactions from images, including both human and object shape and pose estimation. We introduce a novel autoregressive transformer-based variational autoencoder that learns a robust shape prior from extensive 3D datasets. By leveraging the reconstructed 3D human body, our approach enhances object shape and pose estimation. Experimental results on the BEHAVE dataset demonstrate the effectiveness of our method, achieving a 40.7 cm Chamfer distance and showcasing the benefits of learning a shape prior.
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