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I am an ELLIS Ph.D. student at INSAIT where I am advised by Prof. Luc Van Gool and a Student Researcher at Google DeepMind in Toronto. Before that I was a visiting researcher from 2021 to 2023 at CMU's Human Sensing Lab working with the amazing Fernando De La Torre. I also spent 7 wonderful years at the University of Toronto's Computer Science department where I earned my HBSc and MS degrees. Email / CV / Google Scholar / Twitter / Github |
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I'm broadly interested in Generative Vision models for content creation, and currently focused on Video synthesis. My research aims to gain a better understanding of how to enable user-intuitive control over Generative models. I am also interested in bias mitigation and harnessing the power of large vision and language models by adapting them to solve personalized tasks using limited data. Relevant work is highlighted here. |
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Lin Zhang, Linghan Xu, Saman Motamed, Shayok Chakraborty, Fernando De la Torre WACV, 2024 arxiv A Multi-Target Active Domain Adaptation (MT-ADA) framework for image classification. |
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Jianjin Xu, Saman Motamed, Praneetha Vaddamanu, Chen Henry Wu, Christian Haene, Jean-Charles Bazin, Fernando De la Torre WACV, 2024 code / arxiv Fast, identity preserving face inpainting with diffusion models. |
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Saman Motamed, Danda Pani Paudel, Luc Van Gool arxiv, 2023 code / arxiv A method for textual inversion of adjectives and verbs in text-to-image diffusion models. |
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Saman Motamed, Jianjin Xu, Chen Henry Wu, Fernando De la Torre ICCV, 2023 ICCV / code / arxiv A tuning method for personalizing inpainting of the face and preserving the odentity of a subject. |
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Chen Henry Wu, Saman Motamed, Shaunak Srivastava, Fernando De La Torre NeurIPS, 2022 NeurIPS / code / arxiv A framework for defining control over latent-based generative models. |
- Oct 2023 Two papers accepted at WACV 2024. Details will be posted soon.
- Oct 2023 I served as a volunteer at ICCV 23 and presented PATMAT.
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