Sam Motamed

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

Research

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.

Publications

	Lego: Learning to Disentangle and Invert Concepts Beyond Object Appearance in Text-to-Image Diffusion Models Saman Motamed, Danda Pani Paudel, Luc Van Gool ECCV, 2024 code / arxiv A method for textual inversion of adjectives and verbs in text-to-image diffusion models.
	Investigating the Effectiveness of Cross-Attention to Unlock Zero-Shot Editing of Text-to-Video Diffusion Models Saman Motamed, Wouter Van Gansbeke, Luc Van Gool CVPR Generative Models Workshop, 2024 code / arxiv Zero-shot control over object shape, position and movement in test-to-video models via cross-attention maps.
	A Unified and Interpretable Emotion Representation and Expression Generation Reni Paskaleva, Mykyta Holubakha, Andela Ilic, Saman Motamed, Luc Van Gool, Danda Paudel CVPR, 2024 arxiv fine-grained generation of expressions in conjunction with other textual inputs and offers a new label space for emotions at the same time.
	D3GU: Multi-Target Active Domain Adaptation via Enhancing Domain Alignment 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.
	Personalized Face Inpainting With Diffusion Models by Parallel Visual Attention 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.
	PATMAT: Person Aware Tuning of Mask-Aware Transformer for Face Inpainting 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.
	Generative Visual Prompt: Unifying Distributional Control of Pre-Trained Generative Models 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.

Happenings

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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