Muhammad Ferjad Naeem

I am a Ph.D. Candidate at the Computer Vision lab at ETH Zürich supervised by Prof. Luc Van Gool and PD. Dr. Federico Tombari. I am also a Research Consultant with Google in Zurich working closely with Federico Tombari's team as part of my Ph.D. I am particularly interested in Machine Learning systems that can adapt and generalize to novel environments. Previously I obtained my Master's degree from the Technical University of Munich with a focus on Generative Models at Naver AI Lab and Zero-shot Learning at UniTübingen AI Research. I have also been an intern at Nvidia.

Email / Google Scholar / Github / Twitter / CV

Publications

	Learning Attention Propagation for Compositional Zero-Shot Learning Muhammad Gul Zain Ali Khan, Muhammad Ferjad Naeem, Luc Van Gool, Alain Pagani, Didier Stricker, Muhammad Zeshan Afzal WACV, 2023
	I2DFormer: Learning Image to Document Attention for Zero-Shot Image Classification Muhammad Ferjad Naeem, Yongqin Xian, Luc Van Gool, Federico Tombari NeurIPS, 2022
	3D Compositional Zero-shot Learning with DeCompositional Consensus Muhammad Ferjad Naeem, Evin Pinar Ornek, Yongqin Xian, Luc Van Gool, Federico Tombari Equal contribution ECCV*, 2022 Paper / Code
	Learning Graph Embeddings for Open World Compositional Zero-shot Learning Massimiliano Mancini, Muhammad Ferjad Naeem, Yongqin Xian, Zeynep Akata TPAMI, 2022 Paper / Code
	Learning Graph Embeddings for Compositional Zero-shot Learning Muhammad Ferjad Naeem, Yongqin Xian, Federico Tombari, Zeynep Akata CVPR, 2021 Paper / Code
	Open World Compositional Zero-Shot Learning Massimiliano Mancini, Muhammad Ferjad Naeem, Yongqin Xian, Zeynep Akata Equal contribution CVPR*, 2021 Paper / Code
	Reliable Fidelity and Diversity Metrics for Generative Models Muhammad Ferjad Naeem, Seong Joon Oh, Youngjung Uh, Yunjey Choi, Jaejun Yoo Equal contribution ICML*, 2020 Paper / Code / Youtube
	Deep Learning Under the Microscope: Improving the Interpretability of Medical Imaging Neural Networks Magdalini Paschali, Muhammad Ferjad Naeem, Walter Simson, Katja Steiger, Martin Mollenhauer, Nassir Navab Equal contribution Arxiv*, 2019 Paper
	A Multi-Faceted OCR Framework for Artificial Urdu News Ticker Text Recognition Sami-Ur-Rehman, Burhan Ul Tayyab, Muhammad Ferjad Naeem, Adnan Ul-Hasan, Faisal Shafait DAS, 2018 Paper
	Impact of Ligature Coverage on Training Practical Urdu OCR Systems Muhammad Ferjad Naeem, Noor ul Sehr Zia, Aqsa Ahmed Awan, Faisal Shafait, Adnan ul Hasan ICDAR, 2017 Paper

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