Face Recognition via Sparse Representation
Welcome! This website introduces a new mathematical framework for classification and recognition problems in computer vision, especially face recognition. The basic idea is to cast recognition as a sparse representation problem, utilizing new mathematical tools from compressed sensing and L1 minimization. This leads to highly robust, scalable algorithms for face recognition based on linear or conv
Aaron Hertzmann
Aaron Hertzmann Principal Scientist, Adobe Research San Francisco, CA ACM Fellow (About), IEEE Fellow Affiliate Professor, University of Washington Editor-in-Chief, FnTCG&V aaron.hertzmann at gmail SIGGRAPH Award Talk: My journey in art and computing [Text/links] Selected recent papers on human vision and art Per-Fixation Perspective in Scientific Reports, 2025 [Paper] Perspective in Drawings, Pho
Andy Wilson at Microsoft Research
About I am a partner researcher at Microsoft Research (opens in new tab). I study ways to apply sensing techniques, signal processing and display technologies to enable new modes of human-computer interaction. These days I am focused on interactive multimodal systems, generative AI techniques to create virtual worlds, ubiquitous computing, and mixed reality. I obtained my BA at Cornell University,
Yann LeCun's Home Page
Yann LeCun, Chief AI Scientist, Meta Jacob T. Schwartz Professor of Computer Science, Data Science, Neural Science, and Electrical and Computer Engineering, New York University. ACM Turing Award Laureate, (sounds like I'm bragging, but a condition of accepting the award is to write this next to your name) Member, National Academy of Engineering, National Academy of Sciences, Académie des Sciences
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Lawrence Saul
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Ashutosh Saxena -- Microsoft and Sloan Fellow, Computer Science, Stanford University
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Machine Learning and Perception
Lawrence Saul