Computer Vision – StAR Lecture Series: Object Recognition
The state-of-the-art in object recognition has undergone dramatic changes in the last 20 years. In this talk, I will review the progression of the field and discuss why various approaches both succeeded and failed. The talk will cover visual recognition from the early 90’s, including handwritten digit and face detection, to the current state-of-the-art in deep learning applied to object categorization. Algorithms will be explained at an intuitive level. The talk is aimed at the non-expert in computer vision with some knowledge of machine learning. While deep learning is briefly covered, Ross Girshick will be giving a more detailed StAR talk on the subject at a later date.
Speaker Details
C. Lawrence Zitnick is a senior researcher in the Interactive Visual Media group at Microsoft Research, and is an affiliate associate professor at the University of Washington. He is interested in a broad range of topics related to visual object recognition. His current interests include object detection and semantically interpreting visual scenes. He developed the PhotoDNA technology used by Microsoft, Facebook, Google, and various law enforcement agencies to combat illegal imagery on the web. Before joining MSR, he received the PhD degree in robotics from Carnegie Mellon University in 2003. In 1996, he co-invented one of the first commercial portable depth cameras.
- Series:
- Microsoft Research Talks
- Date:
- Speakers:
- Larry Zitnick
- Affiliation:
- MSR
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Jeff Running
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Larry Zitnick
Principal Researcher
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Series: Microsoft Research Talks
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- Phil Bernstein
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From SqueezeNet to SqueezeBERT: Developing Efficient Deep Neural Networks
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Hope Speech and Help Speech: Surfacing Positivity Amidst Hate
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'F' to 'A' on the N.Y. Regents Science Exams: An Overview of the Aristo Project
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Checkpointing the Un-checkpointable: the Split-Process Approach for MPI and Formal Verification
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Learning Structured Models for Safe Robot Control
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