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(2) In future presentations of the research findings, in addition to the course project website and public presentations, your real name and personal information will not appear in this research report. If you are interested in the research results, we can provide you with an executive summary after the study is completed.
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Uedu Open / Machine Learning for Inverse Graphics
6.S980

Machine Learning for Inverse Graphics

Prof. Vincent Sitzmann | Fall 2022
Data Science, Analytics & Computer Technology AI Machine Learning Visualization Computer Science Engineering Artificial Intelligence Graphics and Visualization
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CC BY-NC-SA 4.0
課程簡介
This course covers fundamental and advanced techniques in this field at the intersection of computer vision, computer graphics, and geometric deep learning. It will lay the foundations of how cameras see the world, how we can represent 3D scenes for artificial intelligence, how we can learn to reconstruct these representations from only a single image, how we can guarantee certain kinds of generalizations, and how we can train these models in a self-supervised way.
Course Information
SourceMIT 開放式課程
科系Electrical Engineering and Computer Science
LanguageEnglish
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