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About Computer Vision:: From 3D Reconstruction To Recognition
This document provides an overview of the CS231A Computer Vision course at Stanford University. The course covers two main areas: 1) Space/Geometry, which involves estimating spatial properties of objects and scenes from images using geometric methods, and 2) Semantics/Learning, which involves estimating semantic and dynamic properties through learning methods. The syllabus outlines 16 lectures covering topics like camera models, calibration, 3D reconstruction, tracking, SLAM, representation learning, and applications in areas like robotics, augmented reality, and autonomous systems. Prerequisites include knowledge of linear algebra, probability, statistics, machine learning and basic computer vision and programming skills.
Detailed Information
| Author: | ['Nono Nono'] |
|---|---|
| Publication Year: | 2022 |
| Pages: | 55 |
| Language: | English |
| Format: | |
| Price: | FREE |
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