Learning 3D object categories by looking around them
Traditional approaches for learning 3D object categories use either synthetic data or manual supervision. In this paper, we propose a method which does not require manual annotations and is instead cued by observing objects from a moving vantage point. Our system builds on two innovations: a Siamese...
| Main Authors: | , , |
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| Formato: | Conference item |
| Idioma: | English |
| Publicado em: |
IEEE
2017
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