Paper

Tackling Two Challenges of 6D Object Pose Estimation: Lack of Real Annotated RGB Images and Scalability to Number of Objects

State-of-the-art methods for 6D object pose estimation typically train a Deep Neural Network per object, and its training data first comes from a 3D object mesh. Models trained with synthetic data alone do not generalise well, and training a model for multiple objects sharply drops its accuracy... (read more)

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