FPM: Fine Pose Parts-Based Model with 3D CAD Models
Author(s)Khosla, Aditya; Torralba, Antonio; Lim, Joseph Jaewhan
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We introduce a novel approach to the problem of localizing objects in an image and estimating their fine-pose. Given exact CAD models, and a few real training images with aligned models, we propose to leverage the geometric information from CAD models and appearance information from real images to learn a model that can accurately estimate fine pose in real images. Specifically, we propose FPM, a fine pose parts-based model, that combines geometric information in the form of shared 3D parts in deformable part based models, and appearance information in the form of objectness to achieve both fast and accurate fine pose estimation. Our method significantly outperforms current state-of-the-art algorithms in both accuracy and speed.
DepartmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Computer Vision – ECCV 2014
Lim, Joseph J., Aditya Khosla, and Antonio Torralba. “FPM: Fine Pose Parts-Based Model with 3D CAD Models.” Lecture Notes in Computer Science (2014): 478–493.
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