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Mask2CAD: 3D Shape Prediction by Learning to Segment and Retrieve
[article]
2020
arXiv
pre-print
Object recognition has seen significant progress in the image domain, with focus primarily on 2D perception. We propose to leverage existing large-scale datasets of 3D models to understand the underlying 3D structure of objects seen in an image by constructing a CAD-based representation of the objects and their poses. We present Mask2CAD, which jointly detects objects in real-world images and for each detected object, optimizes for the most similar CAD model and its pose. We construct a joint
arXiv:2007.13034v1
fatcat:yabpz6uoczdhtopk2fmmfkwqq4