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Deep Deformation Network for Object Landmark Localization
ECCV 2016 | We propose a cascaded framework for localizing landmarks in non-rigid objects. The first stage initializes the shape as constrained to lie within a low-rank manifold, and the second stage estimates local deformations parameterized as thin-plate spline transformations. Since our framework does not incorporate either handcrafted features or part connectivity, it is easy to train and test and generally applicable to various object types.
Collaborators: Feng Zhou, Manmohan Chandraker
