7 Result(s)
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Chapter and Conference Paper
Learning to Look around Objects for Top-View Representations of Outdoor Scenes
Given a single RGB image of a complex outdoor road scene in the perspective view, we address the novel problem of estimating an occlusion-reasoned semantic scene layout in the top-view. This challenging proble...
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Chapter and Conference Paper
Materials for Masses: SVBRDF Acquisition with a Single Mobile Phone Image
We propose a material acquisition approach to recover the spatially-varying BRDF and normal map of a near-planar surface from a single image captured by a handheld mobile phone camera. Our method images the su...
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Chapter and Conference Paper
Hierarchical Metric Learning and Matching for 2D and 3D Geometric Correspondences
Interest point descriptors have fueled progress on almost every problem in computer vision. Recent advances in deep neural networks have enabled task-specific learned descriptors that outperform hand-crafted d...
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Chapter and Conference Paper
Deep Deformation Network for Object Landmark Localization
We propose a novel cascaded framework, namely deep deformation network (DDN), for localizing landmarks in non-rigid objects. The hallmarks of DDN are its incorporation of geometric constraints within a convolu...
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Chapter and Conference Paper
A 4D Light-Field Dataset and CNN Architectures for Material Recognition
We introduce a new light-field dataset of materials, and take advantage of the recent success of deep learning to perform material recognition on the 4D light-field. Our dataset contains 12 material categories...
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Chapter and Conference Paper
On Shape and Material Recovery from Motion
We present a framework for the joint recovery of the shape and reflectance of an object with dichromatic BRDF, using motion cues. We show that four (small or differential) motions of the object, or three motio...
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Article
Open AccessGlobally Optimal Algorithms for Stratified Autocalibration
We present practical algorithms for stratified autocalibration with theoretical guarantees of global optimality. Given a projective reconstruction, we first upgrade it to affine by estimating the position of t...
