
Common Objects in 3D: LargeScale Learning and Evaluation of Reallife 3D Category Reconstruction
Traditional approaches for learning 3D object categories have been predo...
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DensePose 3D: Lifting Canonical Surface Maps of Articulated Objects to the Third Dimension
We tackle the problem of monocular 3D reconstruction of articulated obje...
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Discovering Relationships between Object Categories via Universal Canonical Maps
We tackle the problem of learning the geometry of multiple categories of...
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NeuroMorph: Unsupervised Shape Interpolation and Correspondence in One Go
We present NeuroMorph, a new neural network architecture that takes as i...
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Unsupervised Learning of 3D Object Categories from Videos in the Wild
Our goal is to learn a deep network that, given a small number of images...
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Continuous Surface Embeddings
In this work, we focus on the task of learning and representing dense co...
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RidgeSfM: Structure from Motion via Robust Pairwise Matching Under Depth Uncertainty
We consider the problem of simultaneously estimating a dense depth map a...
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3D Multibodies: Fitting Sets of Plausible 3D Human Models to Ambiguous Image Data
We consider the problem of obtaining dense 3D reconstructions of humans ...
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Canonical 3D Deformer Maps: Unifying parametric and nonparametric methods for dense weaklysupervised category reconstruction
We propose the Canonical 3D Deformer Map, a new representation of the 3D...
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Accelerating 3D Deep Learning with PyTorch3D
Deep learning has significantly improved 2D image recognition. Extending...
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C3DPO: Canonical 3D Pose Networks for NonRigid Structure From Motion
We propose C3DPO, a method for extracting 3D models of deformable object...
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Semiconvolutional Operators for Instance Segmentation
Object detection and instance segmentation are dominated by regionbased...
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Selfsupervised Learning of Geometrically Stable Features Through Probabilistic Introspection
Selfsupervision can dramatically cut back the amount of manuallylabell...
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Learning 3D Object Categories by Looking Around Them
Traditional approaches for learning 3D object categories use either synt...
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Learning the semantic structure of objects from Web supervision
While recent research in image understanding has often focused on recogn...
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Cascaded Sparse Spatial Bins for Efficient and Effective Generic Object Detection
A novel efficient method for extraction of object proposals is introduce...
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Understanding the Fisher Vector: a multimodal part model
Fisher Vectors and related orderless visual statistics have demonstrated...
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David Novotny
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