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SDF-SRN: Learning Signed Distance 3D Object Reconstruction from Static Images
Dense 3D object reconstruction from a single image has recently witnesse...
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Deep NRSfM++: Towards 3D Reconstruction in the Wild
The recovery of 3D shape and pose solely from 2D landmarks stemming from...
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Photometric Mesh Optimization for Video-Aligned 3D Object Reconstruction
In this paper, we address the problem of 3D object mesh reconstruction f...
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ST-GAN: Spatial Transformer Generative Adversarial Networks for Image Compositing
We address the problem of finding realistic geometric corrections to a f...
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Semantic Photometric Bundle Adjustment on Natural Sequences
The problem of obtaining dense reconstruction of an object in a natural ...
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Object-Centric Photometric Bundle Adjustment with Deep Shape Prior
Reconstructing 3D shapes from a sequence of images has long been a probl...
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Learning Efficient Point Cloud Generation for Dense 3D Object Reconstruction
Conventional methods of 3D object generative modeling learn volumetric p...
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Deep-LK for Efficient Adaptive Object Tracking
In this paper we present a new approach for efficient regression based o...
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Inverse Compositional Spatial Transformer Networks
In this paper, we establish a theoretical connection between the classic...
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The Conditional Lucas & Kanade Algorithm
The Lucas & Kanade (LK) algorithm is the method of choice for efficient ...
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