Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Learning Dense Correspondence via 3D-guided Cycle Consistency   Discriminative deep learning approaches have shown impressive results for
problems where human-labeled ground truth is plentiful, but what about tasks
where labels are difficult or impossible to obtain? This paper tackles one such
problem: establishing dense visual correspondence across different object
instances. For this task, although we do not know what the ground-truth is, we
know it should be consistent across instances of that category. We exploit this
consistency as a supervisory signal to train a convolutional neural network to
predict cross-instance correspondences between pairs of images depicting
objects of the same category. For each pair of training images we find an
appropriate 3D CAD model and render two synthetic views to link in with the
pair, establishing a correspondence flow 4-cycle. We use ground-truth
synthetic-to-synthetic correspondences, provided by the rendering engine, to
train a ConvNet to predict synthetic-to-real, real-to-real and
real-to-synthetic correspondences that are cycle-consistent with the
ground-truth. At test time, no CAD models are required. We demonstrate that our
end-to-end trained ConvNet supervised by cycle-consistency outperforms
state-of-the-art pairwise matching methods in correspondence-related tasks.

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The categories of this paper are: mtrl-th
6
The categories of this paper are: astro-ph
32
The categories of this paper are: atom-ph
0
The categories of this paper are: hep-ph
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The categories of this paper are: bayes-an
9
The categories of this paper are: nlin
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The categories of this paper are: patt-sol
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The categories of this paper are: supr-con
12
The categories of this paper are: nucl-th
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The categories of this paper are: comp-gas
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The categories of this paper are: chem-ph
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The categories of this paper are: math
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The categories of this paper are: physics
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The categories of this paper are: hep-th
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The categories of this paper are: math-ph
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The categories of this paper are: hep-lat