Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Slim DensePose: Thrifty Learning from Sparse Annotations and Motion Cues   DensePose supersedes traditional landmark detectors by densely mapping image
pixels to body surface coordinates. This power, however, comes at a greatly
increased annotation time, as supervising the model requires to manually label
hundreds of points per pose instance. In this work, we thus seek methods to
significantly slim down the DensePose annotations, proposing more efficient
data collection strategies. In particular, we demonstrate that if annotations
are collected in video frames, their efficacy can be multiplied for free by
using motion cues. To explore this idea, we introduce DensePose-Track, a
dataset of videos where selected frames are annotated in the traditional
DensePose manner. Then, building on geometric properties of the DensePose
mapping, we use the video dynamic to propagate ground-truth annotations in time
as well as to learn from Siamese equivariance constraints. Having performed
exhaustive empirical evaluation of various data annotation and learning
strategies, we demonstrate that doing so can deliver significantly improved
pose estimation results over strong baselines. However, despite what is
suggested by some recent works, we show that merely synthesizing motion
patterns by applying geometric transformations to isolated frames is
significantly less effective, and that motion cues help much more when they are
extracted from videos.

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The categories of this paper are: dg-ga
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The categories of this paper are: stat
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The categories of this paper are: q-bio
34
The categories of this paper are: chem-ph
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The categories of this paper are: chao-dyn
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The categories of this paper are: atom-ph
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The categories of this paper are: econ
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The categories of this paper are: comp-gas
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The categories of this paper are: q-fin
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The categories of this paper are: cond-mat
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The categories of this paper are: math
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The categories of this paper are: quant-ph
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The categories of this paper are: gr-qc
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The categories of this paper are: plasm-ph
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The categories of this paper are: eess
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The categories of this paper are: patt-sol