Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Dynamic Kernel Distillation for Efficient Pose Estimation in Videos   Existing video-based human pose estimation methods extensively apply large
networks onto every frame in the video to localize body joints, which suffer
high computational cost and hardly meet the low-latency requirement in
realistic applications. To address this issue, we propose a novel Dynamic
Kernel Distillation (DKD) model to facilitate small networks for estimating
human poses in videos, thus significantly lifting the efficiency. In
particular, DKD introduces a light-weight distillator to online distill pose
kernels via leveraging temporal cues from the previous frame in a one-shot
feed-forward manner. Then, DKD simplifies body joint localization into a
matching procedure between the pose kernels and the current frame, which can be
efficiently computed via simple convolution. In this way, DKD fast transfers
pose knowledge from one frame to provide compact guidance for body joint
localization in the following frame, which enables utilization of small
networks in video-based pose estimation. To facilitate the training process,
DKD exploits a temporally adversarial training strategy that introduces a
temporal discriminator to help generate temporally coherent pose kernels and
pose estimation results within a long range. Experiments on Penn Action and
Sub-JHMDB benchmarks demonstrate outperforming efficiency of DKD, specifically,
10x flops reduction and 2x speedup over previous best model, and its
state-of-the-art accuracy.

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The categories of this paper are: cmp-lg
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The categories of this paper are: q-alg
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The categories of this paper are: chao-dyn
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The categories of this paper are: physics
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The categories of this paper are: q-bio
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The categories of this paper are: chem-ph
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The categories of this paper are: eess
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The categories of this paper are: stat
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The categories of this paper are: nucl-th
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The categories of this paper are: dg-ga
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The categories of this paper are: plasm-ph
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The categories of this paper are: mtrl-th
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The categories of this paper are: atom-ph
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The categories of this paper are: bayes-an
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The categories of this paper are: hep-ph
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The categories of this paper are: gr-qc