Condensing Two-stage Detection with Automatic Object Key Part Discovery
- URL: http://arxiv.org/abs/2006.05597v3
- Date: Thu, 13 Aug 2020 01:08:50 GMT
- Title: Condensing Two-stage Detection with Automatic Object Key Part Discovery
- Authors: Zhe Chen, Jing Zhang, Dacheng Tao
- Abstract summary: Two-stage object detectors generally require excessively large models for their detection heads to achieve high accuracy.
We propose that the model parameters of two-stage detection heads can be condensed and reduced by concentrating on object key parts.
Our proposed technique consistently maintains original performance while waiving around 50% of the model parameters of common two-stage detection heads.
- Score: 87.1034745775229
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Modern two-stage object detectors generally require excessively large models
for their detection heads to achieve high accuracy. To address this problem, we
propose that the model parameters of two-stage detection heads can be condensed
and reduced by concentrating on object key parts. To this end, we first
introduce an automatic object key part discovery task to make neural networks
discover representative sub-parts in each foreground object. With these
discovered key parts, we then decompose the object appearance modeling into a
key part modeling process and a global modeling process for detection. Key part
modeling encodes fine and detailed features from the discovered key parts, and
global modeling encodes rough and holistic object characteristics. In practice,
such decomposition allows us to significantly abridge model parameters without
sacrificing much detection accuracy. Experiments on popular datasets illustrate
that our proposed technique consistently maintains original performance while
waiving around 50% of the model parameters of common two-stage detection heads,
with the performance only deteriorating by 1.5% when waiving around 96% of the
original model parameters. Codes are released on:
https://github.com/zhechen/Condensing2stageDetection.
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