Simple Baselines for Human Pose Estimation and Tracking
Published in
European Conference on Computer Vision(2018)External Links:
TL
TL;DR
This work provides simple and effective baseline methods for pose estimation that are helpful for inspiring and evaluating new ideas for the field and achieved on challenging benchmarks.
Abstract
There has been significant progress on pose estimation and increasing interests on pose tracking in recent years. At the same time, the overall algorithm and system complexity increases as well, making the algorithm analysis and comparison more difficult. This work provides simple and effective baseline methods. They are helpful for inspiring and evaluating new ideas for the field. State-of-the-art results are achieved on challenging benchmarks. The code will be available at this https URL.
References41 items
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Pose Flow: Efficient Online Pose Tracking
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Detect-and-Track: Efficient Pose Estimation in Videos
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Cascaded Pyramid Network for Multi-person Pose Estimation
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PoseTrack: A Benchmark for Human Pose Estimation and Tracking
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