Simple Baselines for Human Pose Estimation and Tracking

ECCV 2018  ·  Bin Xiao, Haiping Wu, Yichen Wei ·

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 https://github.com/leoxiaobin/pose.pytorch.

PDF Abstract ECCV 2018 PDF ECCV 2018 Abstract
Task Dataset Model Metric Name Metric Value Global Rank Result Benchmark
Pose Estimation AIC SimpleBaseline (ResNet-101) AP 29.4 # 9
AP50 73.6 # 5
AP75 17.4 # 6
AR 33.7 # 6
AR50 76.3 # 6
Keypoint Detection COCO test-challenge Simple Base+* AR 80.5 # 3
ARM 75.3 # 3
AP 74.5 # 3
AP50 90.9 # 3
AP75 80.8 # 3
APL 87.5 # 2
AR50 95.1 # 3
AR75 86.3 # 3
ARL 82.9 # 3
Keypoint Detection COCO test-dev Simple Base APL 80.0 # 6
APM 70.3 # 5
AP50 91.9 # 5
AP75 81.1 # 5
AR 79.0 # 5
Pose Estimation COCO test-dev Flow-based (ResNet-152) AP 73.7 # 24
AP50 91.9 # 18
AP75 81.1 # 21
APL 80 # 16
APM 70.3 # 21
AR 79 # 20
Keypoint Detection COCO test-dev Simple Base+* APL 82.7 # 2
APM 73.0 # 2
AP50 92.4 # 4
AP75 84.0 # 2
AR 81.5 # 3
AR50 95.8 # 2
AR75 88.2 # 1
ARL 87.2 # 1
ARM 77.4 # 2
Multi-Person Pose Estimation CrowdPose Simple baseline mAP @0.5:0.95 60.8 # 18
AP Easy 71.4 # 14
AP Medium 61.2 # 17
AP Hard 51.2 # 15
Keypoint Detection MS COCO ResNet-50 Validation AP 72.2 # 10
Pose Estimation OCHuman ResNet-152 Test AP 33.3 # 8
Validation AP 41.0 # 7
Keypoint Detection OCHuman ResNet-50 Test AP 29.5 # 7
Validation AP 32.1 # 7
Keypoint Detection OCHuman ResNet-152 Test AP 33.3 # 4
Validation AP 41.0 # 3
2D Human Pose Estimation OCHuman ResNet-50 Test AP 30.4 # 8
Validation AP 37.8 # 6
2D Human Pose Estimation OCHuman ResNet-152 Test AP 33.3 # 5
Validation AP 41.0 # 3
Pose Estimation OCHuman ResNet-50 Test AP 29.5 # 11
Validation AP 32.1 # 11
Pose Tracking PoseTrack2017 MSRA (FlowTrack) MOTA 57.81 # 5
mAP 74.57 # 2
Pose Tracking PoseTrack2018 MSRA MOTA 61.37 # 4
mAP 74.03 # 1

Results from Other Papers


Task Dataset Model Metric Name Metric Value Rank Source Paper Compare
Pose Estimation AIC SimpleBaseline (ResNet-152) AP 29.9 # 8
AP50 73.8 # 4
AP75 18.3 # 5
AR 34.3 # 5
AR50 76.9 # 5
Pose Estimation AIC SimpleBaseline (ResNet-50) AP 28.0 # 10
AP50 71.6 # 6
AP75 15.8 # 7
AR 32.1 # 7
AR50 74.1 # 7
2D Human Pose Estimation JHMDB (2D poses only) SimplePose PCK 94.4 # 2
Multi-Person Pose Estimation OCHuman SimplePose Validation AP 24.1 # 6
AP50 37.4 # 7
AP75 26.8 # 7

Methods