Self-Correctable and Adaptable Inference for Generalizable Human Pose Estimation

by   Zhehan Kan, et al.

A central challenge in human pose estimation, as well as in many other machine learning and prediction tasks, is the generalization problem. The learned network does not have the capability to characterize the prediction error, generate feedback information from the test sample, and correct the prediction error on the fly for each individual test sample, which results in degraded performance in generalization. In this work, we introduce a self-correctable and adaptable inference (SCAI) method to address the generalization challenge of network prediction and use human pose estimation as an example to demonstrate its effectiveness and performance. We learn a correction network to correct the prediction result conditioned by a fitness feedback error. This feedback error is generated by a learned fitness feedback network which maps the prediction result to the original input domain and compares it against the original input. Interestingly, we find that this self-referential feedback error is highly correlated with the actual prediction error. This strong correlation suggests that we can use this error as feedback to guide the correction process. It can be also used as a loss function to quickly adapt and optimize the correction network during the inference process. Our extensive experimental results on human pose estimation demonstrate that the proposed SCAI method is able to significantly improve the generalization capability and performance of human pose estimation.


page 7

page 8


Self-Constrained Inference Optimization on Structural Groups for Human Pose Estimation

We observe that human poses exhibit strong group-wise structural correla...

Human Pose Estimation with Iterative Error Feedback

Hierarchical feature extractors such as Convolutional Networks (ConvNets...

Pose Trainer: Correcting Exercise Posture using Pose Estimation

Fitness exercises are very beneficial to personal health and fitness; ho...

Deep Learning for Fitness

We present Fitness tutor, an application for maintaining correct posture...

Mirror, mirror on the wall, tell me, is the error small?

Do object part localization methods produce bilaterally symmetric result...

Online Monitoring for Neural Network Based Monocular Pedestrian Pose Estimation

Several autonomy pipelines now have core components that rely on deep le...

Heatmap Distribution Matching for Human Pose Estimation

For tackling the task of 2D human pose estimation, the great majority of...

Please sign up or login with your details

Forgot password? Click here to reset