Robust optimization for deep regression

Belagiannis V, Rupprecht C, Carneiro G, Navab N (2015)

Publication Type: Conference contribution

Publication year: 2015

Publisher: Institute of Electrical and Electronics Engineers Inc.

Book Volume: 2015 International Conference on Computer Vision, ICCV 2015

Pages Range: 2830-2838

Conference Proceedings Title: Proceedings of the IEEE International Conference on Computer Vision

Event location: Santiago CL

ISBN: 9781467383912

DOI: 10.1109/ICCV.2015.324

Abstract

Convolutional Neural Networks (ConvNets) have successfully contributed to improve the accuracy of regression-based methods for computer vision tasks such as human pose estimation, landmark localization, and object detection. The network optimization has been usually performed with L2 loss and without considering the impact of outliers on the training process, where an outlier in this context is defined by a sample estimation that lies at an abnormal distance from the other training sample estimations in the objective space. In this work, we propose a regression model with ConvNets that achieves robustness to such outliers by minimizing Tukey's biweight function, an M-estimator robust to outliers, as the loss function for the ConvNet. In addition to the robust loss, we introduce a coarse-to-fine model, which processes input images of progressively higher resolutions for improving the accuracy of the regressed values. In our experiments, we demonstrate faster convergence and better generalization of our robust loss function for the tasks of human pose estimation and age estimation from face images. We also show that the combination of the robust loss function with the coarse-to-fine model produces comparable or better results than current state-of-the-art approaches in four publicly available human pose estimation datasets.

Authors with CRIS profile

Vasileios Belagiannis

Involved external institutions

Technische Universität München (TUM) DE Germany (DE) University of Adelaide AU Australia (AU)

How to cite

APA:

Belagiannis, V., Rupprecht, C., Carneiro, G., & Navab, N. (2015). Robust optimization for deep regression. In Proceedings of the IEEE International Conference on Computer Vision (pp. 2830-2838). Santiago, CL: Institute of Electrical and Electronics Engineers Inc..

MLA:

Belagiannis, Vasileios, et al. "Robust optimization for deep regression." Proceedings of the 15th IEEE International Conference on Computer Vision, ICCV 2015, Santiago Institute of Electrical and Electronics Engineers Inc., 2015. 2830-2838.

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