Learning Rotation-Invariant and Fisher Discriminative Convolutional Neural Networks for Object Detection

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
Gong ChengDong Xu

Abstract

The performance of object detection has recently been significantly improved due to the powerful features learnt through convolutional neural networks (CNNs). Despite the remarkable success, there are still several major challenges in object detection, including object rotation, within-class diversity, and between-class similarity, which generally degenerate object detection performance. To address these issues, we build up the existing state-of-the-art object detection systems and propose a simple but effective method to train rotation-invariant and Fisher discriminative CNN models to further boost object detection performance. This is achieved by optimizing a new objective function that explicitly imposes a rotation-invariant regularizer and a Fisher discrimination regularizer on the CNN features. Specifically, the first regularizer enforces the CNN feature representations of the training samples before and after rotation to be mapped closely to each other in order to achieve rotation-invariance. The second regularizer constrains the CNN features to have small within-class scatter but large between-class separation. We implement our proposed method under four popular object detection frameworks, including region-CNN (R-CNN), ...Continue Reading

References

Jul 17, 2010·IEEE Transactions on Pattern Analysis and Machine Intelligence·Pedro F FelzenszwalbDeva Ramanan
Sep 10, 2015·IEEE Transactions on Pattern Analysis and Machine Intelligence·Kaiming HeJian Sun
Dec 15, 2015·IEEE Transactions on Pattern Analysis and Machine Intelligence·Ross GirshickJitendra Malik
Aug 3, 2016·IEEE Transactions on Pattern Analysis and Machine Intelligence· Jin Xie Yi Fang
Aug 20, 2016·IEEE Transactions on Pattern Analysis and Machine Intelligence· Shaoqing Ren Jian Sun
Jan 6, 2017·IEEE Transactions on Cybernetics·Jin XieYi Fang
Jan 17, 2017·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Jin XieYi Fang
Oct 11, 2017·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society· Gong Cheng Junwei Han
Jan 13, 2018·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Junwei HanFeiping Nie

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Citations

Nov 19, 2020·Sensors·Delia-Georgiana StuparuCiprian Dobre

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