Beyond spatial pooling: Fine-grained representation learning in multiple domains

Abstract

Object recognition systems have shown great progress over recent years. However, creating object representations that are robust to changes in viewpoint while capturing local visual details continues to be a challenge. In particular, recent convolutional architectures employ spatial pooling to achieve scale and shift invariances, but they are still… (More)
DOI: 10.1109/CVPR.2015.7299125

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@article{Li2015BeyondSP, title={Beyond spatial pooling: Fine-grained representation learning in multiple domains}, author={Chi Li and Austin Reiter and Gregory D. Hager}, journal={2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, year={2015}, pages={4913-4922} }