For ImageNet localization, the authors observed that images usually contain one dominant object and RPN proposals overlap heavily, producing very similar RoI-pooled features. They argue that image-centric Fast R-CNN therefore yields low-variation stochastic samples, and use the original RoI-centric R-CNN instead.

For ImageNet localization, the authors observed that images usually contain one dominant object and RPN proposals overlap heavily, producing very similar RoI-pooled features. They argue that image-centric Fast R-CNN therefore yields low-variation stochastic samples, and use the original RoI-centric R-CNN instead. · CiteArk

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