Abstract
While most steps in the modern object detection methods are learnable, the
region feature extraction step remains largely hand-crafted, featured by RoI
pooling methods. This work proposes a general viewpoint that unifies existing
region feature extraction methods and a novel method that is end-to-end
learnable. The proposed method removes most heuristic choices and outperforms
its RoI pooling counterparts. It moves further towards fully learnable object
detection.
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