R-FCN-3000 at 30fps: Decoupling Detection and Classification
论文地址：R-FCN-3000 at 30fps: Decoupling Detection and Classification 概述： 【导读】美国马里兰大学、复旦大学和Gobasco人工智能实验室联合提出R-FCN-3000实时3000类目标检测框架，对R-FCN框架中的物体检测和分类进行解耦。本文对R-FCN体系结构进行修改，其中位置敏感滤波器在不同的目标类之间共享来进行定位。对于细粒度的
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相关文章
- 1. 【R-FCN-3000】《R-FCN-3000 at 30fps: Decoupling Detection and Classification》
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