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Learning RoI Transformer for Oriented Object Detection in ...

Learning RoI Transformer for Oriented Object Detection in Aerial ImagesJian Ding, Nan Xue, Yang Long, Gui-Song Xia , Qikai LuLIESMARS-CAPTAIN, Wuhan University, Wuhan, 430079, China{ , xuenan, longyang, , Detection in aerial images is an active yet chal-lenging task in computer vision because of the bird s-eyeview perspective, the highly complex backgrounds, and thevariant appearances of objects. Especially when detectingdensely packed objects in aerial images, methods relying onhorizontal proposals for common Object Detection often in-troduce mismatches between the Region of Interests (RoIs)and objects. This leads to the common misalignment be-tween the final Object classification confidence and local-ization accuracy.}

avoid a large number of anchors designed for oriented object detection. • We design a Rotated Position Sensitive RoI Align-ment module for spatially invariant feature extraction, which can effectively boost the object classification andlocationregression. Themoduleisacrucialdesign when using the light-head RoI-wise operation, which

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  Design, Object, Oriented, Object oriented

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