Xingxing Xie

2 accepted papers

2026

Does YOLO Really Need to See Every Training Image in Every Epoch?

Xingxing Xie, Jiahua Dong, Junwei Han, Gong Cheng

CVPR 2026

YOLO detectors are known for their fast inference speed, yet training them remains unexpectedly time-consuming due to their exhaustive pipeline that processes every training image in every epoch, even when many images have already been sufficiently learned. This stands in clear contrast to the effic

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2021

Oriented R-CNN for Object Detection

Xingxing Xie, Gong Cheng, Jiabao Wang, Xiwen Yao, Junwei Han

ICCV 2021poster

Current state-of-the-art two-stage detectors generate oriented proposals through time-consuming schemes. This diminishes the detectors' speed, thereby becoming the computational bottleneck in advanced oriented object detection systems. This work proposes an effective and simple oriented object detec…

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