With the vigorous development of computer vision, oriented object detection has gradually been featured. In this paper, a novel differentiable angle coder named phase-shifting coder (PSC) is proposed to accurately predict the orientation of objects, along with a dual-frequency version (PSCD). By mapping the rotational periodicity of different cycles into the phase of different frequencies, we provide a unified framework for various periodic fuzzy problems caused by rotational symmetry in oriented object detection. Upon such a framework, common problems in oriented object detection such as boundary discontinuity and square-like problems are elegantly solved in a unified form. Visual analysis and experiments on three datasets prove the effectiveness and the potentiality of our approach. When facing scenarios requiring high-quality bounding boxes, the proposed methods are expected to give a competitive performance. The codes are publicly available at https://github.com/open-mmlab/mmrotate.

翻译：随着计算机视觉的蓬勃发展，旋转目标检测逐渐受到关注。本文提出一种名为相位编码器（PSC）的新型可微分角度编码器，用于精确预测目标的朝向，同时提出其双频版本（PSCD）。通过将不同周期的旋转周期性映射为不同频率的相位，我们为旋转目标检测中由旋转对称性导致的各种周期性模糊问题提供了统一框架。在此框架下，旋转目标检测中的常见问题（如边界不连续性和方块问题）得以以统一形式优雅解决。对三个数据集的可视化分析与实验证明了我们方法的有效性与潜力。在需要高质量边界框的场景中，所提方法有望展现竞争性性能。相关代码已开源至 https://github.com/open-mmlab/mmrotate。