SIMMKD: Simple Mask-Flow Keypoint Detection for Both Typhoon Detection and Typhoon Eye Location

Recently, deep learning-based methods has gained increasing attention in typhoon tasks. Due to different optimization targets, existing works apply multi-object detection to typhoon detection and keypoint detection to typhoon eye location. However, such two-stage methods ignored the internal connection between tasks in this special scenario, leading to complexity and time consumption. Therefore, we propose Simple Mask-Flow Keypoint Detection(SimMKD), a unified framework for two typhoon tasks that optimizes different targets uniformly. In SimMKD, our Mask-Flow mechanism simplifies typhoon detection from a multi-object into single-object detection tasks in turn, while our Hierarchic Keypoint Detection (HKD) model reformulates it as a two-point detection task, then merged with typhoon eye location task. Hence two different tasks are simplified and integrated as a single keypoint detection task. Furthermore, we publish the Multi-object Typhoon Eye Dataset (MTED), which meets more task requirements. Extensive experimental results show that the SimMKD can achieve new SOTA on existing datasets.
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