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In this paper, we propose a radio-assisted human detection framework by incorporating radio information into the state-of-the-art detection methods, including anchor-based one-stage detectors and two-stage detectors. We extract the radio localization and identifier information from the radio signals to assist the human detection, due to which the problem of false positives and false negatives can be greatly alleviated. For both detectors, we use the confidence score revision based on the radio localization to improve the detection performance. For two-stage detection methods, we propose to utilize the region proposals generated from radio localization rather than relying on region proposal network (RPN). Moreover, with the radio identifier information, a non-max suppression method with the radio localization constraint has also been proposed to further suppress the false detections and reduce miss detections …