Abstract: Addressing the time-consuming issue of mainstream keypoint detection algorithms, a novel keypoint detection and description method is proposed. First, the rotating pixel difference convolution module is designed to symmetrically sample differential information from images. This module is further extended to implement the judger module that integrates sampled differential and convolutional information, effectively extracting features from the raw image. Finally, shared encoder and lightweight decoder, which coordinates information between decoders, are designed, while improving the loss function to construct an efficient encoder-decoder network model. Experimental results demonstrate that the proposed method maintains favorable real-time performance while achieving high computational accuracy, providing a solution that balances real-time capability and precision for applications such as image matching and visual localization.