Diff-Net: Image Feature Difference based High-Definition Map Change Detection

• URL: http://arxiv.org/abs/2107.07030v1
• Date: Wed, 14 Jul 2021 22:51:30 GMT
• Title: Diff-Net: Image Feature Difference based High-Definition Map Change Detection
• Authors: Lei He and Shengjie Jiang and Xiaoqing Liang and Ning Wang and Shiyu Song
• Abstract summary: Up-to-date High-Definition (HD) maps are essential for self-driving cars. We present a deep neural network (DNN), Diff-Net, to detect changes in them. Results demonstrate that our Diff-Net achieves better performance than the baseline methods and is ready to be integrated into a map production maintaining an up-to-date HD map.
• Score: 13.666189678747996
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Up-to-date High-Definition (HD) maps are essential for self-driving cars. To achieve constantly updated HD maps, we present a deep neural network (DNN), Diff-Net, to detect changes in them. Compared to traditional methods based on object detectors, the essential design in our work is a parallel feature difference calculation structure that infers map changes by comparing features extracted from the camera and rasterized images. To generate these rasterized images, we project map elements onto images in the camera view, yielding meaningful map representations that can be consumed by a DNN accordingly. As we formulate the change detection task as an object detection problem, we leverage the anchor-based structure that predicts bounding boxes with different change status categories. Furthermore, rather than relying on single frame input, we introduce a spatio-temporal fusion module that fuses features from history frames into the current, thus improving the overall performance. Finally, we comprehensively validate our method's effectiveness using freshly collected datasets. Results demonstrate that our Diff-Net achieves better performance than the baseline methods and is ready to be integrated into a map production pipeline maintaining an up-to-date HD map.

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