LaPOD: Latency Prediction for Real-Time LiDAR Object Detection
Xie, Wenjing Ren, Tianchi Wu, Jen-Ming Xue, Chun Jason Guan, Nan
Xie, Wenjing
Ren, Tianchi
Wu, Jen-Ming
Xue, Chun Jason
Guan, Nan
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Department
Computer Science
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Conference proceeding
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Abstract
LiDAR-based object detection is widely used in real-time systems such as autonomous vehicles and robotics. In these applications, it is essential to achieve high accuracy while ensuring detection is completed within the timing constraints. However, the latency of LiDAR-based object detection is highly variable and unpredictable, making it difficult to meet the timing constraints. To address this challenge, an essential capability needed is accurately predicting the inference latency of the LiDAR-based object detection algorithm before execution begins. Intuitively, the processing time of LiDAR-based object detection depends on the input point cloud size. However, our experiments reveal that even with the same number of input points, the processing time can still vary significantly. We analyze this phenomenon and find that the spatial distribution of points also plays a critical role in determining the inference latency. Based on these insights, we propose LaPOD, a lightweight latency predictor that rapidly estimates inference latency based on point cloud inputs. Specifically, we develop a representation to capture key features of the point cloud that influence inference latency. Moreover, LaPOD can be quickly adapted to different hardware platforms through fine-tuning with a limited number of samples. We evaluate LaPOD on the widely used KITTI dataset, demonstrating its effectiveness and robustness.
Citation
W. Xie, T. Ren, J.-M. Wu, C.J. Xue, N. Guan, "LaPOD: Latency Prediction for Real-Time LiDAR Object Detection," 2026, pp. 1049-1055.
Source
Conference
2026 31st Asia and South Pacific Design Automation Conference (ASP-DAC)
Keywords
40 Engineering, 4013 Geomatic Engineering, 46 Information and Computing Sciences, 4605 Data Management and Data Science
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Source
2026 31st Asia and South Pacific Design Automation Conference (ASP-DAC)
Publisher
IEEE