FC-TrackNet:用于合成域6D姿态跟踪的快速收敛网络

Proceedings of the ... AAAI Conference on Artificial Intelligence. AAAI Conference on Artificial Intelligence Pub Date : 2023-06-26 DOI:10.1609/aaai.v37i13.27077

Di Jia, Qianqian Wang, Jun Cao, Peng Cai, Zhiyang Jin

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引用次数: 0

摘要

在这项工作中，我们提出了一种基于综合数据驱动方法的快速收敛跟踪网络，或FC-TrackNet，以维持长期的6D姿态跟踪。在两个不同的数据集上进行了对比实验，结果表明，我们的方法可以实现90.9 Hz的一致跟踪频率，并且比目前的方法具有更高的精度。

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FC-TrackNet: Fast Convergence Net for 6D Pose Tracking in Synthetic Domains

In this work, we propose a fast convergence track net, or FC-TrackNet, based on a synthetic data-driven approach to maintaining long-term 6D pose tracking. Comparison experiments are performed on two different datasets, The results demonstrate that our approach can achieve a consistent tracking frequency of 90.9 Hz as well as higher accuracy than the state-of-the art approaches.

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Proceedings of the ... AAAI Conference on Artificial Intelligence. AAAI Conference on Artificial Intelligence

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