Learning 1-Bit LiDAR-based Localization with Auxiliary Objective
6-DoF LiDAR-based localization is a fundamental capability for autonomous systems operating in large-scale outdoor environments. Many deep-learning-based localization methods have achieved promising performance so far. However, as one of the always-on modules competing for limited on-board computational resources, the localization module is expected to consume only a small portion of the overall compute budget. Most existing learning-based methods are still too heavy for this purpose. In contrast, binary neural networks (BNNs) offer an appealing solution, but the 1-bit compression causes severe information loss and performance drop. In this paper, we address this challenge by proposing Bi...
| Authors | Kaijie Yin, Zhiyuan Zhang, Tian Gao et al. |
|---|---|
| Primary category | cs.CV |
| Published | 26 June 2026 |
| Last updated at source | 22 September 2026 |
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