Autonomous driving systems demand real-time, accurate perception to navigate complex environments. Addressing this, we introduce the Dynamic Router Network (DyRoNet), a framework that innovates with low-rank dynamic routing for enhanced streaming perception. By integrating specialized pre-trained branch networks, fine-tuned for various environmental conditions, DyRoNet achieves a balance between latency and precision. Its core feature, the speed router module, intelligently directs input data to the best-suited branch network, optimizing performance. The extensive evaluations reveal that DyRoNet adapts effectively to multiple branch selection strategies, setting a new benchmark in performance across a range of scenarios. DyRoNet not only establishes a new benchmark for streaming perception but also provides valuable engineering insights for future work. More project information is available at https://tastevision.github.io/DyRoNet/

翻译：自动驾驶系统需要实时、精准的感知能力以应对复杂环境。针对这一需求，我们提出动态路由器网络（DyRoNet），该框架通过创新性地采用低秩动态路由机制，实现了增强型流式感知。通过整合针对不同环境条件微调的专业化预训练分支网络，DyRoNet在延迟与精度之间取得了平衡。其核心模块——速度路由器，能够智能地将输入数据导向最适配的分支网络，从而优化性能。大量评估表明，DyRoNet可有效适配多种分支选择策略，在各类场景中树立了新的性能标杆。该工作不仅为流式感知建立了新基准，更为未来研究提供了宝贵的工程实践启示。更多项目信息请访问 https://tastevision.github.io/DyRoNet/