Accurate and comprehensive semantic segmentation of Bird's Eye View (BEV) is essential for ensuring safe and proactive navigation in autonomous driving. Although cooperative perception has exceeded the detection capabilities of single-agent systems, prevalent camera-based algorithms in cooperative perception neglect valuable information derived from historical observations. This limitation becomes critical during sensor failures or communication issues as cooperative perception reverts to single-agent perception, leading to degraded performance and incomplete BEV segmentation maps. This paper introduces TempCoBEV, a temporal module designed to incorporate historical cues into current observations, thereby improving the quality and reliability of BEV map segmentations. We propose an importance-guided attention architecture to effectively integrate temporal information that prioritizes relevant properties for BEV map segmentation. TempCoBEV is an independent temporal module that seamlessly integrates into state-of-the-art camera-based cooperative perception models. We demonstrate through extensive experiments on the OPV2V dataset that TempCoBEV performs better than non-temporal models in predicting current and future BEV map segmentations, particularly in scenarios involving communication failures. We show the efficacy of TempCoBEV and its capability to integrate historical cues into the current BEV map, improving predictions under optimal communication conditions by up to 2% and under communication failures by up to 19%. The code is available at https://github.com/cvims/TempCoBEV

翻译：准确而全面的鸟瞰图语义分割对于确保自动驾驶的安全性和前瞻性导航至关重要。尽管协同感知已超越单智能体系统的检测能力，但当前主流的基于摄像头的协同感知算法忽略了从历史观测中获取的宝贵信息。这一局限在传感器故障或通信中断时变得尤为关键，因为协同感知会退化为单智能体感知，导致性能下降和鸟瞰图分割不完整。本文提出TempCoBEV，一种旨在将历史线索融入当前观测的时序模块，从而提升鸟瞰图分割的质量与可靠性。我们设计了一种重要性引导的注意力架构，以有效整合时序信息，并优先考虑对鸟瞰图分割相关的关键特征。TempCoBEV是一个独立的时序模块，可无缝集成到最先进的基于摄像头的协同感知模型中。通过在OPV2V数据集上的大量实验，我们证明TempCoBEV在预测当前及未来鸟瞰图分割方面优于非时序模型，尤其在涉及通信故障的场景中。我们展示了TempCoBEV的有效性及其将历史线索融入当前鸟瞰图的能力，在最优通信条件下可将预测精度提升高达2%，在通信故障时提升高达19%。代码发布于https://github.com/cvims/TempCoBEV