TY - INPR A1 - Rößle, Dominik A1 - Gerner, Jeremias A1 - Bogenberger, Klaus A1 - Cremers, Daniel A1 - Schmidtner, Stefanie A1 - Schön, Torsten T1 - Unlocking Past Information: Temporal Embeddings in Cooperative Bird’s Eye View Prediction N2 - 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 will be published on GitHub. UR - https://doi.org/10.48550/arXiv.2401.14325 Y1 - 2024 UR - https://doi.org/10.48550/arXiv.2401.14325 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-46123 PB - arXiv CY - Ithaca ER - TY - INPR A1 - Chandra Sekaran, Karthikeyan A1 - Geisler, Markus A1 - Rößle, Dominik A1 - Mohan, Adithya A1 - Cremers, Daniel A1 - Utschick, Wolfgang A1 - Botsch, Michael A1 - Huber, Werner A1 - Schön, Torsten T1 - UrbanIng-V2X: A Large-Scale Multi-Vehicle, Multi-Infrastructure Dataset Across Multiple Intersections for Cooperative Perception UR - https://doi.org/10.48550/arXiv.2510.23478 Y1 - 2025 UR - https://doi.org/10.48550/arXiv.2510.23478 PB - arXiv CY - Ithaca ER - TY - INPR A1 - Mohan, Adithya A1 - Rößle, Dominik A1 - Cremers, Daniel A1 - Schön, Torsten T1 - Advancing Robustness in Deep Reinforcement Learning with an Ensemble Defense Approach UR - https://doi.org/10.48550/arXiv.2507.17070 Y1 - 2025 UR - https://doi.org/10.48550/arXiv.2507.17070 PB - arXiv CY - Ithaca ER - TY - INPR A1 - Rößle, Dominik A1 - Xie, Xujun A1 - Mohan, Adithya A1 - Thirugnana Sambandham, Venkatesh A1 - Cremers, Daniel A1 - Schön, Torsten T1 - DrivIng: A Large-Scale Multimodal Driving Dataset with Full Digital Twin Integration UR - https://doi.org/10.48550/arXiv.2601.15260 Y1 - 2026 UR - https://doi.org/10.48550/arXiv.2601.15260 PB - arXiv CY - Ithaca ER -