activity
20232026
collaborators

8 papers

cs.AI2026

Wavelet Phase Diffusion for Structurally and Semantically Consistent Sim-to-Real Translation

Kaiwen Wang, Frank Bieder, Yinzhe Shen +3

Simulation-to-reality translation must bridge the appearance gap between synthetic and real domains while preserving structural and semantic consistency. Conditioning-based methods…

cs.CV2026

Creating Impactful Autonomous Driving Datasets: A Strategic Guide from Research Gap to Benchmark

Richard Schwarzkopf, Jonas Merkert, Frank Bieder +22

Well-designed autonomous driving datasets have fundamentally shaped research progress, yet existing literature primarily describes what datasets contain rather than how to strategi…

cs.CV2026

The Road Ahead in Autonomous Driving: The KITScenes Multimodal Dataset

Richard Schwarzkopf, Fabian Immel, Alexander Blumberg +21

Existing autonomous driving datasets have enabled major progress, but fall short in sensor fidelity, map completeness, or geographic diversity. We present KITScenes Multimodal, a E…

cs.RO2026

Mosaic: An Extensible Framework for Composing Rule-Based and Learned Motion Planners

Nick Le Large, Marlon Steiner, Lingguang Wang +4

Safe and explainable motion planning remains a central challenge in autonomous driving. While rule-based planners offer predictable and explainable behavior, they often fail to gra…

cs.CV2024

SceneMotion: From Agent-Centric Embeddings to Scene-Wide Forecasts

Royden Wagner, Ömer Sahin Tas, Marlon Steiner +5

Self-driving vehicles rely on multimodal motion forecasts to effectively interact with their environment and plan safe maneuvers. We introduce SceneMotion, an attention-based model…

cs.LG2024

Words in Motion: Extracting Interpretable Control Vectors for Motion Transformers

Omer Sahin Tas, Royden Wagner

Transformer-based models generate hidden states that are difficult to interpret. In this work, we analyze hidden states and modify them at inference, with a focus on motion forecas…