6 papers · 1 filter
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…
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…
Reasoning models do not yet follow their reasoning in autonomous driving: The KITScenes LongTail Dataset
Royden Wagner, Omer Sahin Tas, Jaime Villa +20
Handling rare events is the central open challenge in autonomous driving. Reasoning models, which generate explicit chains of reasoning before acting, promise to generalize to such…
RetroMotion: Retrocausal Motion Forecasting Models are Instructable
Royden Wagner, Omer Sahin Tas, Felix Hauser +7
Motion forecasts of road users (i.e., agents) vary in complexity depending on the number of agents, scene constraints, and interactions. In particular, the output space of joint tr…
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…
JointMotion: Joint Self-Supervision for Joint Motion Prediction
Royden Wagner, Omer Sahin Tas, Marvin Klemp +1
We present JointMotion, a self-supervised pre-training method for joint motion prediction in self-driving vehicles. Our method jointly optimizes a scene-level objective connecting…