collaborators

5 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.CV2026

LongTail Driving Scenarios with Reasoning Traces: The KITScenes LongTail Dataset

Royden Wagner, Omer Sahin Tas, Jaime Villa +18

In real-world domains such as self-driving, generalization to rare scenarios remains a fundamental challenge. To address this, we introduce a new dataset designed for end-to-end dr…

cs.CV2025

Divide and Merge: Motion and Semantic Learning in End-to-End Autonomous Driving

Yinzhe Shen, Omer Sahin Tas, Kaiwen Wang +2

Perceiving the environment and its changes over time corresponds to two fundamental yet heterogeneous types of information: semantics and motion. Previous end-to-end autonomous dri…