activity
20212025
most citedV2X-Real: a Large-Scale Dataset for Vehicle-to-Everything Cooperative Perception

2 citations · 2 across the 8 of their papers we have counts for

collaborators

10 papers

cs.CV2025

SMOL-MapSeg: Show Me One Label as prompt

Yunshuang Yuan, Frank Thiemann, Thorsten Dahms +1

Historical maps offer valuable insights into changes on Earth's surface but pose challenges for modern segmentation models due to inconsistent visual styles and symbols. While deep…

cs.CV2025

Leveraging LLMs and attention-mechanism for automatic annotation of historical maps

Yunshuang Yuan, Monika Sester

Historical maps are essential resources that provide insights into the geographical landscapes of the past. They serve as valuable tools for researchers across disciplines such as…

cs.CV2025

SparseAlign: A Fully Sparse Framework for Cooperative Object Detection

Yunshuang Yuan, Yan Xia, Daniel Cremers +1

Cooperative perception can increase the view field and decrease the occlusion of an ego vehicle, hence improving the perception performance and safety of autonomous driving. Despit…

cs.CV2025

Semantic Segmentation for Sequential Historical Maps by Learning from Only One Map

Yunshuang Yuan, Frank Thiemann, Monika Sester

Historical maps are valuable resources that capture detailed geographical information from the past. However, these maps are typically available in printed formats, which are not c…

cs.CV2024

StreamLTS: Query-based Temporal-Spatial LiDAR Fusion for Cooperative Object Detection

Yunshuang Yuan, Monika Sester

Cooperative perception via communication among intelligent traffic agents has great potential to improve the safety of autonomous driving. However, limited communication bandwidth,…

cs.CV2024

CoSense3D: an Agent-based Efficient Learning Framework for Collective Perception

Yunshuang Yuan, Monika Sester

Collective Perception has attracted significant attention in recent years due to its advantage for mitigating occlusion and expanding the field-of-view, thereby enhancing reliabili…