publications

2026

1. ASE

   Bridging Stakeholder and Product Requirements: An Empirical Study of Requirement Engineering in the Automotive Industry

   Zixu Wang, Shengcheng Yu, Zhenchang Xing, Tobias Wenzel, and Chunyang Chen

   In 41st IEEE/ACM International Conference on Automated Software Engineering (ASE), Industry Showcase, 2026

   Abs arXiv Bib

   An empirical study of how stakeholder-level requirements are evaluated, refined, and transformed into product-level requirements in industrial automotive practice, based on over 8,000 stakeholder and 5,800 product requirements with traceability links and decision outcomes.

   @inproceedings{wang2026bridging,
     title = {Bridging Stakeholder and Product Requirements: An Empirical Study of Requirement Engineering in the Automotive Industry},
     author = {Wang, Zixu and Yu, Shengcheng and Xing, Zhenchang and Wenzel, Tobias and Chen, Chunyang},
     booktitle = {41st IEEE/ACM International Conference on Automated Software Engineering (ASE), Industry Showcase},
     year = {2026},
   }

2025

1. arXiv

   XD-RCDepth: Lightweight Radar-Camera Depth Estimation with Explainability-Aligned and Distribution-Aware Distillation

   Huawei Sun, Zixu Wang, Xiangyuan Peng, Julius Ott, Georg Stettinger, Lorenzo Servadei, and Robert Wille

   arXiv preprint arXiv:2510.13565, 2025

   arXiv Bib

   @article{sun2025xdrcdepth,
     title = {XD-RCDepth: Lightweight Radar-Camera Depth Estimation with Explainability-Aligned and Distribution-Aware Distillation},
     author = {Sun, Huawei and Wang, Zixu and Peng, Xiangyuan and Ott, Julius and Stettinger, Georg and Servadei, Lorenzo and Wille, Robert},
     journal = {arXiv preprint arXiv:2510.13565},
     year = {2025},
   }

2. TMLR

   TRIDE: A Text-assisted Radar-Image Weather-aware Fusion Network for Depth Estimation

   Huawei Sun, Zixu Wang, Hao Feng, Julius Ott, Lorenzo Servadei, and Robert Wille

   Transactions on Machine Learning Research, 2025

   arXiv Bib

   @article{sun2025tride,
     title = {TRIDE: A Text-assisted Radar-Image Weather-aware Fusion Network for Depth Estimation},
     author = {Sun, Huawei and Wang, Zixu and Feng, Hao and Ott, Julius and Servadei, Lorenzo and Wille, Robert},
     journal = {Transactions on Machine Learning Research},
     year = {2025},
   }

3. WACV

   GET-UP: GEomeTric-aware Depth Estimation with Radar Points UPsampling

   Huawei Sun, Zixu Wang, Hao Feng, Julius Ott, Lorenzo Servadei, and Robert Wille

   In IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2025

   arXiv Bib Code

   @inproceedings{sun2025getup,
     title = {GET-UP: GEomeTric-aware Depth Estimation with Radar Points UPsampling},
     author = {Sun, Huawei and Wang, Zixu and Feng, Hao and Ott, Julius and Servadei, Lorenzo and Wille, Robert},
     booktitle = {IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
     year = {2025},
   }

2024

1. arXiv

   SocialFormer: Social Interaction Modeling with Edge-enhanced Heterogeneous Graph Transformers for Trajectory Prediction

   Zixu Wang, Zhigang Sun, Juergen Luettin, and Lavdim Halilaj

   arXiv preprint arXiv:2405.03809, 2024

   Abs arXiv Bib

   A graph transformer that captures semantic and spatial agent interactions for trajectory prediction in autonomous driving, combining temporal encoding and road topology to reach state-of-the-art results on the nuScenes benchmark.

   @article{wang2024socialformer,
     title = {SocialFormer: Social Interaction Modeling with Edge-enhanced Heterogeneous Graph Transformers for Trajectory Prediction},
     author = {Wang, Zixu and Sun, Zhigang and Luettin, Juergen and Halilaj, Lavdim},
     journal = {arXiv preprint arXiv:2405.03809},
     year = {2024},
   }

2. RA-L

   Semanticformer: Holistic and Semantic Traffic Scene Representation for Trajectory Prediction Using Knowledge Graphs

   Zhigang Sun, Zixu Wang, Lavdim Halilaj, and Juergen Luettin

   IEEE Robotics and Automation Letters, 2024

   arXiv Bib

   @article{sun2024semanticformer,
     title = {Semanticformer: Holistic and Semantic Traffic Scene Representation for Trajectory Prediction Using Knowledge Graphs},
     author = {Sun, Zhigang and Wang, Zixu and Halilaj, Lavdim and Luettin, Juergen},
     journal = {IEEE Robotics and Automation Letters},
     volume = {9},
     number = {9},
     pages = {7381--7388},
     year = {2024},
   }

2023

1. ICCVW

   nuScenes Knowledge Graph: A Comprehensive Semantic Representation of Traffic Scenes for Trajectory Prediction

   Leon Mlodzian, Zhigang Sun, Hendrik Berkemeyer, Sebastian Monka, Zixu Wang, Stefan Dietze, Lavdim Halilaj, and Juergen Luettin

   In IEEE/CVF International Conference on Computer Vision Workshops (ICCVW), Scene Graphs and Graph Representation Learning, 2023

   arXiv Bib Code

   @inproceedings{mlodzian2023nuscenes,
     title = {nuScenes Knowledge Graph: A Comprehensive Semantic Representation of Traffic Scenes for Trajectory Prediction},
     author = {Mlodzian, Leon and Sun, Zhigang and Berkemeyer, Hendrik and Monka, Sebastian and Wang, Zixu and Dietze, Stefan and Halilaj, Lavdim and Luettin, Juergen},
     booktitle = {IEEE/CVF International Conference on Computer Vision Workshops (ICCVW), Scene Graphs and Graph Representation Learning},
     year = {2023},
   }