Jiawei Xu ( 许家威 )

Jiawei Xu ( 许家威 )

Ph.D. student @ Nankai University

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Pages

Posts

Future Blog Post

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Blog Post number 1

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biographies

Biography </h2>

I am a third-year Ph.D. student at Tianjin Key Laboratory of Visual Computing and Intelligent Perception ( VCIP ), Nankai University, advised by Prof. Jian Yang and Prof. Jin Xie (co-advisor). My reseach mainly focuses on:

  • World Model & Autonomous Driving.
  • 3DGS & NeRF & 3DV.
It is my honor to exchange ideas with researchers from all over the world, and I will do my best to make my work open-source and easy to understand. If you are interested in my research, feel free to contact me via email ( jiaweixu [AT] mail.nankai.edu.cn ).

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Education </h2>

  • [Sept. 2023 ~ Present] Ph.D., Computer Science and Technology, Nankai University.
  • [Sept. 2019 ~ June. 2023] Bachelor of Engineering, Information Security, Nankai University.

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Internship </h2>

  • [Sept. 2025 ~ Present] Horizion Robotics, Shanghai. Research Intern. Mentored by Wei Yin.

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News </h2>

  • [2026-05] EponaV2 is now available on Arxiv.
  • [2026-01] VGGT-Long is accepted by ICRA 2026.
  • [2025-06] AD-GS is accepted by ICCV 2025.

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Professional Activities </h2>

  • Reviewer of NeurIPS.

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portfolio

publications

AD-GS: Object-Aware B-Spline Gaussian Splatting for Self-Supervised Autonomous Driving

ICCV, 2025
Jiawei Xu, Kai Deng, Zexin Fan, Shenlong Wang, Jin Xie, Jian Yang
AD-GS is a novel, self-supervised framework for high-quality rendering of dynamic urban driving scenes that eliminates the need for manual annotations by combining a learnable motion model, simplified segmentation, and dynamic Gaussians to achieve performance competitive with state-of-the-art, annotation-dependent approaches.
Website  Paper  Arxiv  Code  Slides  Poster 

VGGT-Long: Chunk it, Loop it, Align it, Pushing VGGT’s Limits on Kilometer-scale Long RGB Sequences

ICRA, 2026
Kai Deng, Zexin Ti, Jiawei Xu, Jian Yang, Jin Xie
To overcome the memory limitations of 3D vision foundation models, VGGT-Long employs a chunk-based processing strategy with overlapping alignment and loop closure optimization to enable accurate, kilometer-scale monocular 3D reconstruction in unbounded outdoor environments without requiring camera calibration or depth supervision.
Paper  Arxiv  Code 

EponaV2: Driving World Model with Comprehensive Future Reasoning

Arxiv, 2026
Jiawei Xu, Zhizhou Zhong, Zhijian Shu, Mingkai Jia, Mingxiao Li, Jia-Wang Bian, Qian Zhang, Kaicheng Zhang, Jin Xie, Jian Yang, Wei Yin
EponaV2 is a novel, perception-free driving world model that achieves state-of-the-art trajectory planning by forecasting comprehensive future 3D geometry and semantic representations and employing an LLM-inspired policy optimization mechanism to enhance real-world reasoning and scene understanding.
Paper  Arxiv  Code 

talks

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

Workshop, University 1, Department, 2015

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