Shaocheng Yan

Shaocheng Yan (颜绍程)

Hey, this is Laka!

🧑‍💻 About Me

Hi, I’m Shaocheng Yan — a first-year Ph.D. student at Wuhan University (M.S. 2023–25 → Ph.D. 2025–), supervised by Prof. Jiayuan Li. My research follows a single question, asked in two steps: given observations, can we reconstruct the world? — and now, can we predict it? From 3D reconstruction to world models, the sensors stay the same; what changes is the ambition.

Outside the lab, you’ll find me on a bicycle 🚴‍♂️ — chasing wind, sunrises 🌅, and sunsets 🌄, wherever the road takes me. When two wheels aren’t enough, I head into the mountains 🏔️ for a good hike 🥾 — no deep thoughts, just legs, trails, and altitude.

Curious to hear from you — research collaborations, half-baked ideas, or trail recommendations.

Currently exploring: 3D Reconstruction · World Models · Robust Geometry · Visual Localization

🔥 News

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  • 2024.07: 🎉 My homepage is created!

📚 Selected Publications

ULF-Loc: Unbiased Landmark Feature for Robust Visual Localization with 3D Gaussian Splatting
CVPR'26 ★ Highlight Top ~3% CCF A
Reviewer scores: 5·5·5·5 (max 6)
PDF Code BibTeX
Yingdong Gu*, Shaocheng Yan*, Zhenjun Zhao, Yuan Kou, Jianxin Luo, Pengcheng Shi, Jiayuan Li
* Equal contribution (co-first authors)
TL;DR: Unbiased landmark features via keypoint-consensus sampling and geometry-weighted feature fusion, fundamentally solving alpha-blending bias for highly accurate and ultra-efficient visual localization with 3D Gaussian Splatting.
TurboReg: TurboClique for Robust and Efficient Point Cloud Registration
ICCV'25 CCF A
PDF Code BibTeX CVlife 3DCVer
Shaocheng Yan, Pengcheng Shi, Zhenjun Zhao, Kaixin Wang, Kuang Cao, Ji Wu, Jiayuan Li
TL;DR: A highly efficient and robust estimator for point cloud registration (PCR), supporting both CPU and GPU platforms.
HeMoRa: Unsupervised Heuristic Consensus Sampling for Robust Point Cloud Registration
CVPR'25 CCF A
PDF Code BibTeX
TL;DR: Learning a sampling probability distribution for matches in robust estimation — no supervision, reinforcement-inspired.
ML-SemReg: Boosting Point Cloud Registration with Multi-level Semantic Consistency
ECCV'24 CCF B
PDF Code BibTeX
Shaocheng Yan, Pengcheng Shi, Jiayuan Li
TL;DR: Boosting 3D keypoint match recall using semantic labels — no learning needed, SLAM-ready.

💻 Selected Projects

ICCV'25
TurboClique-based robust & efficient point cloud registration (CPU/GPU).
CVPR'26
Unbiased landmark features for visual localization with 3D Gaussian Splatting.
ECCV'24
Multi-level semantic consistency for boosting registration recall.

🎙 Invited Talks & Sharing

2025.08 Replay
Invited talk on TurboReg @ 3DCVer
2025.07 Replay
Invited talk on TurboReg @ CVlife

🏆 Honors and Awards

  • 2025.04, Outstanding Graduate, Class of 2025
  • 2024.11, National Second Prize, China Graduate Mathematical Modeling Contest
  • 2022.08, National First Prize (Champion), China University Robotics Innovation Competition
  • 2020.12, First Prize, 11th National College Student Mathematics Competition (Non-Math Major Category)

🎓 Educations

  • 2025.09 - Present, Ph.D. in Photogrammetry and Remote Sensing, School of Remote Sensing and Information Engineering, Wuhan University
  • 2023.09 - 2025.06, M.S. in Geomatics Engineering, School of Remote Sensing and Information Engineering, Wuhan University
  • 2019.09 - 2023.06, B.S. in Electronic and Information Engineering, School of Electrical Engineering, Southwest Jiaotong University