I am a Lead Researcher and team manager in the Imaging Algorithm Center of VIVO. Our group is the core algorithm team responsible for advancing the photographic quality in the flagship smartphones with the cutting-edge technologies (3D, AIGC, etc).
I was a Senior Researcher in the Visual Computing Center of Tencent AI Lab between 2021 to 2023.
I was a Postdoctoral Researcher in Stanford University supervised by Prof. Leonidas Guibas between 2019 to 2021.
I obtained my PhD degree in the Computer Science and Technology School of Shandong University at 2019. I was supervised by Prof. Baoquan Chen.
My research focus lies in computational photography, computer graphics, 3D vision, Embodied AI. I have published about 40 papers at the top international conferences. For the complete publication list, please refer to my google scholar page.
👩🎓🧑🎓 Internship at VIVO. If you are interested in the research internship on computational photography, 3DV and Embodied AI, feel free to drop me an email.
🔥 Tech Transfer
VIVO X200 series: Telephoto Image Quality Enhancement
📝 Selected Publications
Equal contribution$^\star$

SLAM3R: Real-Time Dense Scene Reconstruction from Monocular RGB Videos
Yuzheng Liu*, Siyan Dong*, Shuzhe Wang, Yingda Yin, Yanchao Yang, Qingnan Fan, Baoquan Chen.
- Award: China3DV 2025, Top1 paper.
- SLAM3R is a real-time dense scene reconstruction system that regresses 3D points from video frames using feed-forward neural networks, without explicitly estimating camera parameters.

Scene-aware Activity Program Generation with Language Guidance
Zejia Su, Qingnan Fan, Xuelin Chen, Oliver van Kaick, Hui Huang, Ruizhen Hu.
project page / supp file / bibtex
- We address the problem of scene-aware activity program generation, which requires decomposing a given activity task into instructions that can be sequentially performed within a target scene to complete the activity.

C·ASE: Learning Conditional Adversarial Skill Embeddings for Physics-based Characters
Zhiyang Dou, Xuelin Chen, Qingnan Fan, Taku Komura, Wenping Wang.
arXiv / project page / video / bibtex
- We present C·ASE, an efficient and effective framework that learns conditional Adversarial Skill Embeddings for Elite physics-based characters.

VAT-Mart: Learning Visual Action Trajectory Proposals for Manipulating 3D ARTiculated Objects
Ruihai Wu*, Yan Zhao*, Kaichun Mo*, Zizheng Guo, Yian Wang, Tianhao Wu, Qingnan Fan, Xuelin Chen, Leonidas Guibas, Hao Dong.
arXiv / project page / codes / video / bibtex
- Award: WAIC 2025, Young Outstanding Paper Award
- We design an interaction-for-perception framework, VAT-MART, to learn actionable visual representations for more effective manipulation of 3D articulated objects.

ADeLA: Automatic Dense Labeling with Attention for Viewpoint Shift in Semantic Segmentation
Yanchao Yang* ,
Hanxiang Ren*,
He Wang,
Bokui Shen,
Qingnan Fan,
Youyi Zheng,
C. Karen Liu,
Leonidas Guibas.
- We describe a method to deal with performance drop in semantic segmentation caused by viewpoint changes within multi-camera systems, where temporally paired images are readily available, but the annotations may only be abundant for a few typical views.

CAPTRA: CAtegory-level Pose Tracking for Rigid and Articulated Objects from Point Clouds
Yijia Weng*, He Wang*, Qiang Zhou, Yuzhe Qin, Yueqi Duan, Qingnan Fan, Baoquan Chen, Hao Su, Leonidas Guibas.
arXiv / project page / codes / video / bibtex
- For the first time, we propose a unified framework that can handle 9-DoF pose tracking for novel rigid object instances as well as per-part pose tracking for 3D articulated objects.

Siyan Dong*, Qingnan Fan*, He Wang, Ji Shi, Li Yi, Thomas Funkhouser, Baoquan Chen, Leonidas Guibas.
arXiv / codes / video / bibtex
- A novel outlier-aware neural tree to tackle the camera localization challenges in dynamic indoor environments. It achieves the best performance in the RIO-10 benchmark.

Image Smoothing via Unsupervised Learning
Qingnan Fan, Jiaolong Yang, David Wipf, Baoquan Chen, Xin Tong.
arXiv / codes / supp file / bibtex
- Treat deep learning as an optimization tool to minimize the proposed image smoothing objective function in an unsupervised manner. Multiple different smoothing effects can be easily learned by adaptively changing the proposed objective function.

Revisiting Deep Intrinsic Image Decompositions
Qingnan Fan, Jiaolong Yang, Gang Hua, Baoquan Chen, David Wipf.
arXiv / codes / slides / supp file / poster / bibtex
- The first demonstration of a single basic deep architecture capable of achieving state-of-the-art results when applied to each of the major intrinsic benchmarks.

JumpCut: Non-Successive Mask Transfer and Interpolation for Video Cutout
Qingnan Fan, Fan Zhong, Dani Lischinski, Daniel Cohen-Or, Baoquan Chen.
codes / slides / video / supp file / dataset / bibtex
- An interactive real-time video segmentation algorithm. Significantly improve the video cutout accuracy and efficiency.

Build-to-Last: Strength to Weight 3D Printed Objects
Lin Lu, Andrei Sharf, Haisen Zhao, Yuan Wei, Qingnan Fan, Xuelin Chen, Yann Savoye, Changhe Tu, Daniel Cohen-Or, Baoquan Chen.
- Reduce the material cost and weight of a given object while providing a durable printed model that is resistant to impact and external forces.
🎖 Honors and Awards
- 2022, Tencent Outstanding Contributor.
- 2020, CCF Doctorial Dissertation Award Nominee (CCF 优博提名)
- 2018, Academic Star Nominee of Shandong University (10/20000)
- 2015, Presidential Scholarship of Shandong University (35/20000) (Highest honor for students in SDU, only 35 elected among around 20000 candidates)
📖 Educations
- 2019.09 - 2021.03, PostDoc, Stanford University
- 2014.09 - 2019.06, Ph.D., Shandong University.
- 2010.09 - 2014.06, Undergraduate, Shandong University.
💬 Invited Talks
- 2022.04, Active 3D scene understanding and its applications, “三维视觉与智能图形”前沿论坛, 图图名师讲堂
- 2021.10, Visual Localization, Embodied AI Workshop, Valse
- 2019.01, Deep Learning in Computational Photography, USC ICT/UW Reality Lab/Berkeley/Stanford/Google/MSR
- 2018.12, Deep Learning for Single Image Artifact Removal, ACCV Tutorial
- 2018.12, Image Smoothing via Unsupervised Learning, GAMES Webinar
- 2018.08, Discovering Unsupervised Learning in Image Processing, CIA, Cambridge University
💻 Internships and Visiting students
- 2018.04 - 2019.08, Beijing Film Academy, China.
- 2018.08 - 2018.10, University of Cambridge, UK.
- 2016.09 - 2018.03, Microsoft Research Asia, China.
- 2015.04 - 2015.05, Tel Aviv University, Israel.
- 2014.10 - 2014.11, The Hebrew University of Jerusalem, Israel.