Shuzhao Xie

I am a PhD student at Tsinghua SIGS, working with Prof. Zhi Wang on 3D Vision and Embodied AI. I received my Master's degree in Computer Technology from Tsinghua University in 2023 and my Bachelor's degree in Computer Science and Technology from Beijing Normal University in 2020.

Email  /  CV [2025.01]  /  Google Scholar  /  Github  /  Twitter  /  Calendar

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Research Interests

My research is in the area of efficient deep learning, 3D vision, and robotics. Specifically, I am interested in building efficient models to support the applications in 3D reconstruction, robot manipulation, and intelligent diagnosis.

Publications
Expansive Supervision for Neural Radiance Field
Weixiang Zhang, Wei Yao, Shuzhao Xie, Shijia Ge, Chen Tang, Zhi Wang
IEEE International Conference on Multimedia & Expo (ICME), 2025
paper
EVOS: Efficient Implicit Neural Training via EVOlutionary Selector
Weixiang Zhang, Shuzhao Xie, Chengwei Ren, Shiyi Xie, Chen Tang, Shijia Ge, Mingzi Wang, Zhi Wang
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2025
paper / code
TextIR: A Simple Framework for Text-based Editable Image Restoration
Yunpeng Bai, Cairong Wang, Shuzhao Xie, Chao Dong, Chun Yuan, Zhi Wang
IEEE Transactions on Visualization and Computer Graphics (TVCG), 2025
paper

In this work, we design an effective framework that allows the user to control the restoration process of degraded images with text descriptions. We use the text-image feature compatibility of the CLIP to alleviate the difficulty of fusing text and image features. Our framework can be used for various image restoration tasks, including image inpainting, image super-resolution, and image colorization.

Lungmix: A Mixup-Based Strategy for Generalization in Respiratory Sound Classification
Shijia Ge, Weixiang Zhang, Shuzhao Xie, Baixu Yan, Zhi Wang
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2025
paper
PulmoScan: A Practical Pulmonary Disease Pre-Screening System
Baixu Yan, Shijia Ge, Meizi Lu, Weixiang Zhang, Shuzhao Xie, Zhi Wang
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2025
paper
Enhancing Implicit Neural Representations via Symmetric Power Transformation
Weixiang Zhang, Shuzhao Xie, Chengwei Ren, Shijia Ge, Mingzi Wang, Zhi Wang
The 39th Annual AAAI Conference on Artificial Intelligence (AAAI), 2025
paper / code
MesonGS: Post-training Compression of 3D Gaussians via Efficient Attribute Transformation
Shuzhao Xie, Weixiang Zhang, Chen Tang, Yunpeng Bai, Rongwei Lu, Shijia Ge, Zhi Wang
European Conference on Computer Vision (ECCV), 2024
paper / project page / code

SkyML: A MLaaS Federation Design for Multicloud-based Multimedia Analytics
Shuzhao Xie, Yuan Xue, Yifei Zhu, Zhi Wang
IEEE Transactions on Multimedia (TMM) , 2024
paper / code

Tuning-Free Visual Customization via View Iterative Self-Attention Control
Xiaojie Li, Chenghao Gu, Shuzhao Xie, Yunpeng Bai, Weixiang Zhang, Zhi Wang
arXiv, 2024
paper

RFQuant: Retraining-free Model Quantization via One-Shot Weight-Coupling Learning
Chen Tang*, Yuan Meng*, Jiacheng Jiang, Shuzhao Xie, Rongwei Lu, Xinzhu Ma, Zhi Wang, Wenwu Zhu
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024
paper / supp / poster / code

A Joint Approach to Local Updating and Gradient Compression for Efficient Asynchronous Federated Learning
Jiajun Song, Jiajun Luo, Rongwei Lu, Shuzhao Xie, Bin Chen, Zhi Wang, Wenwu Zhu
International European Conference on Parallel and Distributed Computing (Euro-Par), 2024
paper

Cost Effective MLaaS Federation: A Combinatorial Reinforcement Learning Approach
Shuzhao Xie, Yuan Xue, Yifei Zhu, Zhi Wang
INFOCOM, 2022
paper / project page / code

As naively using multiple ML APIs can lead to lower analytical accuracy and poor user experience, we employ reinforcement learning to select the optimal combination of MLaaSes, thus maximizing accuracy while minimizing cost.

Industry Experience
Tencent Youtu Lab, Shanghai, China
Research Intern
Jan - May 2022

  • Deployed Faster-RCNN into CPU environments with C++.
  • Analyzed model performance under heterogeneous environments.
  • Professional Service and Teaching
    Journal and Conference Reviewer
  • CVPR: 2025
  • ACM MM: 2024
  • ICASSP: 2023 - 2025
  • Teaching Assistant
  • Big Data System (B), Tsinghua University, Fall 2021
  • Distributed Machine Learning, Tsinghua University, Fall 2024

  • Template from Jon Barron. Last updated in Jan 2025.