Lu Ming

My research focuses on the intersection of AI and Graphics (AIG), where I possess a deep understanding of both visual AI and computer graphics. I did my Ph.D focused on 3D vision and computer graphics at Tsinghua University, where I was advised by Prof. Zhang Li.

I'm especially interested in 1) Neural Fields (robot navigation/robot manipulation/autonomous driving/digital human/thermal/underwater/etc.), 2) Large Vision-Language Models (training-free/efficient algorithms for the post-training of SAM/Diffusion Model/LLaVA/Qwen-VL/VLA/VLN/etc.), 3) Small Image/Video Processing Models (style transfer/super-resolution/denoising/relighting/retouching/etc.), and 4) AI for Sciences (neural field for medical data compression/etc.).

I have published over 50 papers on top-tier journals and conference proceedings. I also have about 30 PCT/US/EP patents approved for filing. Some of my works have been used in Intel GPU/CPU, Chris Lee's MV, and the opening ceremony of the Winter Olympic Games 2022.

Research Intro  /  Email  /  CV  /  Google Scholar  /  Github

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Neural Fields
[1] Real-time 3D Eyelids Tracking from Semantic Edges
Quan Wen, Feng Xu, Ming Lu, Jun-Hai Yong
ACM Transactions on Graphics (TOG), 2017

[2] Emotion-preserving Blendshape Update with Real-time Face Tracking
Zhibo Wang, Jingwang Ling, Chengzeng Feng, Ming Lu, Feng Xu
Transactions on Visualization and Computer Graphics (TVCG), 2020

[3] Semantically Disentangled Variational Autoencoder for Modeling 3D Facial Details
Jingwang Ling, Zhibo Wang, Ming Lu, Quan Wang, Chen Qian, Feng Xu
Transactions on Visualization and Computer Graphics (TVCG), 2022

[4] Structure-aware Editable Morphable Model for 3D Facial Detail Animation and Manipulation
Jingwang Ling, Zhibo Wang, Ming Lu, Quan Wang, Chen Qian, Feng Xu
European Conference on Computer Vision (ECCV), 2022

[5] NTO3D: Neural Target Object 3D Reconstruction with Segment Anything
Xiaobao Wei, Renrui Zhang, Jiarui Wu, Jiaming Liu, Ming Lu, Yandong Guo, Shanghang Zhang
Conference on Computer Vision and Pattern Recognition (CVPR), 2024

[6] Superpixel-based Efficient Sampling for Learning Neural Fields from Large Input
Zhongwei Xuan, Zunjie Zhu, Shuai Wang, Haibing Yin, Hongkui Wang, Ming Lu
International Conference on Multimedia (MM), 2024

[7] Graphavatar: Compact Head Avatars with GNN-Generated 3D Gaussians
Xiaobao Wei, Peng Chen, Ming Lu, Hui Chen, Feng Tian
Conference on Artificial Intelligence (AAAI), 2025

[8] ThermalGaussian: Thermal 3D Gaussian Splatting
Rongfeng Lu, Hangyu Chen, Zunjie Zhu, Yuhang Qin, Ming Lu, Le Zhang, Chenggang Yan, Anke Xue
International Conference on Learning Representations (ICLR), 2025

[9] SliceOcc: Indoor 3D Semantic Occupancy Prediction with Vertical Slice Representation
Jianing Li, Ming Lu, Hao Wang, Chenyang Gu, Wenzhao Zheng, Li Du, Shanghang Zhang
International Conference on Robotics and Automation (ICRA), 2025

[10] PLGS: Robust Panoptic Lifting with 3D Gaussian Splatting
Yu Wang, Xiaobao Wei, Ming Lu, Guoliang Kang
Transactions on Image Processing (TIP), 2025

[11] K-Buffers: A Plug-in Method for Enhancing Neural Fields with Multiple Buffers
Haofan Ren, Zunjie Zhu, Xiang Chen, Ming Lu, Rongfeng Lu, Chenggang Yan
International Joint Conference on Artificial Intelligence (IJCAI), 2025

[12] GazeGaussian: High-Fidelity Gaze Redirection with 3D Gaussian Splatting
Xiaobao Wei, Peng Chen, Guangyu Li, Ming Lu, Hui Chen, Feng Tian
International Conference on Computer Vision (ICCV), 2025

[13] EMD: Explicit Motion Modeling for High-Quality Street Gaussian Splatting
Xiaobao Wei, Qingpo Wuwu, Zhongyu Zhao, Zhuangzhe Wu, Nan Huang, Ming Lu, Ningning Ma, Shanghang Zhang
International Conference on Computer Vision (ICCV), 2025

[14] 3DRealCar: An In-the-wild RGB-D Car Dataset with 360-degree Views
Xiaobiao Du, Haiyang Sun, Shuyun Wang, Zhuojie Wu, Hongwei Sheng, Jiaying Ying, Ming Lu, Tianqing Zhu, Kun Zhan, Xin Yu
International Conference on Computer Vision (ICCV), 2025

Large Vision-Language Models
[1] MoVE-KD: Knowledge Distillation for VLMs with Mixture of Visual Encoders
Jiajun Cao, Yuan Zhang, Tao Huang, Ming Lu, Qizhe Zhang, Ruichuan An, Ningning Ma, Shanghang Zhang
Conference on Computer Vision and Pattern Recognition (CVPR), 2025

[2] Beyond Text-Visual Attention: Exploiting Visual Cues for Effective Token Pruning in VLMs
Qizhe Zhang, Aosong Cheng, Ming Lu, Zhiyong Zhuo, Minqi Wang, Jiajun Cao, Shaobo Guo, Qi She, Shanghang Zhang
International Conference on Computer Vision (ICCV), 2025

[3] Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs
Qizhe Zhang, Mengzhen Liu, Lichen Li, Ming Lu, Yuan Zhang, Junwen Pan, Qi She, Shanghang Zhang
arXiv, 2025

[4] FastInit: Fast Noise Initialization for Temporally Consistent Video Generation
Chengyu Bai, Yuming Li, Zhongyu Zhao, Jintao Chen, Peidong Jia, Qi She, Ming Lu, Shanghang Zhang
arXiv, 2025

[5] AutoV: Learning to Retrieve Visual Prompt for Large Vision-Language Models
Yuan Zhang, Chun-Kai Fan, Tao Huang, Ming Lu, Sicheng Yu, Junwen Pan, Kuan Cheng, Qi She, Shanghang Zhang
arXiv, 2025

[6] MC-LLaVA: Multi-Concept Personalized Vision-Language Model
Ruichuan An, Sihan Yang, Ming Lu, Renrui Zhang, Kai Zeng, Yulin Luo, Jiajun Cao, Hao Liang, Ying Chen, Qi She, Shanghang Zhang, Wentao Zhang
arXiv, 2025

[7] Concept-as-Tree: Synthetic Data is All You Need for VLM Personalization
Ruichuan An, Kai Zeng, Ming Lu, Sihan Yang, Renrui Zhang, Huitong Ji, Qizhe Zhang, Yulin Luo, Hao Liang, Wentao Zhang
arXiv, 2025

[8] UniCTokens: Boosting Personalized Understanding and Generation via Unified Concept Tokens
Ruichuan An, Sihan Yang, Renrui Zhang, Zijun Shen, Ming Lu, Gaole Dai, Hao Liang, Ziyu Guo, Shilin Yan, Yulin Luo, Bocheng Zou, Chaoqun Yang, Wentao Zhang
arXiv, 2025

Small Image/Video Processing Models
[1] Decoder Network over Lightweight Reconstructed Feature for Fast Semantic Style Transfer
Ming Lu, Hao Zhao, Anbang Yao, Feng Xu, Yurong Chen, Li Zhang
International Conference on Computer Vision (ICCV), 2017

[2] A Closed-Form Solution to Universal Style Transfer
Ming Lu, Hao Zhao, Anbang Yao, Yurong Chen, Feng Xu, Zhang Li
International Conference on Computer Vision (ICCV), 2019

[3] Single Image Portrait Relighting via Explicit Multiple Reflectance Channel Modeling
Zhibo Wang, Xin Yu, Ming Lu, Quan Wang, Chen Qian, Feng Xu
ACM Transactions on Graphics (ToG), 2020

[4] Overfitting the Data: Compact Neural Video Delivery via Content-aware Feature Modulation
Jiaming Liu, Ming Lu, Kaixin Chen, Xiaoqi Li, Shizun Wang, Zhaoqing Wang, Enhua Wu, Yurong Chen, Chuang Zhang, Ming Wu
International Conference on Computer Vision (ICCV), 2021

[5] Deep Likelihood Network for Image Restoration With Multiple Degradation Levels
Yiwen Guo, Ming Lu, Wangmeng Zuo, Changshui Zhang, Yurong Chen
Transactions on Image Processing (TIP), 2021

[6] SamplingAug: On the Importance of Patch Sampling Augmentation for Single Image Super-Resolution
Shizun Wang, Ming Lu, Kaixin Chen, Jiaming Liu, Xiaoqi Li, Ming Wu
British Machine Vision Conference (BMVC), 2021

[7] Efficient Meta-Tuning for Content-Aware Neural Video Delivery
Xiaoqi Li, Jiaming Liu, Shizun Wang, Cheng Lyu, Ming Lu, Yurong Chen, Anbang Yao, Yandong Guo, Shanghang Zhang
European Conference on Computer Vision (ECCV), 2022

[8] Adaptive Patch Exiting for Scalable Single Image Super-Resolution
Shizun Wang, Jiaming Liu, Kaixin Chen, Xiaoqi Li, Ming Lu, Yandong Guo
European Conference on Computer Vision (ECCV Oral), 2022

[9] CABM: Content-Aware Bit Mapping for Single Image Super-Resolution Network with Large Input
Senmao Tian, Ming Lu, Jiaming Liu, Yandong Guo, Yurong Chen, Shunli Zhang
Conference on Computer Vision and Pattern Recognition (CVPR), 2023

[10] A Comprehensive Comparison of Projections in Omnidirectional Super-Resolution
Huicheng Pi, Senmao Tian, Ming Lu, Jiaming Liu, Yandong Guo, Shunli Zhang
International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023

[11] DanceU: Motion-and-Music-based Automatic Effect Generation for Dance Videos
Yanjie Pan, Yaru Du, Shandong Wang, Yun Ye, Yong Jiang, Zhen Zhou, Li Xu, Ming Lu, Yunbiao Lin, Jiehui Lu
International Conference on Multimedia and Expo (ICME), 2023

[12] HQRetouch: Learning Professional Face Retouching via Masked Feature Fusion and Semantic-aware Modulation
Gangyi Hong, Fangshi Wang, Senmao Tian, Ming Lu, Jiaming Liu, Shunli Zhang
International Conference on Multimedia and Expo (ICME), 2023

AI for Sciences
[1] I-MedSAM: Implicit Medical Image Segmentation with Segment Anything
Xiaobao Wei, Jiajun Cao, Yizhu Jin, Ming Lu, Guangyu Wang, Shanghang Zhang
European Conference on Computer Vision (ECCV), 2024

[2] A Generalist Foundation Model and Database for Open-World Medical Image Segmentation
Siqi Zhang, Qizhe Zhang, Shanghang Zhang, Xiaohong Liu, Jingkun Yue, Ming Lu, ..., Guangyu Wang
Nature Biomedical Engineering (NBE), 2025

[3] Implicit Neural Image Field for Biological Microscopy Image Compression
Gaole Dai, Cheng-Ching Tseng, Qingpo Wuwu, Rongyu Zhang, Shaokang Wang, Ming Lu,..., Jianxu Chen, Shanghang Zhang
Nature Computational Science (NCS), 2025

Application Demos
blind-date Our 3D face technique has been applied to Chris Lee's MV
blind-date Our 3D body technique has been applied to the opening ceremony of Winter Olympic Games 2022