I am a Ph.D. student at Imperial College London (Since April 2024), under the supervision of Professor
Krystian Mikolajczyk. My Ph.D. is generously funded by the Department of EEE. I have broad interests in computer vision and machine learning, with a current focus on 3D vision.
Prior to my doctoral studies, I worked as a research engineer at ByteDance and Meituan UAV.
I received my Master’s degree from Tsinghua University, where I was supervised by
Professor Yu Wang. During my Master’s studies, I also interned at Xilinx
(now part of AMD) and SenseTime.
I earned my Bachelor’s degree from Wuhan University.
Contrastive Language-Colored Pointmap Pretraining for Unified 3D Scene Understanding Ye Mao, Weixun Luo, Ranran Huang, Junpeng Jingand Krystian Mikolajczyk
European Conference on Computer Vision (ECCV), 2026
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From None to All: Self-Supervised 3D Reconstruction via Novel View Synthesis Ranran Huang, Weixun Luo, Ye Mao and Krystian Mikolajczyk
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2026
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POMA-3D: The Point Map Way to 3D Scene Understanding Ye Mao, Nigel Luo, Ranran Huang, Junpeng Jing, and Krystian Mikolajczyk
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR Findings), 2026
[Project Page]
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[Code]
SPFSplatV2: Efficient Self-Supervised Pose-Free 3D Gaussian Splatting from Sparse Views Ranran Huang, and Krystian Mikolajczyk
arXiv, 2025
[Project Page]
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No Pose at All: Self-Supervised Pose-Free 3D Gaussian Splatting from Sparse Views Ranran Huang, and Krystian Mikolajczyk
IEEE/CVF International Conference on Computer Vision (ICCV), Highlight, 2025
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DRKF: Distilled Rotated Kernel Fusion for Efficient Rotation Invariant Descriptors in Local Feature Matching Ranran Huang, Jiancheng Cai, Chao Li, Zhuoyuan Wu, Xinmin Liu, and Zhenhua Chai
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2023
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Cross-layer Attention Network for Fine-grained Visual Categorization Ranran Huang, Yu Wang, and Huazhong Yang
IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) , 2021
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Feature Variance Regularization: A Simple Way to Improve the Generalizability of Neural Networks Ranran Huang, Hanbo Sun, Ji Liu, Lu Tian, Li Wang, Yi Shan, and Yu Wang
AAAI Conference on Artificial Intelligence (AAAI), Oral, 2020
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