Ranran Huang

I am a Ph.D. student at MatchLab, 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 Meituan UAV and ByteDance. 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.

Email / Google Scholar / Github

Publication

	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 [Project Page] [Paper] [Code]
	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] [Paper] [Code]
	SPFSplatV2: Efficient Self-Supervised Pose-Free 3D Gaussian Splatting from Sparse Views Ranran Huang, and Krystian Mikolajczyk arXiv, 2025 [Project Page] [Paper] [Code]
	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 [Project Page] [Paper] [Code]
	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), Oral, 2023 [Paper]
	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 [Paper]
	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 [Paper]

Competition

	2^nd place Drone Satellite Matching Challenge (ACM Multimedia Workshop 2023) [Link] [Certificate]
	Winner on Object Detection Track, 2^nd place on Crowd Counting Track VisDrone Challenge, 2022 [Link]
	2^nd place on Video Track IEEE Low Power Computer Vision Challenge (ICCV Workshop 2021) [Link]
	6th / 216 on Fine-grained Visual Categorization iNaturalist Competition (CVPR Workshop 2019) [Link]

Teaching

Deep Learning (ELEC60009), TA, 2025

Computer Vision and Pattern Recognition (ELEC70073), TA, 2025

Academic Services

Conference Reviewer: NeurIPS, ICLR, ICML, ICCV, AAAI, CVPR, ECCV.

Thanks to Jon Barron for sharing the source code of his site.