Qiang Meng (孟强)
I am currently a senior engineer at Didi, specializing in perception for autonomous driving.
Before this role, I worked as an algorithm engineer and sub-core team leader at Aibee.
During my tenure at Aibee, I actively contributed to diverse computer vision projects, encompassing tasks such as face recognition, image retrieval, and car/person re-identification, etc.
I completed my Master's degree in Industrial Engineering at the University of Washington, Seattle.
Prior to that, I received my Bachelor's degree in Mechanical Engineering from the University of Science and Technology of China, with a GPA of 3.78/4.3 (Rank: 3/61).
E-mail  | 
Curriculum Vitae  | 
Publications
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Github
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News
- 03/2024:    Make public the paper "Small, Versatile and Mighty: A Range-View Perception Framework" on arXiv.
- 02/2023:    Our paper "Curricular Object Manipulation in LiDAR-based Object Detection" has been accepted by CVPR 2023.
- 08/2022:    Make public the paper "Towards Privacy-Preserving, Real-Time and Lossless Feature Matching" on arXiv.
- 04/2022:    Invited to deliver a talk at Beijing Jiaotong University.
- 03/2022:    Invited to deliver a talk in ICLR 直播分享会 organized by ReadPaper.
- 01/2022:    Our Paper "Improving Federated Learning Face Recognition via Privacy-Agnostic Clusters" has been accepted by ICLR 2022 as a SPOTLIGHT paper.
- 01/2022:    Make public the paper "Basket-based Softmax" on arXiv.
- 11/2021:    Invited to deliver a talk in the workshop on face image quality organized by EAB, DHS-OBIM, NIST, eu-LISA, etc.
- 07/2021:    Our paper "Learning Compatible Embeddings" has been accepted by ICCV 2021.
- 07/2021:    Make public the paper "PoseFace: Pose-Invariant Features and Pose-Adaptive Loss for Face Recognition" on arXiv. .
- 06/2021:    Invited to deliver a talk about MagFace in CVPR 论文分享会 organized by 机器之心.
- 03/2021:    Our paper "MagFace: A Universal Representation for Face Recognition and Quality Assessment" has been accepted by CVPR 2021 as an ORAL paper.
- 12/2020:    Our paper "Searching for Alignment in Face Recognition" has been accepted by AAAI 2021.
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First-author Publications |
My research interests lie in computer vision, deep learning and optimization.
Representative works are highlighted.
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Curricular Object Manipulation in LiDAR-based Object Detection
Ziyue Zhu*, Qiang Meng*, Xiao Wang, Ke Wang, Liujiang Yan, Jian Yang
*equal contirbution
CVPR, 2023
paper
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code
Curricular object manipulation (COM) is a framework for LiDAR-based object detection that incorporates the
easy-to-hard training strategy into both loss design and
augmentation process.
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Improving Federated Learning Face Recognition via Privacy-Agnostic Clusters
Qiang Meng, Feng Zhou, Hainan Ren, Tianshu Feng, Guochao Liu, Yuanqing Lin
ICLR , 2022 (Spotlight)
project page
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paper
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知乎
A pragmatic framework that markedly enhances the performance of federated learning in face recognition while ensuring privacy guarantees. Key components encompass a meticulously crafted differentially private local clustering mechanism and a recognition loss that is consensus-aware.
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Basket-based Softmax
Qiang Meng, Guxin Qian, Xiaqing Xu, Feng Zhou
arXiv, 2022
A simple but effective mining-during-training strategy that enables models to be trained in an end-to-end fashion on multiple datasets.
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PoseFace: Pose-Invariant Features and Pose-Adaptive Loss for Face Recognition
Qiang Meng, Xiaqing Xu, Xiaobo Wang, Yang Qian, Yunxiao Qin, Zezheng Wang, Chenxu Zhao, Feng Zhou, Zhen Lei
arXiv, 2021
An efficient large-pose face recognition method that leverages facial landmarks to disentangle pose-invariant features and incorporates a pose-adaptive loss to dynamically address the imbalance issue.
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Searching for Alignment in Face Recognition
Xiaqing Xu, Qiang Meng,
Yunxiao Qin, Jianzhu Guo, Chenxu Zhao, Feng Zhou, Zhen Lei
AAAI, 2021
paper
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知乎
We design a face template searching space with decomposed crop size and vertical shift, and propose the Face Alignment Policy Search (FAPS) to find optimal alignment templates for face recognition.
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