温程璐 国家级青年人才项目入选者、教授、博士生导师

福建省智慧城市感知与计算重点实验室副主任

中国农业大学 博士(2009)

研究方向:三维视觉 三维点云处理 智能机器人

电子邮件:clwen (AT) xmu.edu.cn

个人主页:https://asc.xmu.edu.cn/t/wenchenglu

个人简历:

主讲课程:

  • Digital Image Processing(全英文本科生课程)

  • 机器人导论(本科生课程)

  • 工程伦理(研究生课程)


学术兼职:

  • IEEE高级会员,CCF会员,ACM会员,CNISDE激光雷达专委会委员,CSIG三维视觉专委会委员,福建省人工智能学会理事,CCF智能汽车分会执行委员

  • IEEE Transactions on Intelligent Transportation Systems, Associate Editor, 期刊编委

  • IEEE Geoscience and Remote Sensing Letters, Associate Editor, 期刊编委

  • IEEE TGRS, ISPRS JPRS, IEEE TITS, CVPR, AAAI, ICCV, ECCV, ACM MM, IJCAI, etc., 审稿人


在研项目:

  • 国家自然科学基金面上项目,面向城市动态场景三维感知的点云序列弱监督学习,主持,2022-2025年

  • 国家重点研发计划青年科学家项目,多平台多模态点云大数据智能处理关键技术与软件,任务负责人,2022-2024年

  • 国家自然科学基金面上项目,联合可测点云/多视角图像的大规模对象标记数据集生成,主持,2018-2021年

  • 国家自然科学基金青年项目,室内移动三维测图点云数据的多元质量评价与修补,主持,2015-2017年


近期论文:

1. H. Wu, C. Wen*, S. Shi, et al., Virtual Sparse Convolution for Multimodal 3D Object Detection, CVPR, 2023. (CCF A)

2. Y. Dai, Y. Lin, X. Lin, C. Wen*, et al., SLOPER4D: A Scene-Aware Dataset for Global 4D Human Pose Estimation in Urban Environments, CVPR, 2023. (CCF A)

3. H. Wu, C. Wen*, W. Li, et al., Transformation-Equivariant 3D Object Detection for Autonomous Driving, AAAI, 2023. (CCF A)

4. Q. Li, C. Wang, C. Wen*, et al., DeepSIR: Deep Semantic Iterative Registration for LiDAR Point Clouds, Pattern Recognition, 2023. (CCF B)

5. Y. Dai, Y. Lin, C. Wen*, S. Shen, et al., HSC4D: Human-centered 4D Scene Capture in Large-scale Indoor-outdoor Space using Wearable IMUs and LiDAR, CVPR, 2022. (CCF A)

6. S. Yu, C. Wang, C. Wen*, et al., LiDAR-based Localization using Universal Encoding and Memory-aware Regression, Pattern Recognition, 2022. (CCF B)

7. H. Wu, J. Deng, C. Wen*, et al., CasA: A Cascade Attention Network for 3D Object Detection from LiDAR point clouds, IEEE Trans. on Geoscience and Remote Sensing, 2022. (CCF B)

8. H. Wu, Q. Li, C. Wen*, et al., Tracklet Proposal Network for Multi-object Tracking on Point Clouds, IJCAI, 2021. (CCF A)

9. H. Wu, W. Han, C. Wen*, 3D Multi-Object Tracking in Point Clouds based on Prediction Confidence-Guided Data Association, IEEE Trans. on Intelligent Transportation Systems, 2021. (CCF B)

10. W. Han, C. Wen*, C. Wang, et al., Point2Node: Correlation Learning of Dynamic-Node for Point Cloud Feature Modeling, AAAI, Oral presentation, 2020. (CCF A)