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王俊印

职称:特聘副教授
学院: 数据科学学院
电子邮箱:wjy199708@163.com
  • 基本信息

  • 项目

  • 获奖

  • 论文

  • 专利

  • 课程

  • 教材或专著

  • 基本信息
    姓名:  王俊印      最高学位:博士                     入职科大时间:2026.07          
    主要研究方向:计算机视觉、多模态融合、智能系统规划 导师类别:    
    国内外重要学术组织任职:International Conference on Learning Representations (ICLR, 2024),International Conference on Machine Learning (ICML, 2025),European Conference on Computer Vision (ECCV 2024),International Joint Conference on Artificial Intelligence (IJCAI, 2025),ACM Multimedia (ACMMM 2023, 2024, 2025),IEEE Transactions on Neural Networks and Learning Systems (TNNLS),Knowledge-Based Systems (KBS), The Visual Computer,IEEE Transactions on Circuits and Systems for Video Technology (T-CSVT)等会议期刊审稿人。
    学习研究经历:
    2022/09-2026/07:武汉理工大学,计算机科学与技术,博士
    2019/09-2022/07:青岛科技大学,计算机技术,硕士
  • 项目
  • 获奖
  • 论文
    [1][1]DLFusion : Painting-Depth Augmenting-LiDAR for Multimodal Fusion 3D Object Detection [C]. ACM MM. 2023.(CCF A,会议论文)
    [2]Driving with Advice: Large Model as Motion Advisor for Joint Planning [C]. AAAI. 2026. (CCF A,会议论文)
    [3]DenseRadar: Dense Radar Generation and Point Consistency Aggregation for 3D Object Detection [J]. IEEE Transactions on Multimedia. 2025. (CCF A,SCI一区)
    [4]CycleVTON: A Cycle Mapping Framework for Parser-Free Virtual Try-On [C]. AAAI. 2023. (CCF A,会议论文)
    [5]Greatness in Simplicity: Unified Self-Cycle Consistency for Parser-Free Virtual Try-On [C]. NIPS. 2023. (CCF A,会议论文)
    [6]HybirdBEV : Hybrid Encode and Distillation for Improved BEV 3D Object Detection [J]. IEEE Transactions on Intelligent Transportation Systems. 2025. (CCF B,SCI一区)
    [7]D3PD: Dual Distillation and Dynamic Fusion of Camera and Radar for 3D Perception Detection [J]. Pattern Recognition. 2025. (CCF B,SCI一区)
    [8]GLV: Geometric Correlation Distillation for Latent Diffusion-Enhanced Parser-Free Virtual Try-On [J]. IEEE Transactions on Circuits and Systems for Video Technology. 2025. (CCF B,SCI一区)
  • 专利
    [1]智能轨迹规划预测方法、装置、设备及存储介质 [P]. 公开授权号:CN119647717B
    [2]占有网络预测方法、装置、设备、存储介质及产品 [P]. 公开授权号: CN118864873B
    [3]基于大模型约束的点集占有网络生成方法、装置、设备及存储介质 [P]. 公开授权号:CN119963574B
  • 课程
  • 教材或专著