关键词云

成果统计

合作作者[TOP 5]

  • 何旭明

    合作成果数:7

  • 刘永飞

    合作成果数:3

  • 贺倩

    合作成果数:3

  • 郑锐

    合作成果数:3

  • 刘志超

    合作成果数:3

周德森 博士生
所在学院: 信息科学与技术学院
职务: --
研究方向:
备注: --
周德森

科研成果

11 5307 206 1683 0 4
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 [1] Wan, Bo,Liu, Yongfei,Zhou, Desen,et al. Weakly-supervised HOI Detection via Prior-guided Bi-level Representation Learning. 2023.浏览/下载:344/0; 被引[WOS]:0评论推荐收藏
 [2] Liu, Zhichao,Wang, Leshan,Zhou, Desen,et al. Temporal Segment Transformer for Action Segmentation. 2023.浏览/下载:222/0; 被引[WOS]:0评论推荐收藏
 [3] Wan, Bo,Liu, Yongfei,Zhou, Desen,et al. Weakly-supervised Hoi Detection Via Prior-guided Bi-level Representation Learning[C]. The Eleventh International Conference On Learning Representations (iclr 2023).International Conference On Learning Representations, Iclr.2023-01-01.浏览/下载:539/1评论推荐收藏
 [4] Liu, Zhichao,Qian, Liyue,Jing, Wenke,et al. Automatic Spinal Curvature Measurement On Ultrasound Spine Images Using Faster R-cnn[C]. Ieee International Ultrasonics Symposium, Ius.345 E 47th St, New York, Ny 10017 Usa.Ieee Computer Society.2021-11-12.浏览/下载:649/192; 被引[WOS]:1评论推荐收藏
 [5] Zeng, Hong-Ye,Ge, Song-Han,Gao, Yu-Chong,et al. Automatic segmentation of vertebral features on ultrasound spine images using Stacked Hourglass Network. 2021.浏览/下载:282/1; 被引[WOS]:0评论推荐收藏
 [6] Desen Zhou,&Qian He.(2020).PoSeg: Pose-Aware Refinement Network for Human Instance Segmentation.IEEE ACCESS,8.浏览/下载:326/0; 被引[WOS]:6; IF:3.4/3.7评论推荐收藏
 [7] Desen Zhou,&Qian He.(2020).Cascaded Multi-Task Learning of Head Segmentation and Density Regression for RGBD Crowd Counting.IEEE ACCESS,8.浏览/下载:259/0; 被引[WOS]:6; IF:3.4/3.7评论推荐收藏
 [8] Wan, Bo,Zhou, Desen,Liu, Yongfei,et al. Pose-aware Multi-level Feature Network For Human Object Interaction Detection[C]. 2019 Ieee/cvf International Conference On Computer Vision (iccv).Institute Of Electrical And Electronics Engineers Inc.2019-10-01,9468-9477.浏览/下载:563/7; 被引[WOS]:188评论推荐收藏
 [9] 刘志超,郑锐,周德森,等. 超声脊柱图像的自动检测和测量[C]. 2019年全国声学大会论文集.2019-09-21,2.浏览/下载:194/0评论推荐收藏
 [10] He, Qian,Zhou, Desen,He, Xuming. 3d Object Structure Recovery Via Semi-supervised Learning On Videos[C]. 29th British Machine Vision Conference, Bmvc 2018.Bmva Press.2019-01-01.浏览/下载:695/3评论推荐收藏