ECCV2016 部分文章

本文摘录了ECCV2016的部分研究,重点关注人体姿态估计、人类活动识别、面部对齐与识别等方向。文章介绍了多种算法和技术,如3D人体姿态估计算法、递归神经网络用于活动识别、基于深度学习的面部特征定位等,展示了计算机视觉领域的最新进展。

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    摘录ECCV2016部分文章,主要有Human pose esimation,  Human activiity / actions, Face alignment, Face detection & recognition & .. , Hand tracking, Eye, and Others.

    以下为文章及标题(可能有错漏)

   

Human pose estimation:

[1]Towards Viewpoint Invariant 3DHuman Pose Estimation

     Albert Haque, Boya Peng, Zelun Luo, Alexandre Alahi, Serena Yeung,and Li Fei-Fei

[2]Fast 6D Pose Estimation from aMonocular Image UsingHierarchical Pose Trees

     Yoshinori Konishi, Yuki Hanzawa, Masato Kawade,and Manabu Hashimoto

[3]Keep It SMPL: AutomaticEstimation of 3D Human Pose and Shapefrom a SingleImage

     Federica Bogo, Angjoo Kanazawa, Christoph Lassner, Peter Gehler,Javier Romero, and Michael J. Black

[4] Zoom Better to See Clearer: Human and Object Parsing withHierarchicalAuto-Zoom Net

     Fangting Xia, PengWang, Liang-Chieh Chen, and Alan L. Yuille

[5] A Sequential Approach to 3D Human Pose Estimation: Separationof Localization and Identification of Body Joints

     Ho Yub Jung, YuminSuh, Gyeongsik Moon, and Kyoung Mu Lee

[6]DeeperCut: A Deeper, Stronger,and Faster Multi-person PoseEstimation Model

     Eldar Insafutdinov, Leonid Pishchulin, Bjoern Andres,Mykhaylo Andriluka, and Bernt Schiele

[7]Human Attribute Recognition byDeep Hierarchical Contexts

     Yining Li, Chen Huang, Chen Change Loy, and Xiaoou Tang

[8]Human Pose Estimation UsingDeep Consensus Voting .

     Ita Lifshitz, Ethan Fetaya, and Shimon Ullman

[9]Human Pose Estimation viaConvolutional Part Heatmap Regression

     Adrian Bulat and Georgios Tzimiropoulos</

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