해당 포스트는 HPE Series의 모든 레퍼런스를 모아놓았습니다. (Last Update: 2023.02.23.)
[DeepPose(2014)] Toshev, Alexander, and Christian Szegedy. “Deeppose: Human pose estimation via deep neural networks.” Proceedings of the IEEE conference on computer vision and pattern recognition. 2014.
[ConvNet(2015)] Tompson, Jonathan, et al. “Efficient object localization using convolutional networks.” Proceedings of the IEEE conference on computer vision and pattern recognition. 2015.
[CPM(2016)] Wei, Shih-En, et al. “Convolutional pose machines.” Proceedings of the IEEE conference on Computer Vision and Pattern Recognition. 2016.
[DeepCut(2016)] Insafutdinov, Eldar, et al. “Deepercut: A deeper, stronger, and faster multi-person pose estimation model.” Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part VI 14 . Springer International Publishing, 2016.
[StackedHourglass(2016)] Newell, Alejandro, Kaiyu Yang, and Jia Deng. “Stacked hourglass networks for human pose estimation.” Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part VIII 14. Springer International Publishing, 2016.
[CMU-Pose(2017)] Cao, Zhe, et al. “Realtime multi-person 2d pose estimation using part affinity fields.” Proceedings of the IEEE conference on computer vision and pattern recognition. 2017.
[AssociatedEmbedding(2017)] Newell, Alejandro, Zhiao Huang, and Jia Deng. “Associative embedding: End-to-end learning for joint detection and grouping.” Advances in neural information processing systems 30 (2017).
[RMPE(2017)] Fang, Hao-Shu, et al. “Rmpe: Regional multi-person pose estimation.” Proceedings of the IEEE international conference on computer vision. 2017.
[MaskR-CNN(2017)] He, Kaiming, et al. “Mask r-cnn.” Proceedings of the IEEE international conference on computer vision. 2017.
[CPN(2018)] Chen, Yilun, et al. “Cascaded pyramid network for multi-person pose estimation.” Proceedings of the IEEE conference on computer vision and pattern recognition. 2018.
[PersonLab(2018)] Papandreou, George, et al. “Personlab: Person pose estimation and instance segmentation with a bottom-up, part-based, geometric embedding model.” Proceedings of the European conference on computer vision (ECCV). 2018.
[SimpleBaseline(2018)] Xiao, Bin, Haiping Wu, and Yichen Wei. “Simple baselines for human pose estimation and tracking.” Proceedings of the European conference on computer vision (ECCV). 2018.
[OpenPose(2019)] Cao, Zhe, et al. “OpenPose: Realtime Multi-Person 2D Pose Estimation Using Part Affinity Fields.” IEEE Transactions on Pattern Analysis and Machine Intelligence 43.1 (2019): 172-186.
[PifPaf(2019)] Kreiss, Sven, Lorenzo Bertoni, and Alexandre Alahi. “Pifpaf: Composite fields for human pose estimation.” Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. 2019.
[SPM(2019)] Nie, Xuecheng, et al. “Single-stage multi-person pose machines.” Proceedings of the IEEE/CVF international conference on computer vision. 2019.
[HRNet(2019)] Sun, Ke, et al. “Deep high-resolution representation learning for human pose estimation.” Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. 2019.
[DirectPose(2019)] Tian, Zhi, Hao Chen, and Chunhua Shen. “Directpose: Direct end-to-end multi-person pose estimation.” arXiv preprint arXiv:1911.07451 (2019).
[HigherHRNet(2020)] Cheng, Bowen, et al. “Higherhrnet: Scale-aware representation learning for bottom-up human pose estimation.” Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. 2020.
[survey2020(1)] Munea, Tewodros Legesse, et al. “The progress of human pose estimation: A survey and taxonomy of models applied in 2D human pose estimation.” IEEE Access 8 (2020): 133330-133348.
[Point-setAnchors(2020)] Wei, Fangyun, et al. “Point-set anchors for object detection, instance segmentation and pose estimation.” Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part X 16. Springer International Publishing, 2020.
[PRTR(2021)] Li, Ke, et al. “Pose recognition with cascade transformers.” Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2021.
[TFPose(2021)] Mao, Weian, et al. “Tfpose: Direct human pose estimation with transformers.” arXiv preprint arXiv:2103.15320 (2021).
[PRTR(2021)] Li, Ke, et al. “Pose recognition with cascade transformers.” Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2021.
[InsPose(2021)] Shi, Dahu, et al. “Inspose: instance-aware networks for single-stage multi-person pose estimation.” Proceedings of the 29th ACM International Conference on Multimedia. 2021.
[FCPose(2021)] Mao, Weian, et al. “Fcpose: Fully convolutional multi-person pose estimation with dynamic instance-aware convolutions.” Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2021.
[PoseDet(2021)] Tian, Chenyu, et al. “Posedet: fast multi-person pose estimation using pose embedding.” 2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021). IEEE, 2021.
[PETR(2022)] Shi, Dahu, et al. “End-to-end multi-person pose estimation with transformers.” Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2022.
[survey(2022)] Lan, Gongjin, et al. “Vision-Based Human Pose Estimation via Deep Learning: A Survey.” IEEE Transactions on Human-Machine Systems (2022).
[AdaptivePose(2022)] Xiao, Yabo, et al. “Adaptivepose: Human parts as adaptive points.” Proceedings of the AAAI Conference on Artificial Intelligence. Vol. 36. No. 3. 2022.
[Transformer(2017)] Vaswani, Ashish, et al. “Attention is all you need.” Advances in neural information processing systems 30 (2017).
[CenterNet(2019)] Zhou, Xingyi, Dequan Wang, and Philipp Krähenbühl. “Objects as points.” arXiv preprint arXiv:1904.07850 (2019).
[DETR(2020)] Carion, Nicolas, et al. “End-to-end object detection with transformers.” Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part I 16. Springer International Publishing, 2020.
[DeformableDETR(2020)] Zhu, Xizhou, et al. “Deformable detr: Deformable transformers for end-to-end object detection.” arXiv preprint arXiv:2010.04159 (2020).
[SwinTransformer(2021)] Liu, Ze, et al. “Swin transformer: Hierarchical vision transformer using shifted windows.” Proceedings of the IEEE/CVF international conference on computer vision. 2021.
[v7labs-HPE] A Comprehensive Guide to Human Pose Estimation
