9D Rotation Representation-SVD Fusion with Deep Learning for Unconstrained Head Pose Estimation

[1] Strazdas Dominykas, Hintz Jan, AlHamadi Ayoub. Robo-hud: interaction concept for contactless operation of industrial cobotic systems [J]. Applied Sciences, 2021, 11(12):5366-5366. Dominykas Strazdas Jan Hintz Ayoub AlHamadi . Robo-hud: interaction concept for contactless operation of industrial cobotic systems [J] . Applied Sciences , 2021 , 11 ( 12): 5366 - 5366 . Search in Google Scholar

[2] CHARISSIS V, FALAH J, LAGOO R, et al. Employing emerging technologies to develop and evaluate in-vehicle intelligent systems for driver support: infotainment ar hud case study [J]. Applied Sciences, 2021,11(4):1397-1397. CHARISSIS V FALAH J LAGOO R Employing emerging technologies to develop and evaluate in-vehicle intelligent systems for driver support: infotainment ar hud case study [J] . Applied Sciences , 2021 , 11 ( 4): 1397 - 1397 . Search in Google Scholar

[3] Werner, P., Saxen, F., & Al-Hamadi, A. Landmark based head pose estimation benchmark and method. In ICIP, 2017. Werner P. Saxen F. Al-Hamadi A. Landmark based head pose estimation benchmark and method . In ICIP , 2017 . Search in Google Scholar

[4] Ruiz, N., Chong, E., & Rehg, J. M. Fine-grained head pose estimation without keypoints. In CVPR, 2018. Ruiz N. Chong E. Rehg J. M. Fine-grained head pose estimation without keypoints . In CVPR 2018 . Search in Google Scholar

[5] Hsu H W, Wu T Y, Wan S, et al. QuatNet: QuaternionBased Head Pose Estimation with Multiregression Loss [J]. Multimedia, IEEE Transactions on, 2018. DOI:10.1109/TMM.2018.2866770. Hsu H W Wu T Y Wan S QuatNet: QuaternionBased Head Pose Estimation with Multiregression Loss [J] . Multimedia, IEEE Transactions on, 2018 . DOI: 10.1109/TMM.2018.2866770 . Open DOISearch in Google Scholar

[6] Huang B, Chen R, Xu W, et al. Improving head pose estimation using two-stage ensembles with top-k regression [J]. Image and Vision Computing, 2019, 93.DOI:10.1016/j.imavis.2019.11.005. Huang B Chen R Xu W Improving head pose estimation using two-stage ensembles with top-k regression [J] . Image and Vision Computing , 2019 , 93 . DOI: 10.1016/j.imavis.2019.11.005 . Open DOISearch in Google Scholar

[7] Zhou Y, Gregson J. WHENet: Real-time Fine-Grained Estimation for Wide Range Head Pose [J]. 2020. DOI:10.48550/arXiv.2005.10353. Zhou Y Gregson J. WHENet: Real-time Fine-Grained Estimation for Wide Range Head Pose [J] . 2020 . DOI: 10.48550/arXiv.2005.10353 . Open DOISearch in Google Scholar

[8] Yang T Y, Chen Y T, Lin Y Y, et al. FSA-Net: Learning Fine-Grained Structure Aggregation for Head Pose Estimation from a Single Image [J]. IEEE, 2020. DOI:10.1109/CVPR.2019.00118. Yang T Y Chen Y T Lin Y Y FSA-Net: Learning Fine-Grained Structure Aggregation for Head Pose Estimation from a Single Image [J] . IEEE , 2020 . DOI: 10.1109/CVPR.2019.00118 . Open DOISearch in Google Scholar

[9] Cao Z, Chu Z, Liu D, et al. A Vector-based Representation to Enhance Head Pose Estimation[C]//Workshop on Applications of Computer Vision. IEEE, 2021. DOI:10.1109/WACV48630.2021.00123. Cao Z Chu Z Liu D A Vector-based Representation to Enhance Head Pose Estimation[C]//Workshop on Applications of Computer Vision . IEEE , 2021 . DOI: 10.1109/WACV48630.2021.00123 . Open DOISearch in Google Scholar

[10] Zhang H, Wang M, Liu Y, et al. FDN: Feature Decoupling Network for Head Pose Estimation [J]. Proceedings of the AAAI Conference on Artificial Intelligence, 2020, 34(7):12789-12796. DOI:10.1609/aaai.v34i07.6974. Zhang H Wang M Liu Y FDN: Feature Decoupling Network for Head Pose Estimation [J] . Proceedings of the AAAI Conference on Artificial Intelligence , 2020 , 34 ( 7 ): 12789 - 12796 . DOI: 10.1609/aaai.v34i07.6974 . Open DOISearch in Google Scholar

[11] Dhingra N. LwPosr: Lightweight Efficient FineGrained Head Pose Estimation [J]. arXiv e-prints, 2022. DOI:10.48550/arXiv.2202.03544. Dhingra N. LwPosr: Lightweight Efficient FineGrained Head Pose Estimation [J] . arXiv e-prints , 2022 . DOI: 10.48550/arXiv.2202.03544 . Open DOISearch in Google Scholar

[12] Zhou Y, Barnes C, Lu J, et al. On the Continuity of Rotation Representations in Neural Networks[C]//2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2019. DOI:10.1109/CVPR.2019.00589. Zhou Y Barnes C Lu J On the Continuity of Rotation Representations in Neural Networks[C] // 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) . IEEE , 2019 . DOI: 10.1109/CVPR.2019.00589 . Open DOISearch in Google Scholar

[13] Geist A R, Frey J, Zobro M, et al. Learning with 3D rotations, a hitchhiker’s guide to SO (3) [J]. arxiv preprint arxiv:2404.11735, 2024. Geist A R Frey J Zobro M Learning with 3D rotations, a hitchhiker’s guide to SO (3) [J] . arxiv preprint arxiv:2404.11735 , 2024 . Search in Google Scholar

[14] Tan M, Le Q V. EfficientNetV2: Smaller Models and Faster Training [J]. 2021. DOI:10.48550/arXiv.2104.00298. Tan M Le Q V. EfficientNetV2: Smaller Models and Faster Training [J] . 2021 . DOI: 10.48550/arXiv.2104.00298 . Open DOISearch in Google Scholar

[15] Xiangyu Zhu, Zhen Lei, Xiaoming Liu 0002, et al. Face alignment across large poses: a 3d solution. [J]. CoRR, 2015. Zhu Xiangyu Lei Zhen Liu 0002 Xiaoming Face alignment across large poses: a 3d solution. [J] . CoRR , 2015 . Search in Google Scholar

[16] Zhu X, Lei Z, Yan J, et al. High-fidelity Pose and Expression Normalization for face recognition in the wild [J]. IEEE, 2015. DOI:10.1109/CVPR.2015.7298679. Zhu X Lei Z Yan J High-fidelity Pose and Expression Normalization for face recognition in the wild [J] . IEEE , 2015 . DOI: 10.1109/CVPR.2015.7298679 . Open DOISearch in Google Scholar

[17] Fanelli G, Matthias Dantone. Random Forests for Real Time 3D Face Analysis [J]. International Journal of Computer Vision, 2013, 101(3):437-458. DOI:10.1007/s11263-012-0549-0. Fanelli G Dantone Matthias . Random Forests for Real Time 3D Face Analysis [J] . International Journal of Computer Vision , 2013 , 101 ( 3 ): 437 - 458 . DOI: 10.1007/s11263-012-0549-0 . Open DOISearch in Google Scholar

[18] Hempel T, Abdelrahman A A, Al-Hamadi A.6D Rotation Representation for Unconstrained Head Pose Estimation [J]. arXiv e-prints, 2022. DOI:10.48550/arXiv.2202.12555. Hempel T Abdelrahman A A Al-Hamadi A. 6D Rotation Representation for Unconstrained Head Pose Estimation [J] . arXiv e-prints , 2022 . DOI: 10.48550/arXiv.2202.12555 . Open DOISearch in Google Scholar

[19] Zhang K, Zhang Z, Li Z, et al. Joint Face Detection and Alignment Using Multitask Cascaded Convolutional Networks [J]. IEEE Signal Processing Letters, 2016, 23(10):1499-1503. DOI:10.1109/LSP.2016.2603342. Zhang K Zhang Z Li Z Joint Face Detection and Alignment Using Multitask Cascaded Convolutional Networks [J] . IEEE Signal Processing Letters , 2016 , 23 ( 10 ): 1499 - 1503 . DOI: 10.1109/LSP.2016.2603342 . Open DOISearch in Google Scholar

[20] Liu H, Fang S, Zhang Z, et al. MFDNet: Collaborative Poses Perception and Matrix Fisher Distribution for Head Pose Estimation [J]. IEEE Transactions on Multimedia, 2021, PP (99): 1-1. DOI:10.1109/TMM.2021.3081873. Liu H Fang S Zhang Z MFDNet: Collaborative Poses Perception and Matrix Fisher Distribution for Head Pose Estimation [J] . IEEE Transactions on Multimedia , 2021 , PP ( 99 ): 1 - 1 . DOI: 10.1109/TMM.2021.3081873 . Open DOISearch in Google Scholar

[21] Aghli N, Ribeiro E. A Data-Driven Approach to Improve 3D Head-Pose Estimation[C]//International Symposium on Visual Computing. Springer, Cham, 2021. DOI:10.1007/978-3-030-90439-5_43. Aghli N Ribeiro E. A Data-Driven Approach to Improve 3D Head-Pose Estimation[C] // International Symposium on Visual Computing . Springer , Cham , 2021 . DOI: 10.1007/978-3-030-90439-5_43 . Open DOISearch in Google Scholar

[22] He K, Zhang X, Ren S, et al. Deep Residual Learning for Image Recognition [J]. IEEE, 2016. DOI:10.1109/CVPR.2016.90. He K Zhang X Ren S Deep Residual Learning for Image Recognition [J] . IEEE , 2016 . DOI: 10.1109/CVPR.2016.90 . Open DOISearch in Google Scholar