The DOI matches its Crossref record; 72 of the 72 references it cites were found in a registry or an index.
3D Human Pose Estimation in Video With Temporal Convolutions and Semi-Supervised Training
Open accessAbstract
In this work, we demonstrate that 3D poses in video can be effectively estimated with a fully convolutional model based on dilated temporal convolutions over 2D keypoints. We also introduce back-projection, a simple and effective semi-supervised training method that leverages unlabeled video data. We start with predicted 2D keypoints for unlabeled video, then estimate 3D poses and finally back-project to the input 2D keypoints. In the supervised setting, our fully-convolutional model outperforms the previous best result from the literature by 6 mm mean per-joint position error on Human3.6M, corresponding to an error reduction of 11%, and the model also shows significant improvements on HumanEva-I. Moreover, experiments with back-projection show that it comfortably outperforms previous state-of-the-art results in semi-supervised settings where labeled data is scarce. Code and models are available at https://github.com/facebookresearch/VideoPose3D.
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He, K., Zhang, X., Ren, S., & Sun, J. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.90 · Cited by 235,474
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
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Microsoft COCO: Common Objects in Context
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Feature Pyramid Networks for Object Detection
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Self-citationMixSTE: Seq2seq Mixed Spatio-Temporal Encoder for 3D Human Pose Estimation in Video
Zhang, J., Tu, Z., Yang, J., Chen, Y., & Yuan, J. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr52688.2022.01288 · Cited by 426
MotionBERT: A Unified Perspective on Learning Human Motion Representations
Zhu, W., Ma, X., Liu, Z., Liu, L., Wu, W., & Wang, Y. (2023) · 2023 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.01385 · Cited by 348
Speech gesture generation from the trimodal context of text, audio, and speaker identity
Yoon, Y., Cha, B., Lee, J.-H., Jang, M., Lee, J., Kim, J., & Lee, G. (2020) · ACM Transactions on Graphics · doi:10.1145/3414685.3417838 · Cited by 328
Attention Mechanism Exploits Temporal Contexts: Real-Time 3D Human Pose Reconstruction
Liu, R., Shen, J., Wang, H., Chen, C., Cheung, S.-C., & Asari, V. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr42600.2020.00511 · Cited by 266
Metadata
- Authors
- Pavllo, D., Feichtenhofer, C., Grangier, D., & Auli, M.
- Venue
- 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
- Publisher
- IEEE
- Published
- 2019-06
- Pages
- 7745-7754
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2903549000
- Cited by
- 1,297
- References
- 72
- FWCI
- 45.12
- Type
- conference paper
- Language
- en
- Open access
- green
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