The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
DeepCut: Joint Subset Partition and Labeling for Multi Person Pose Estimation
Open accessAbstract
This paper considers the task of articulated human pose estimation of multiple people in real world images. We propose an approach that jointly solves the tasks of detection and pose estimation: it infers the number of persons in a scene, identifies occluded body parts, and disambiguates body parts between people in close proximity of each other. This joint formulation is in contrast to previous strategies, that address the problem by first detecting people and subsequently estimating their body pose. We propose a partitioning and labeling formulation of a set of body-part hypotheses generated with CNN-based part detectors. Our formulation, an instance of an integer linear program, implicitly performs non-maximum suppression on the set of part candidates and groups them to form configurations of body parts respecting geometric and appearance constraints. Experiments on four different datasets demonstrate state-of-the-art results for both single person and multi person pose estimation.
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Cites
Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs
Chen, L.-C., Papandreou, G., Kokkinos, I., Murphy, K., & Yuille, A. L. (2014) · arXiv · doi:10.48550/arxiv.1412.7062 · Cited by 4,213
Bansal, N., Blum, A., & Chawla, S. (2004) · Machine Learning · doi:10.1023/b:mach.0000033116.57574.95 · Cited by 1,075
Deza, M. M., & Laurent, M. (1997) · Algorithms and combinatorics · doi:10.1007/978-3-642-04295-9 · Cited by 1,014
Correlation clustering in general weighted graphs
Demaine, E. D., Emanuel, D., Fiat, A., & Immorlica, N. (2006) · Theoretical Computer Science · doi:10.1016/j.tcs.2006.05.008 · Cited by 283
Image Segmentation UsingHigher-Order Correlation Clustering
Kim, S., Yoo, C. D., Nowozin, S., & Kohli, P. (2014) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2014.2303095 · Cited by 127
Probabilistic image segmentation with closedness constraints
Andres, B., Kappes, J. H., Beier, T., Köthe, U., & Hamprecht, F. A. (2011) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2011.6126550 · Cited by 105
Self-citationParsing occluded people by flexible compositions
Chen, X., & Yuille, A. (2015) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2015.7299020 · Cited by 72
Fast Planar Correlation Clustering for Image Segmentation
Yarkony, J., Ihler, A., & Fowlkes, C. C. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-33783-3_41 · Cited by 58
Ensemble Segmentation Using Efficient Integer Linear Programming
Alush, A., & Goldberger, J. (2012) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2011.280 · Cited by 52
Cited by
Realtime Multi-person 2D Pose Estimation Using Part Affinity Fields
Cao, Z., Simon, T., Wei, S.-E., & Sheikh, Y. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.143 · Cited by 7,539
“Table 1 compares mAP performance between our method and other approaches on the same subset of 288 testing images as in [27], and the entire MPI testing set.”
BackgroundMethodInfluentialDeep High-Resolution Representation Learning for Human Pose Estimation
Sun, K., Xiao, B., Liu, D., & Wang, J. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2019.00584 · Cited by 5,984
Stacked Hourglass Networks for Human Pose Estimation
Newell, A., Yang, K., & Deng, J. (2016) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-46484-8_29 · Cited by 5,634
OpenPose: Realtime Multi-Person 2D Pose Estimation Using Part Affinity Fields
Cao, Z., Hidalgo, G., Simon, T., Wei, S.-E., & Sheikh, Y. (2021) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2019.2929257 · Cited by 5,536
DeepLabCut: markerless pose estimation of user-defined body parts with deep learning
Mathis, A., Mamidanna, P., Cury, K. M., Abe, T., Murthy, V. N., Mathis, M. W., & Bethge, M. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0209-y · Cited by 5,187
Metadata
- Authors
- Pishchulin, L., Insafutdinov, E., Tang, S., Andres, B., Andriluka, M., Gehler, P., & Schiele, B.
- Venue
- 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
- Publisher
- IEEE
- Published
- 2016-06
- Pages
- 4929-4937
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2175012183
- Cited by
- 1,051
- References
- 9
- FWCI
- 40.06
- Type
- conference paper
- Language
- en
- Open access
- green
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- Pishchulin, L., Insafutdinov, E., Tang, S., Andres, B., Andriluka, M., Gehler, P., & Schiele, B. (2016). DeepCut: Joint Subset Partition and Labeling for Multi Person Pose Estimation. 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). https://doi.org/10.1109/cvpr.2016.533
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