Name
Abstract | ||
|---|---|---|
•Ensemble modeling is applied to human pose estimation.•Complex interdependence among pose predictions is captured by a deep neural network.•The separated models can be trained in an efficient and distributed manner.•Our model compares favorably against baseline and state-of-the-art methods. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.cviu.2017.12.005 | Computer Vision and Image Understanding |
Keywords | Field | DocType |
Human pose estimation,Ensemble models,Pose modality | Ensemble forecasting,Convolution,Convolutional neural network,Deconvolution,Pose,Complex interdependence,Artificial intelligence,Machine learning,Mathematics | Journal |
Volume | Issue | ISSN |
169 | 1 | 1077-3142 |
Citations | PageRank | References |
3 | 0.39 | 43 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuki Kawana | 1 | 3 | 1.06 |
| Norimichi Ukita | 2 | 227 | 42.60 |
| Jia-Bin Huang | 3 | 920 | 42.90 |
| Yang Ming-Hsuan | 4 | 15303 | 620.69 |