Pose Estimation Models
Stacked Hourglass Network
Introduced by Newell et al. in Stacked Hourglass Networks for Human Pose EstimationStacked Hourglass Networks are a type of convolutional neural network for pose estimation. They are based on the successive steps of pooling and upsampling that are done to produce a final set of predictions.
Source: Stacked Hourglass Networks for Human Pose Estimation
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Object Detection | 9 | 17.31% |
| Pose Estimation | 8 | 15.38% |
| Semantic Segmentation | 2 | 3.85% |
| Multi-Task Learning | 2 | 3.85% |
| Multi-Person Pose Estimation | 2 | 3.85% |
| Stereo Matching | 2 | 3.85% |
| Stereo Matching Hand | 2 | 3.85% |
| Table Detection | 1 | 1.92% |
| Table Recognition | 1 | 1.92% |
Hourglass Module
