Stacked Hourglass Networks
Stacked Hourglass Networks 本工作为人类姿势估计任务引入了一种新型卷积网络架构。特征在所有尺度上进行处理，并进行整合，以最好地捕捉与身体相关的各种空间关系。我们展示了自下而上、自上而下的重复处理与中间监督的结合是如何提高网络性能的关键。我们将该架构称为 "堆叠沙漏 "网络，基于连续的池化和上采样步骤来产生最终的预测集。在FLIC和MPII基准上取得了最先进的结果，超过了所
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相关文章
- 1. Stacked Hourglass Networks
- 2. Stacked Hourglass Networks简析
- 3. Stacked Hourglass Networks 理解
- 4. Stacked Hourglass Networks for Human Pose Estimation
- 5. Stacked Hourglass Network for Human Pose Estimation
- 6. Stacked Hourglass Networks - 堆叠沙漏网络结构详解
- 7. 论文翻译：Stacked Hourglass Networks for Human Pose Estimation
- 8. 论文笔记 Stacked Hourglass Networks for Human Pose Estimation
- 9. 论文解读-Stacked Hourglass Networks for Human Pose Estimation
- 10. 论文阅读理解 - Stacked Hourglass Networks for Human Pose Estimation