UniPose: Unified Human Pose Estimation in Single Images and Videos
網絡結構如上如所示 圖片經過ResNet-101網絡，經過WASP模塊，在經過Decoder,得到關鍵點的特徵圖heatmap，每一個heatmap對應一個關節。在通過雙線性差值回覆原始的分辨率。在通過局部最大值操作定位最後的關鍵點。 創新：WASP模塊：瀑布結構 WASP模塊學習了ASPP配置的大的感受野和級聯方式。參考了 ASPP,級聯和Res2Net的結構。 與ASPP和Res2N
相關文章
- 1. 3D Human Pose Estimation = 2D Pose Estimation + Matching(2017)
- 2. 【轉】DensePose: Dense Human Pose Estimation In The Wild
- 3. 論文閱讀：《Flowing ConvNets for Human Pose Estimation in Videos》ICCV 2015
- 4. DensePose: Dense Human Pose Estimation In The Wild
- 5. Fast Human Pose Estimation
- 6. Paper Reading:Real-time human pose recognition in parts from single depth images
- 7. (20) Recurrent Human Pose Estimation
- 8. Human Pose Estimation using Global and Local Normalization
- 9. Simple Baselines for Human Pose Estimation and Tracking
- 10. VIBE: Video Inference for Human Body Pose and Shape Estimation
- 更多相關文章...
- • Docker images 命令 - Docker命令大全
- • SQL IN 操作符 - SQL 教程
- • RxJava操作符（七）Conditional and Boolean
- • Docker 清理命令
相關標籤/搜索
每日一句
-
每一个你不满意的现在，都有一个你没有努力的曾经。
歡迎關注本站公眾號,獲取更多信息
相關文章
- 1. 3D Human Pose Estimation = 2D Pose Estimation + Matching(2017)
- 2. 【轉】DensePose: Dense Human Pose Estimation In The Wild
- 3. 論文閱讀：《Flowing ConvNets for Human Pose Estimation in Videos》ICCV 2015
- 4. DensePose: Dense Human Pose Estimation In The Wild
- 5. Fast Human Pose Estimation
- 6. Paper Reading:Real-time human pose recognition in parts from single depth images
- 7. (20) Recurrent Human Pose Estimation
- 8. Human Pose Estimation using Global and Local Normalization
- 9. Simple Baselines for Human Pose Estimation and Tracking
- 10. VIBE: Video Inference for Human Body Pose and Shape Estimation