R-C3D: Region Convolutional 3D Network for Temporal Activity Detection
這篇文章是ICCV 2017的一篇文章，作者主要是以C3D網絡爲基礎。借鑑了Faster RCNN的思路，對於任意的輸入視頻L，先進行proposal，然後3D-pooling,最後後進行分類和迴歸操作。文章主要貢獻點有3個： 可以針對任意長度視頻、任意長度行爲進行端到端的檢測 速度很快(是目前網絡的5倍)，通過共享Progposal generation 和Classification網絡的C3
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相關文章
- 1. R-C3D Region Convolutional 3D Network for Temporal Activity Detection
- 2. R-C3D: Region Convolutional 3D Network for Temporal Activity Detection
- 3. 3d fully convolutional network for vehicle detection in point cloud
- 4. Convolutional Neural Network - Object Detection
- 5. PBRNet:Progressive Boundary Refinement Network for Temporal Action Detection （AAAI 2020）
- 6. 3D Fully Convolutional Network for Vehicle Detection in Point Cloud解析(3D-CNN模型）
- 7. MS-TCN: Multi-Stage Temporal Convolutional Network for Action Segmentation
- 8. Region-Based Convolutional Networks for Accurate Object Detection and Segmentation
- 9. TricorNet: A Hybrid Temporal Convolutional and Recurrent Network for Video Action Segmentation 翻譯
- 10. 【翻譯】Convolutional Experts Network for Facial Landmark Detection