Mask R-CNNを実装してみました
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Mask R-CNN is a neural network model that performs both object detection and segmentation. It uses a Feature Pyramid Network and ROI Align to extract features from each region of interest and predict a segmentation mask in addition to class and bounding box. Mask R-CNN has been implemented in frameworks such as TensorFlow, Chainer, and MXNet and can be used for tasks like instance segmentation, keypoint detection, and depth segmentation from Kinect data.
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- 2. • • Twitter: @tkato_ • https://www.teamlab.art/ • •
- 4. Mask R-CNN Task:Instance Segmentation, Keypoint detection
- 5. chainercv Faster-RCNN Segmentation Mask branch DeNA (https://engineer.dena.jp/2017/12/chainercvmask-r-cnn.html)
- 6. : Feature Pyramid Network • Deep Upsampling • Chainer
- 7. : RoI Align Crop & Resize
- 8. RoI Align • chainer ROIPooling2D • • forward cpu gpu • backward • Caffe2 RoIAlign forward • CuPy ElementwiseKernel
- 11. • Kinect V2 • SDK • Depth or IR User Segmentation Keypoint Detection • Mask RCNN
- 13. Mask RCNN http://deeplearning.csail.mit.edu/instance_ross.pdf RoI Align Mask R-CNN RoI Align Fast(er) R-CNN RoI Pooling https://qiita.com/yu4u/items/5cbe9db166a5d72f9eb8 Keynote template http://sanographix.github.io/azusa-colors/