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Clockwork ConvNets for Video Semantic Segmentation

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Slide for Paper: Clockwork Convnets

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Clockwork ConvNets for Video Semantic Segmentation

  1. 1. Clockwork ConvNets for Video Semantic Segmentation 2018/02/10
  2. 2. Fully Convolutional Networks
  3. 3. The Idea – Adapt FCN to Video Segmentation • Naïve Idea: segment video frames as still images • Drawbacks • Computation redundancy • Ignoring the temporal continuity inherit • Two Key observations: • The speed of motion varies in video. • Deeper layers in the feature hierarchy change more slowly.
  4. 4. Analysis
  5. 5. The Overall Framework
  6. 6. Clockwork ConvNets on Time
  7. 7. Clockwork • Fix-rated clockwork • Exponential clockwork: 1, 2, 4, 8, … • Alternating clockwork: 0, 1, 0, 1 • Adaptive clockwork • Threshold clockwork: • Learned clockwork:
  8. 8. Fix-rated Clockwork – translated PASCAL
  9. 9. Adaptive Clockwork – YouTube-Objects
  10. 10. The Idea -- Clockwork • Hardship in learning Long-term dependencies (Vanishing gradient)
  11. 11. The Clockwork RNN
  12. 12. The End

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