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Fully Convolutional Networks for Semantic Segmentation [1] Jonathan Long, Evan Shelhamer and Trevor Darrell ECE 289G: Paper Presentation Philipp Gysel

Fully Convolutional Networks for Semantic Segmentation [1] › ~yjlee › teaching › ecs289g... · Fully Convolutional Networks for Semantic Segmentation [1] Jonathan Long, Evan

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Page 1: Fully Convolutional Networks for Semantic Segmentation [1] › ~yjlee › teaching › ecs289g... · Fully Convolutional Networks for Semantic Segmentation [1] Jonathan Long, Evan

Fully Convolutional Networks for Semantic Segmentation [1] Jonathan Long, Evan Shelhamer and Trevor Darrell

ECE 289G: Paper Presentation Philipp Gysel

Page 2: Fully Convolutional Networks for Semantic Segmentation [1] › ~yjlee › teaching › ecs289g... · Fully Convolutional Networks for Semantic Segmentation [1] Jonathan Long, Evan

ECE 289G Paper Presentation, Philipp Gysel Slide 2

Analyse Genome of C Elegans

1) Nucleus

2) Nucleus membrane

3) Cytoplasm

4) Cell wall

5) External medium

[2]

an

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Page 3: Fully Convolutional Networks for Semantic Segmentation [1] › ~yjlee › teaching › ecs289g... · Fully Convolutional Networks for Semantic Segmentation [1] Jonathan Long, Evan

PASCAL VOC 2011

ECE 289G Paper Presentation, Philipp Gysel Slide 3

[3]

Person

Motorbike

Chair

Page 4: Fully Convolutional Networks for Semantic Segmentation [1] › ~yjlee › teaching › ecs289g... · Fully Convolutional Networks for Semantic Segmentation [1] Jonathan Long, Evan

Accuracy Metric

▪ Mean intersection over union (IU):

▪ Pixel Accuracy:

ECE 289G Paper Presentation, Philipp Gysel Slide 4

[1]

Prediction Ground truth

Page 5: Fully Convolutional Networks for Semantic Segmentation [1] › ~yjlee › teaching › ecs289g... · Fully Convolutional Networks for Semantic Segmentation [1] Jonathan Long, Evan

FCN: Fully Connected CNN

ECE 289G Paper Presentation, Philipp Gysel Slide 5

[1]

“Cat”

“Cat”

“Dog”

CNN:

FCN:

Page 6: Fully Convolutional Networks for Semantic Segmentation [1] › ~yjlee › teaching › ecs289g... · Fully Convolutional Networks for Semantic Segmentation [1] Jonathan Long, Evan

FCN Speedup

ECE 289G Paper Presentation, Philipp Gysel Slide 6

1.2

22

110

0

20

40

60

80

100

120

1 227x227 100 500x500 100 500x500

Runtime of FCN vs naïve CNNs

Inference [ms]

• Keep kernel sizes

and strides

• Replace dense

layer with

convolution

[1]

Page 7: Fully Convolutional Networks for Semantic Segmentation [1] › ~yjlee › teaching › ecs289g... · Fully Convolutional Networks for Semantic Segmentation [1] Jonathan Long, Evan

Upsampling: Backwards strided convolution

ECE 289G Paper Presentation, Philipp Gysel Slide 7

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In-network upsampling

pixelwise loss

Page 8: Fully Convolutional Networks for Semantic Segmentation [1] › ~yjlee › teaching › ecs289g... · Fully Convolutional Networks for Semantic Segmentation [1] Jonathan Long, Evan

Deep jet

ECE 289G Paper Presentation, Philipp Gysel Slide 8

[1]

Page 9: Fully Convolutional Networks for Semantic Segmentation [1] › ~yjlee › teaching › ecs289g... · Fully Convolutional Networks for Semantic Segmentation [1] Jonathan Long, Evan

Experiment setup

▪ Pre-trained networks: AlexNet, VGG and GoogLeNet

▪ Convert dense to convolutional layer

▪ Discard final classifier

▪ Add deconvolution layer for up-sampling

▪ Fine-tuning end-to-end on

▪ PASCAL VOC

▪ NYUDv2

▪ SIFT

ECE 289G Paper Presentation, Philipp Gysel Slide 9

[4],

[5

]

Page 10: Fully Convolutional Networks for Semantic Segmentation [1] › ~yjlee › teaching › ecs289g... · Fully Convolutional Networks for Semantic Segmentation [1] Jonathan Long, Evan

Experiment #1: PASCAL VOC 2011

▪ 20 classes (e.g. airplane, boat, bicycle, person, cat)

▪ Relative margin of 20% to previous state-of-art

▪ Inference time is reduced 114x and 286x respectively

ECE 289G Paper Presentation, Philipp Gysel Slide 10

[1],

[3

]

Page 11: Fully Convolutional Networks for Semantic Segmentation [1] › ~yjlee › teaching › ecs289g... · Fully Convolutional Networks for Semantic Segmentation [1] Jonathan Long, Evan

Experiment #2: NYUDv2

▪ 40 classes from indoor scenes

▪ Densely labeled RGB and depth images

ECE 289G Paper Presentation, Philipp Gysel Slide 11

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Page 12: Fully Convolutional Networks for Semantic Segmentation [1] › ~yjlee › teaching › ecs289g... · Fully Convolutional Networks for Semantic Segmentation [1] Jonathan Long, Evan

Experiment #3: SIFT Flow

▪ 33 semantic categories (e.g. bridge, mountain)

▪ 3 geometric categories (horizontal, vertical)

▪ Two-headed FCN

ECE 289G Paper Presentation, Philipp Gysel Slide 12

[1]

Page 13: Fully Convolutional Networks for Semantic Segmentation [1] › ~yjlee › teaching › ecs289g... · Fully Convolutional Networks for Semantic Segmentation [1] Jonathan Long, Evan

Questions?

ECE 289G Paper Presentation, Philipp Gysel Slide 13

Page 14: Fully Convolutional Networks for Semantic Segmentation [1] › ~yjlee › teaching › ecs289g... · Fully Convolutional Networks for Semantic Segmentation [1] Jonathan Long, Evan

References

[1] Long, Jonathan, Evan Shelhamer, and Trevor Darrell. "Fully convolutional networks for semantic segmentation." arXiv preprint arXiv:1411.4038 (2014).

[2] Ning, Feng, et al. "Toward automatic phenotyping of developing embryos from videos." Image Processing, IEEE Transactions on 14.9 (2005): 1360-1371.

[3] Everingham, Mark, et al. "The pascal visual object classes (voc) challenge." International journal of computer vision 88.2 (2010): 303-338.

[4] Krizhevsky, Alex, Ilya Sutskever, and Geoffrey E. Hinton. "Imagenet classification with deep convolutional neural networks." Advances in neural information processing systems. 2012.

[5] Szegedy, Christian, et al. "Going deeper with convolutions." arXiv preprint arXiv:1409.4842 (2014).

ECE 289G Paper Presentation, Philipp Gysel Slide 14