Method

Deeper Spatial Pyramid Network with refined up-sampling [DSPyNet]
[Anonymous Submission]

Submitted on 10 Mar. 2018 11:59 by
[Anonymous Submission]

Running time:0.03 s
Environment:GPU @ 1 Ghz (lua)

Method Description:
we refine the network architecture at each pyramid
level into a deeper one through convolutional
factorization and the addition of the inception
module and the 1 x 1 convolutional layers to enhance
the representational power.we replace the bi-linear
interpolation method with small CNNs.
Parameters:
Adam optimization method with beta1 = 0.9 and beta2 =
0.999 and a batchsize of 16. And every epoch contains
4000 iterations.
Latex Bibtex:

Detailed Results

This page provides detailed results for the method(s) selected. For each of the first 20 test images, the number of erroneous pixels at all thresholds is depicted in the table. Underneath, the left input image, the disparity / end-point error map and the estimated (and interpolated) disparity / optical flow map are shown. The error map scales linearly between 0 (black) and >=5 (white) pixels error. Red denotes all occluded pixels, falling outside the image boundaries. The false color map is scaled to the largest ground truth disparity / flow value.

Test Set Average

Error Out-Noc Out-All Avg-Noc Avg-All
2 pixels 84.34 % 86.00 % 5.0 px 7.8 px
3 pixels 63.09 % 66.88 % 5.0 px 7.8 px
4 pixels 34.53 % 41.05 % 5.0 px 7.8 px
5 pixels 14.64 % 22.62 % 5.0 px 7.8 px
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Reflective Regions

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Test Image 0

Error Out-Noc Out-All Avg-Noc Avg-All
2 pixels 83.58 % 85.48 % 4.7 px 6.8 px
3 pixels 63.10 % 67.26 % 4.7 px 6.8 px
4 pixels 33.61 % 40.98 % 4.7 px 6.8 px
5 pixels 15.46 % 24.27 % 4.7 px 6.8 px
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Test Image 1

Error Out-Noc Out-All Avg-Noc Avg-All
2 pixels 82.36 % 83.85 % 3.4 px 3.8 px
3 pixels 59.81 % 62.98 % 3.4 px 3.8 px
4 pixels 28.55 % 33.76 % 3.4 px 3.8 px
5 pixels 7.90 % 13.86 % 3.4 px 3.8 px
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Test Image 2

Error Out-Noc Out-All Avg-Noc Avg-All
2 pixels 84.04 % 86.45 % 4.4 px 7.4 px
3 pixels 63.71 % 69.05 % 4.4 px 7.4 px
4 pixels 35.92 % 44.87 % 4.4 px 7.4 px
5 pixels 16.49 % 27.35 % 4.4 px 7.4 px
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Test Image 3

Error Out-Noc Out-All Avg-Noc Avg-All
2 pixels 83.37 % 85.95 % 4.2 px 6.9 px
3 pixels 60.01 % 65.98 % 4.2 px 6.9 px
4 pixels 31.37 % 40.76 % 4.2 px 6.9 px
5 pixels 12.72 % 23.00 % 4.2 px 6.9 px
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Test Image 4

Error Out-Noc Out-All Avg-Noc Avg-All
2 pixels 83.22 % 84.30 % 4.2 px 4.8 px
3 pixels 60.84 % 63.07 % 4.2 px 4.8 px
4 pixels 33.51 % 37.06 % 4.2 px 4.8 px
5 pixels 15.59 % 19.09 % 4.2 px 4.8 px
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Test Image 5

Error Out-Noc Out-All Avg-Noc Avg-All
2 pixels 82.79 % 85.13 % 3.7 px 7.8 px
3 pixels 61.14 % 66.06 % 3.7 px 7.8 px
4 pixels 30.67 % 39.00 % 3.7 px 7.8 px
5 pixels 9.69 % 19.58 % 3.7 px 7.8 px
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Test Image 6

Error Out-Noc Out-All Avg-Noc Avg-All
2 pixels 79.68 % 81.17 % 3.7 px 4.8 px
3 pixels 58.03 % 60.82 % 3.7 px 4.8 px
4 pixels 29.17 % 33.55 % 3.7 px 4.8 px
5 pixels 9.74 % 14.78 % 3.7 px 4.8 px
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Test Image 7

Error Out-Noc Out-All Avg-Noc Avg-All
2 pixels 85.40 % 87.16 % 5.0 px 9.1 px
3 pixels 63.74 % 68.28 % 5.0 px 9.1 px
4 pixels 34.80 % 42.82 % 5.0 px 9.1 px
5 pixels 14.42 % 23.81 % 5.0 px 9.1 px
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Test Image 8

Error Out-Noc Out-All Avg-Noc Avg-All
2 pixels 85.79 % 88.18 % 4.5 px 8.2 px
3 pixels 63.57 % 69.59 % 4.5 px 8.2 px
4 pixels 34.42 % 44.79 % 4.5 px 8.2 px
5 pixels 12.81 % 25.80 % 4.5 px 8.2 px
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Test Image 9

Error Out-Noc Out-All Avg-Noc Avg-All
2 pixels 85.58 % 87.38 % 4.3 px 6.1 px
3 pixels 69.32 % 73.02 % 4.3 px 6.1 px
4 pixels 42.08 % 48.80 % 4.3 px 6.1 px
5 pixels 22.84 % 30.73 % 4.3 px 6.1 px
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Test Image 10

Error Out-Noc Out-All Avg-Noc Avg-All
2 pixels 86.32 % 88.60 % 4.0 px 9.2 px
3 pixels 65.65 % 71.38 % 4.0 px 9.2 px
4 pixels 36.04 % 46.53 % 4.0 px 9.2 px
5 pixels 14.30 % 27.85 % 4.0 px 9.2 px
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Test Image 11

Error Out-Noc Out-All Avg-Noc Avg-All
2 pixels 84.34 % 85.55 % 3.9 px 6.1 px
3 pixels 62.30 % 65.17 % 3.9 px 6.1 px
4 pixels 31.24 % 36.78 % 3.9 px 6.1 px
5 pixels 9.21 % 15.75 % 3.9 px 6.1 px
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Test Image 12

Error Out-Noc Out-All Avg-Noc Avg-All
2 pixels 83.16 % 85.78 % 4.5 px 6.8 px
3 pixels 63.83 % 69.13 % 4.5 px 6.8 px
4 pixels 35.99 % 44.78 % 4.5 px 6.8 px
5 pixels 15.20 % 25.83 % 4.5 px 6.8 px
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Test Image 13

Error Out-Noc Out-All Avg-Noc Avg-All
2 pixels 83.61 % 85.55 % 6.3 px 9.1 px
3 pixels 64.02 % 68.20 % 6.3 px 9.1 px
4 pixels 36.84 % 43.81 % 6.3 px 9.1 px
5 pixels 16.88 % 25.41 % 6.3 px 9.1 px
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Test Image 14

Error Out-Noc Out-All Avg-Noc Avg-All
2 pixels 86.74 % 88.70 % 10.5 px 17.7 px
3 pixels 68.35 % 72.59 % 10.5 px 17.7 px
4 pixels 43.81 % 51.03 % 10.5 px 17.7 px
5 pixels 26.23 % 35.09 % 10.5 px 17.7 px
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Test Image 15

Error Out-Noc Out-All Avg-Noc Avg-All
2 pixels 84.89 % 87.23 % 4.9 px 9.0 px
3 pixels 65.54 % 70.76 % 4.9 px 9.0 px
4 pixels 41.11 % 49.78 % 4.9 px 9.0 px
5 pixels 23.01 % 33.89 % 4.9 px 9.0 px
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Test Image 16

Error Out-Noc Out-All Avg-Noc Avg-All
2 pixels 85.78 % 86.96 % 3.3 px 4.2 px
3 pixels 58.58 % 61.83 % 3.3 px 4.2 px
4 pixels 26.33 % 31.85 % 3.3 px 4.2 px
5 pixels 6.57 % 12.72 % 3.3 px 4.2 px
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Test Image 17

Error Out-Noc Out-All Avg-Noc Avg-All
2 pixels 85.44 % 87.59 % 5.6 px 10.1 px
3 pixels 65.19 % 70.20 % 5.6 px 10.1 px
4 pixels 37.58 % 46.24 % 5.6 px 10.1 px
5 pixels 16.98 % 27.88 % 5.6 px 10.1 px
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Test Image 18

Error Out-Noc Out-All Avg-Noc Avg-All
2 pixels 84.42 % 85.88 % 3.8 px 5.5 px
3 pixels 62.12 % 65.38 % 3.8 px 5.5 px
4 pixels 29.67 % 35.31 % 3.8 px 5.5 px
5 pixels 9.20 % 15.58 % 3.8 px 5.5 px
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Test Image 19

Error Out-Noc Out-All Avg-Noc Avg-All
2 pixels 81.36 % 82.96 % 3.4 px 4.5 px
3 pixels 58.52 % 61.80 % 3.4 px 4.5 px
4 pixels 27.65 % 33.01 % 3.4 px 4.5 px
5 pixels 7.22 % 13.39 % 3.4 px 4.5 px
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