Method

Multistage full matching [MFM-Net]
[Anonymous Submission]

Submitted on 2 Sep. 2020 08:03 by
[Anonymous Submission]

Running time:0.47 s
Environment:GPU @ 1.5 Ghz (Python)

Method Description:
The high-resolution similarity distribution
estimation is learned directly in MFM through simply
decomposing the full matching task into multiple
stages of the cost volume refinement module.
Specifically, we decompose the high-resolution
predicted results into multiple groups, and every
stage of the newly designed cost volume refinement
module learns only to estimate the results for a
group of points. In this way, the high-resolution
results are obtained by multistage CNNs instead of
linear interpolation, and the computation cost is
maintained for the decomposition mechanism. In
addition,we propose an interphase mutual aid method,
in which the prediction results of other stages vote
on the distribution, and the voting information
provides a reference for the current estimation.
Parameters:
n=4,\gamma = 1
Latex Bibtex:

Detailed Results

This page provides detailed results for the method(s) selected. For the first 20 test images, the percentage of erroneous pixels is depicted in the table. We use the error metric described in Object Scene Flow for Autonomous Vehicles (CVPR 2015), which considers a pixel to be correctly estimated if the disparity or flow end-point error is <3px or <5% (for scene flow this criterion needs to be fulfilled for both disparity maps and the flow map). Underneath, the left input image, the estimated results and the error maps are shown (for disp_0/disp_1/flow/scene_flow, respectively). The error map uses the log-color scale described in Object Scene Flow for Autonomous Vehicles (CVPR 2015), depicting correct estimates (<3px or <5% error) in blue and wrong estimates in red color tones. Dark regions in the error images denote the occluded pixels which fall outside the image boundaries. The false color maps of the results are scaled to the largest ground truth disparity values / flow magnitudes.

Test Set Average

Error D1-bg D1-fg D1-all
All / All 1.51 3.67 1.87
All / Est 1.51 3.67 1.87
Noc / All 1.39 3.36 1.72
Noc / Est 1.39 3.36 1.72
This table as LaTeX

Test Image 0

Error D1-bg D1-fg D1-all
All / All 1.63 0.45 1.47
All / Est 1.63 0.45 1.47
Noc / All 1.58 0.45 1.42
Noc / Est 1.58 0.45 1.42
This table as LaTeX

Input Image

D1 Result

D1 Error


Test Image 1

Error D1-bg D1-fg D1-all
All / All 1.43 2.16 1.51
All / Est 1.43 2.16 1.51
Noc / All 1.36 2.16 1.45
Noc / Est 1.36 2.16 1.45
This table as LaTeX

Input Image

D1 Result

D1 Error


Test Image 2

Error D1-bg D1-fg D1-all
All / All 2.03 0.94 1.98
All / Est 2.03 0.94 1.98
Noc / All 1.96 0.94 1.91
Noc / Est 1.96 0.94 1.91
This table as LaTeX

Input Image

D1 Result

D1 Error


Test Image 3

Error D1-bg D1-fg D1-all
All / All 2.11 0.84 2.00
All / Est 2.11 0.84 2.00
Noc / All 2.10 0.84 1.98
Noc / Est 2.10 0.84 1.98
This table as LaTeX

Input Image

D1 Result

D1 Error


Test Image 4

Error D1-bg D1-fg D1-all
All / All 0.67 0.25 0.60
All / Est 0.67 0.25 0.60
Noc / All 0.66 0.25 0.59
Noc / Est 0.66 0.25 0.59
This table as LaTeX

Input Image

D1 Result

D1 Error


Test Image 5

Error D1-bg D1-fg D1-all
All / All 3.06 0.76 2.85
All / Est 3.06 0.76 2.85
Noc / All 2.82 0.76 2.63
Noc / Est 2.82 0.76 2.63
This table as LaTeX

Input Image

D1 Result

D1 Error


Test Image 6

Error D1-bg D1-fg D1-all
All / All 4.24 0.81 3.88
All / Est 4.24 0.81 3.88
Noc / All 4.33 0.81 3.96
Noc / Est 4.33 0.81 3.96
This table as LaTeX

Input Image

D1 Result

D1 Error


Test Image 7

Error D1-bg D1-fg D1-all
All / All 0.41 2.70 0.85
All / Est 0.41 2.70 0.85
Noc / All 0.41 2.70 0.86
Noc / Est 0.41 2.70 0.86
This table as LaTeX

Input Image

D1 Result

D1 Error


Test Image 8

Error D1-bg D1-fg D1-all
All / All 0.44 1.85 0.70
All / Est 0.44 1.85 0.70
Noc / All 0.44 1.85 0.70
Noc / Est 0.44 1.85 0.70
This table as LaTeX

Input Image

D1 Result

D1 Error


Test Image 9

Error D1-bg D1-fg D1-all
All / All 0.43 1.18 0.62
All / Est 0.43 1.18 0.62
Noc / All 0.43 1.23 0.63
Noc / Est 0.43 1.23 0.63
This table as LaTeX

Input Image

D1 Result

D1 Error


Test Image 10

Error D1-bg D1-fg D1-all
All / All 1.04 2.42 1.36
All / Est 1.04 2.42 1.36
Noc / All 1.05 2.42 1.37
Noc / Est 1.05 2.42 1.37
This table as LaTeX

Input Image

D1 Result

D1 Error


Test Image 11

Error D1-bg D1-fg D1-all
All / All 0.67 0.33 0.61
All / Est 0.67 0.33 0.61
Noc / All 0.67 0.33 0.61
Noc / Est 0.67 0.33 0.61
This table as LaTeX

Input Image

D1 Result

D1 Error


Test Image 12

Error D1-bg D1-fg D1-all
All / All 0.75 0.75 0.75
All / Est 0.75 0.75 0.75
Noc / All 0.61 0.75 0.62
Noc / Est 0.61 0.75 0.62
This table as LaTeX

Input Image

D1 Result

D1 Error


Test Image 13

Error D1-bg D1-fg D1-all
All / All 0.74 0.01 0.65
All / Est 0.74 0.01 0.65
Noc / All 0.70 0.01 0.61
Noc / Est 0.70 0.01 0.61
This table as LaTeX

Input Image

D1 Result

D1 Error


Test Image 14

Error D1-bg D1-fg D1-all
All / All 1.39 0.00 1.37
All / Est 1.39 0.00 1.37
Noc / All 1.30 0.00 1.28
Noc / Est 1.30 0.00 1.28
This table as LaTeX

Input Image

D1 Result

D1 Error


Test Image 15

Error D1-bg D1-fg D1-all
All / All 2.82 0.09 2.57
All / Est 2.82 0.09 2.57
Noc / All 2.86 0.09 2.61
Noc / Est 2.86 0.09 2.61
This table as LaTeX

Input Image

D1 Result

D1 Error


Test Image 16

Error D1-bg D1-fg D1-all
All / All 3.45 0.46 3.01
All / Est 3.45 0.46 3.01
Noc / All 3.31 0.46 2.89
Noc / Est 3.31 0.46 2.89
This table as LaTeX

Input Image

D1 Result

D1 Error


Test Image 17

Error D1-bg D1-fg D1-all
All / All 0.85 0.34 0.80
All / Est 0.85 0.34 0.80
Noc / All 0.85 0.34 0.80
Noc / Est 0.85 0.34 0.80
This table as LaTeX

Input Image

D1 Result

D1 Error


Test Image 18

Error D1-bg D1-fg D1-all
All / All 4.49 0.38 2.54
All / Est 4.49 0.38 2.54
Noc / All 4.43 0.38 2.49
Noc / Est 4.43 0.38 2.49
This table as LaTeX

Input Image

D1 Result

D1 Error


Test Image 19

Error D1-bg D1-fg D1-all
All / All 0.72 0.82 0.73
All / Est 0.72 0.82 0.73
Noc / All 0.72 0.82 0.73
Noc / Est 0.72 0.82 0.73
This table as LaTeX

Input Image

D1 Result

D1 Error




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