Spring Dataset and Benchmark Logo

Spring: L. Mehl, J. Schmalfuss, A. Jahedi, Y. Nalivayko, A. Bruhn — University of Stuttgart

RobustSpring: V. Oei, J. Schmalfuss, L. Mehl, M. Bartsch, S. Agnihotri, M. Keuper, A. Bulling, A. Bruhn — University of Stuttgart, University of Mannheim, MPI for Informatics

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GANet

Nov. 1, 2022, 2 p.m.  —  Public

đŸ’¡ submitted by spring team | F. Zhang, V. Prisacariu, R. Yang, and P. HS Torr. "GA-Net: Guided Aggregation Net for End-to-end Stereo Matching." In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019.

Code: https://github.com/feihuzhang/GANet

Stereo

1px
total
1px
low-detail
1px
high-detail
1px
matched
1px
unmatched
1px
not sky
1px
sky
1px
s0-10
1px
s10-40
1px
s40+
23.225 22.912 42.064 20.976 67.878 18.418 96.274 24.286 16.427 41.499
 
Abs
total
Abs
low-detail
Abs
high-detail
Abs
matched
Abs
unmatched
Abs
not sky
Abs
sky
Abs
s0-10
Abs
s10-40
Abs
s40+
4.594 4.568 6.154 3.472 26.859 2.588 35.081 7.253 2.009 7.265
 
D1
total
D1
low-detail
D1
high-detail
D1
matched
D1
unmatched
D1
not sky
D1
sky
D1
s0-10
D1
s10-40
D1
s40+
10.393 10.313 15.229 8.483 48.317 7.769 50.272 12.022 6.854 17.867

Robustness Evaluation (Overall)

1px
total
Abs
total
D1
total
45.260 12.110 17.930

Robustness per Corruption

Robustness Evaluation (Per-Corruption)

Corruption 1px Abs D1
Brightness 10.740 2.110 3.390
Contrast 23.140 3.940 6.740
Saturate 13.530 2.700 3.860
Defocus Blur 12.340 2.460 3.160
Gaussian Blur 13.760 2.690 3.450
Glass Blur 19.420 2.610 3.150
Motion Blur 13.120 2.310 3.610
Zoom Blur 59.890 7.290 11.210
Gaussian Noise 85.780 33.350 45.020
Impulse Noise 85.000 38.940 50.450
Speckle Noise 83.700 29.650 41.900
Shot Noise 81.490 28.200 39.890
Pixelate 59.610 3.700 4.070
JPEG Compression 59.520 6.760 10.100
Elastic Transform 76.470 4.850 5.050
Fog 20.550 9.680 9.750
Frost 47.400 11.200 24.310
Rain 59.220 26.500 42.340
Snow 45.880 17.240 33.300
Spatter 34.580 6.040 13.860
reference frame
Reference Frame
color visualization of disparity 1
Disparity 1 visualization
grayscale visualization of disparity 1 error
Disparity 1 error
reference frame
Reference Frame
color visualization of disparity 1
Disparity 1 visualization
grayscale visualization of disparity 1 error
Disparity 1 error
reference frame
Reference Frame
color visualization of disparity 1
Disparity 1 visualization
grayscale visualization of disparity 1 error
Disparity 1 error
reference frame
Reference Frame
color visualization of disparity 1
Disparity 1 visualization
grayscale visualization of disparity 1 error
Disparity 1 error
reference frame
Reference Frame
color visualization of disparity 1
Disparity 1 visualization
grayscale visualization of disparity 1 error
Disparity 1 error
reference frame
Reference Frame
color visualization of disparity 1
Disparity 1 visualization
grayscale visualization of disparity 1 error
Disparity 1 error
reference frame
Reference Frame
color visualization of disparity 1
Disparity 1 visualization
grayscale visualization of disparity 1 error
Disparity 1 error
reference frame
Reference Frame
color visualization of disparity 1
Disparity 1 visualization
grayscale visualization of disparity 1 error
Disparity 1 error
reference frame
Reference Frame
color visualization of disparity 1
Disparity 1 visualization
grayscale visualization of disparity 1 error
Disparity 1 error
reference frame
Reference Frame
color visualization of disparity 1
Disparity 1 visualization
grayscale visualization of disparity 1 error
Disparity 1 error
Error visualization color code
blue to white to red error visualization color code