Submitted by Nicolas Jourdan.

Submission data

Full nameGANet reference submission for robust vision challenge
DescriptionGANet reference submission as baseline for the
stereo benchmark of the robust vision challenge
All method credits go to the original author
(Zhang et al.)

We are formulating traditional geometric and
optimization of stereo into deep neural networks.
ParametersTrained on Middleburry, KITTI, ETH3D from the KITTI
checkpoint made available in the GANet repository
on Github by the original authors.
Frequency of sampling was adapted to the dataset
size. Test images scaled to next multiple of 48.
Publication titleGA-Net: Guided Aggregation Net for End- to-end Stereo Matching
Publication authorsZhang, Feihu and Prisacariu, Victor and Yang, Ruigang and Torr, Philip HS
Publication venueCVPR 2019
Publication URL
Programming language(s)Python (PyTorch), CUDA
HardwareIntel Core I9-9920X, Nvidia Quadro RTX 8000
Source code or download URL
Submission creation date17 Jul, 2020
Last edited17 Jul, 2020

High-res multi-view results

multi-view co.statueterrac.
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Low-res many-view results

indooroutdoorlakesidesand boxstorage roomstorage room 2tunnel
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Low-res two-view results

Infoalllakes. 1llakes. 1ssand box 1lsand box 1sstora. room 1lstora. room 1sstora. room 2lstora. room 2sstora. room 2 1lstora. room 2 1sstora. room 2 2lstora. room 2 2sstora. room 3lstora. room 3stunnel 1ltunnel 1stunnel 2ltunnel 2stunnel 3ltunnel 3s
permissivetwo views6.562.897.583.410.4012.969.5815.0917.2510.3310.6212.278.1612.214.530.410.

SLAM results

allboxesboxes darkbuddhacables 4cables 5desk 1desk 2desk changing 2desk dark 1desk dark 2desk global light changesdesk ir lightdinodroneforeground occlusionhelmetkidnap 2lamplarge loop 2large loop 3large non loopmotion 2motion 3motion 4planar 1reflective 2scale changetable 1table 2table 5table 6table global light changestable local light changestable scenetrashbin
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