Submitted by JUNHONG MIN.

Submission data

Full nameConfidence Aware Stereo Matching
DescriptionOur approach estimates disparities using implicitly inferred confidence levels. This capability is facilitated by our newly developed U-net transformer, which incorporates various attention mechanisms to extract global and local contexts from rectified image pairs.
Parametersfeature dimension:128
refinement iterations: 3
4-level u-net transformer
Publication titleConfidence Aware Stereo Matching for Realistic Cluttered Scenario
Publication authorsJunhong Min, Youngpil Jeon
Publication venueICIP 2024 submissions (1861)
Programming language(s)python
HardwareIntel i9-13900K, Nvidia 4090
Submission creation date5 Feb, 2024
Last edited5 Feb, 2024

High-res multi-view results



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indooroutdoorbotani.boulde.bridgedoorexhibi.lectur.living.loungeobserv.old co.statueterrac.
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Low-res many-view results



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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
two views4.111.275.285.630.314.892.8611.5211.7311.0611.804.161.636.302.220.630.000.600.130.150.07

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
MethodInfo
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