Result details - ETH3D

Submitted by JUNHONG MIN.

Submission data

Full name	Confidence Aware Stereo Matching
Description	Our 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.
Parameters	feature dimension:128 refinement iterations: 3 4-level u-net transformer
Publication title	Confidence Aware Stereo Matching for Realistic Cluttered Scenario
Publication authors	Junhong Min, Youngpil Jeon
Publication venue	ICIP 2024 submissions (1861)
Programming language(s)	python
Hardware	Intel i9-13900K, Nvidia 4090
Submission creation date	5 Feb, 2024
Last edited	5 Feb, 2024

High-res multi-view results

Info	all	high-res multi-view	indoor	outdoor	botani.	boulde.	bridge	door	exhibi.	lectur.	living.	lounge	observ.	old co.	statue	terrac.
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Low-res many-view results

Info	all	low-res many-view	indoor	outdoor	lakeside	sand box	storage room	storage room 2	tunnel
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Low-res two-view results

Info	all	lakes. 1l	lakes. 1s	sand box 1l	sand box 1s	stora. room 1l	stora. room 1s	stora. room 2l	stora. room 2s	stora. room 2 1l	stora. room 2 1s	stora. room 2 2l	stora. room 2 2s	stora. room 3l	stora. room 3s	tunnel 1l	tunnel 1s	tunnel 2l	tunnel 2s	tunnel 3l	tunnel 3s
	0.98	0.32	1.62	0.65	0.07	2.11	0.14	3.50	4.03	3.77	1.41	0.31	0.29	0.80	0.57	0.01	0.00	0.00	0.00	0.04	0.01

SLAM results

		all	boxes	boxes dark	buddha	cables 4	cables 5	desk 1	desk 2	desk changing 2	desk dark 1	desk dark 2	desk global light changes	desk ir light	dino	drone	foreground occlusion	helmet	kidnap 2	lamp	large loop 2	large loop 3	large non loop	motion 2	motion 3	motion 4	planar 1	reflective 2	scale change	table 1	table 2	table 5	table 6	table global light changes	table local light changes	table scene	trashbin
	Method	Info
No results yet.