Result details - ETH3D

Submitted anonymously.

Submission data

Full name	RobustSparseGeometryMapping
Description	A sparse geometric mapping framework that estimates camera motion and reconstructs 3D landmarks from stereo image pairs. The method employs robust outlier rejection, adaptive landmark selection, and graph-based optimization to maintain accurate localization in large-scale environments. IMU integration improves motion estimation during rapid movements and low-texture scenes.
Parameters	Maximum landmarks: 5000 Feature detection threshold: 0.02 RANSAC iterations: 1000 Keyframe insertion distance: 0.5 m Graph optimization frequency: every 20 frames IMU fusion weight: 0.40
Programming language(s)	C++, Eigen, OpenCV
Hardware	A100
Submission creation date	23 Jun, 2026
Last edited	23 Jun, 2026

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	delivery area	electro	forest	playground	terrains
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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
							1.58	15.53	8.23	14.15	16.14	14.44	5.82	9.21	2.69	0.12	0.16	0.00	0.19	0.16

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
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