Result details - ETH3D

Submitted anonymously.

Submission data

Full name	AdaptiveHybridVisualOdometry
Description	A hybrid visual odometry system that combines direct image alignment with sparse feature tracking. The method dynamically switches between tracking modes based on scene texture and motion characteristics. Stereo depth and IMU measurements are fused through an adaptive Kalman filter, while loop closure detection reduces long-term drift and improves global consistency.
Parameters	Maximum tracked features: 3000 Direct alignment pyramid levels: 4 Feature re-detection interval: 10 frames IMU update rate: 200 Hz Loop closure similarity threshold: 0.85 Pose optimization iterations: 50
Programming language(s)	C++, Python, CUDA
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
							0.36	0.82	0.61	0.46	0.89	0.71	0.49	0.88	0.80	0.16	0.15	0.14	0.13	0.22

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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