SOTAVerified

Visual Odometry

Visual Odometry is an important area of information fusion in which the central aim is to estimate the pose of a robot using data collected by visual sensors.

Source: Bi-objective Optimization for Robust RGB-D Visual Odometry

Papers

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Showing 1–10 of 408 papers

TitleStatusHype
DINO-VO: A Feature-based Visual Odometry Leveraging a Visual Foundation Model—0
UFM: A Simple Path towards Unified Dense Correspondence with Flow—0
ZeroVO: Visual Odometry with Minimal Assumptions—0
cuVSLAM: CUDA accelerated visual odometry and mapping—0
eStonefish-scenes: A synthetically generated dataset for underwater event-based optical flow prediction tasks—0
Structureless VIO—0
SafeNav: Safe Path Navigation using Landmark Based Localization in a GPS-denied Environment—0
Large-scale visual SLAM for in-the-wild videos—0
An Online Adaptation Method for Robust Depth Estimation and Visual Odometry in the Open WorldCode0
MonoGS++: Fast and Accurate Monocular RGB Gaussian SLAM—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CIVORelative Position Error Translation [cm]1.36—Unverified