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

Showing 101110 of 408 papers

TitleStatusHype
Direct Sparse OdometryCode0
Beyond Photometric Loss for Self-Supervised Ego-Motion EstimationCode0
Loss it right: Euclidean and Riemannian Metrics in Learning-based Visual OdometryCode0
MAVNet: an Effective Semantic Segmentation Micro-Network for MAV-based TasksCode0
Learning Depth from Monocular Videos using Direct MethodsCode0
Leveraging Consistent Spatio-Temporal Correspondence for Robust Visual OdometryCode0
eCARLA-scenes: A synthetically generated dataset for event-based optical flow predictionCode0
Edge-Direct Visual OdometryCode0
Mind the Gap! A Study on the Transferability of Virtual vs Physical-world Testing of Autonomous Driving SystemsCode0
DeepVO: Towards End-to-End Visual Odometry with Deep Recurrent Convolutional Neural NetworksCode0
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Benchmark Results

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