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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 276–300 of 408 papers

TitleStatusHype
Multi-Spectral Visual Odometry without Explicit Stereo Matching—0
Sequential Adversarial Learning for Self-Supervised Deep Visual Odometry—0
Some Aspects of Geometric Computer Vision for Analysing Dynamical Scenes focusing Automotive Applications—0
DynaNet: Neural Kalman Dynamical Model for Motion Estimation and Prediction—0
Enhancing self-supervised monocular depth estimation with traditional visual odometry—0
Local Supports Global: Deep Camera Relocalization with Sequence Enhancement—0
Unsupervised Learning of Depth and Deep Representation for Visual Odometry from Monocular Videos in a Metric Space—0
Distilling Knowledge From a Deep Pose Regressor Network—0
Robust Real-time RGB-D Visual Odometry in Dynamic Environments via Rigid Motion Model—0
Scene Motion Decomposition for Learnable Visual Odometry—0
Stereo relative pose from line and point feature tripletsCode0
SGANVO: Unsupervised Deep Visual Odometry and Depth Estimation with Stacked Generative Adversarial Networks—0
PoseConvGRU: A Monocular Approach for Visual Ego-motion Estimation by Learning—0
Edge-Direct Visual OdometryCode0
Recurrent Neural Network for (Un-)Supervised Learning of Monocular Video Visual Odometry and Depth—0
Extending Monocular Visual Odometry to Stereo Camera Systems by Scale OptimizationCode0
Robust Dense Mapping for Large-Scale Dynamic Environments—0
Learning by Inertia: Self-supervised Monocular Visual Odometry for Road Vehicles—0
Recurrent Neural Network for (Un-)supervised Learning of Monocular VideoVisual Odometry and DepthCode0
Continuous Direct Sparse Visual Odometry from RGB-D ImagesCode0
MAVNet: an Effective Semantic Segmentation Micro-Network for MAV-based TasksCode0
Beyond Tracking: Selecting Memory and Refining Poses for Deep Visual Odometry—0
Semantic Nearest Neighbor Fields Monocular Edge Visual-Odometry—0
Probabilistic Regression of Rotations using Quaternion Averaging and a Deep Multi-Headed Network—0
Learning Monocular Visual Odometry through Geometry-Aware Curriculum Learning—0
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Benchmark Results

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