SOTAVerified

Camera Pose Estimation

Camera pose estimation is a crucial task in computer vision and robotics that involves determining the position and orientation (pose) of a camera relative to a given reference frame. This task is essential for various applications, such as augmented reality, 3D reconstruction, SLAM, and autonomous navigation.

Papers

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Showing 211–220 of 304 papers

TitleStatusHype
LiM-Loc: Visual Localization with Dense and Accurate 3D Reference Maps Directly Corresponding 2D Keypoints to 3D LiDAR Point Clouds—0
Line-based Camera Pose Estimation in Point Cloud of Structured Environments—0
Long Short-Term Memory Kalman Filters:Recurrent Neural Estimators for Pose Regularization—0
Long Short-Term Memory Kalman Filters: Recurrent Neural Estimators for Pose Regularization—0
Long-term 3D Localization and Pose from Semantic Labellings—0
MobileARLoc: On-device Robust Absolute Localisation for Pervasive Markerless Mobile AR—0
Mono3R: Exploiting Monocular Cues for Geometric 3D Reconstruction—0
Multi-Person 3D Pose Estimation from Multi-View Uncalibrated Depth Cameras—0
MonoNeRF: Learning Generalizable NeRFs from Monocular Videos without Camera Pose—0
Large Scale Joint Semantic Re-Localisation and Scene Understanding via Globally Unique Instance Coordinate Regression—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Monodepth2Average Translational Error et[%]43.21—Unverified
2SfMLearnerAverage Translational Error et[%]29.78—Unverified
3GeoNetAverage Translational Error et[%]26.31—Unverified
4SC-DepthAverage Translational Error et[%]12.2—Unverified
5DeepMatchVOAverage Translational Error et[%]11.05—Unverified
6SCIPaDAverage Translational Error et[%]8.63—Unverified
7Manydepth2Average Translational Error et[%]7.15—Unverified