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 161–170 of 304 papers

TitleStatusHype
EgoCOL: Egocentric Camera pose estimation for Open-world 3D object Localization @Ego4D challenge 2023Code0
Learning Probabilistic Coordinate Fields for Robust Correspondences—0
FlowCam: Training Generalizable 3D Radiance Fields without Camera Poses via Pixel-Aligned Scene Flow—0
Learning Correspondence Uncertainty via Differentiable Nonlinear Least Squares—0
Edge-aware Consistent Stereo Video Depth Estimation—0
Region contrastive camera localizationCode0
Graph-CoVis: GNN-based Multi-view Panorama Global Pose Estimation—0
Pose Constraints for Consistent Self-supervised Monocular Depth and Ego-motionCode0
Accelerating Globally Optimal Consensus Maximization in Geometric Vision—0
Event-based Camera Tracker by t NeRF—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