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 201–210 of 304 papers

TitleStatusHype
Learnable Motion Coherence for Correspondence Pruning—0
Learning Correspondence Uncertainty via Differentiable Nonlinear Least Squares—0
Learning Multi-View Camera Relocalization With Graph Neural Networks—0
Learning Probabilistic Coordinate Fields for Robust Correspondences—0
Learning Robust Multi-Scale Representation for Neural Radiance Fields from Unposed Images—0
Learning Rotation-Equivariant Features for Visual Correspondence—0
Learning to Switch CNNs with Model Agnostic Meta Learning for Fine Precision Visual Servoing—0
LetsGo: Large-Scale Garage Modeling and Rendering via LiDAR-Assisted Gaussian Primitives—0
Level Set-Based Camera Pose Estimation From Multiple 2D/3D Ellipse-Ellipsoid Correspondences—0
Light3R-SfM: Towards Feed-forward Structure-from-Motion—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