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 221–230 of 304 papers

TitleStatusHype
Event-based Camera Tracker by t NeRF—0
FAR: Flexible, Accurate and Robust 6DoF Relative Camera Pose Estimation—0
FAR: Flexible Accurate and Robust 6DoF Relative Camera Pose Estimation—0
Feature-Level Collaboration: Joint Unsupervised Learning of Optical Flow, Stereo Depth and Camera Motion—0
Five Shades of Grey for Fast and Reliable Camera Pose Estimation—0
FLARE: Feed-forward Geometry, Appearance and Camera Estimation from Uncalibrated Sparse Views—0
FlowCam: Training Generalizable 3D Radiance Fields without Camera Poses via Pixel-Aligned Scene Flow—0
Fusing the Old with the New: Learning Relative Camera Pose with Geometry-Guided Uncertainty—0
GaussianCAD: Robust Self-Supervised CAD Reconstruction from Three Orthographic Views Using 3D Gaussian Splatting—0
GCRayDiffusion: Pose-Free Surface Reconstruction via Geometric Consistent Ray Diffusion—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