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 271–280 of 304 papers

TitleStatusHype
Computing CNN Loss and Gradients for Pose Estimation with Riemannian GeometryCode0
GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera PoseCode0
Predicting Out-of-View Feature Points for Model-Based Camera Pose Estimation—0
Generic 3D Representation via Pose Estimation and MatchingCode0
A Line-Point Unified Solution to Relative Camera Pose Estimation—0
SceneNet RGB-D: Can 5M Synthetic Images Beat Generic ImageNet Pre-Training on Indoor Segmentation?—0
Long Short-Term Memory Kalman Filters: Recurrent Neural Estimators for Pose Regularization—0
Refractive Structure-From-Motion Through a Flat Refractive Interface—0
Globally-Optimal Inlier Set Maximisation for Simultaneous Camera Pose and Feature Correspondence—0
Joint Estimation of Camera Pose, Depth, Deblurring, and Super-Resolution from a Blurred Image Sequence—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