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 226–250 of 304 papers

TitleStatusHype
Learning to Switch CNNs with Model Agnostic Meta Learning for Fine Precision Visual Servoing—0
Perspective Plane Program Induction from a Single Image—0
Adversarial Transfer of Pose Estimation Regression—0
Learning Multi-View Camera Relocalization With Graph Neural Networks—0
TRPLP - Trifocal Relative Pose From Lines at Points—0
End-to-End Camera Calibration for Broadcast Videos—0
Beyond Photometric Consistency: Gradient-based Dissimilarity for Improving Visual Odometry and Stereo Matching—0
Real-Time Camera Pose Estimation for Sports Fields—0
On-line non-overlapping camera calibration net—0
Unsupervised Learning of Camera Pose with Compositional Re-estimation—0
Necessary and Sufficient Polynomial Constraints on Compatible Triplets of Essential Matrices—0
Estimating 3D Camera Pose from 2D Pedestrian Trajectories—0
Line-based Camera Pose Estimation in Point Cloud of Structured Environments—0
Privacy Preserving Image Queries for Camera Localization—0
Spatial Correspondence With Generative Adversarial Network: Learning Depth From Monocular Videos—0
Estimating the Fundamental Matrix Without Point Correspondences With Application to Transmission Imaging—0
How to improve CNN-based 6-DoF camera pose estimation—0
Large Scale Joint Semantic Re-Localisation and Scene Understanding via Globally Unique Instance Coordinate Regression—0
EPOSIT: An Absolute Pose Estimation Method for Pinhole and Fish-Eye CamerasCode0
Camera Pose Correction in SLAM Based on Bias Values of Map Points—0
Hybrid Camera Pose Estimation with Online Partitioning for SLAM—0
Pan-tilt-zoom SLAM for Sports VideosCode0
Introduction to Camera Pose Estimation with Deep Learning—0
ACNe: Attentive Context Normalization for Robust Permutation-Equivariant LearningCode0
EKFPnP: Extended Kalman Filter for Camera Pose Estimation in a Sequence of ImagesCode0
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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