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Camera Calibration

Camera calibration involves estimating camera parameters(including camera intrinsics and extrinsics) to infer geometric features from captured sequences, which is crucial for computer vision and robotics. Driven by different architectures of the neural network, the researchers have developed two main paradigms for learning-based camera calibration and its applications. One is Regression-based Calibration,Reconstruction-based Calibration is another.

Papers

Showing 2130 of 343 papers

TitleStatusHype
High-precision visual navigation device calibration method based on collimator0
CalibRefine: Deep Learning-Based Online Automatic Targetless LiDAR-Camera Calibration with Iterative and Attention-Driven Post-RefinementCode1
Spatiotemporal Multi-Camera Calibration using Freely Moving People0
Automated intrinsic/extrinsic PTZ camera calibration using mobile LiDAR data0
CoL3D: Collaborative Learning of Single-view Depth and Camera Intrinsics for Metric 3D Shape Recovery0
PTZ-Calib: Robust Pan-Tilt-Zoom Camera CalibrationCode1
What Really Matters for Learning-based LiDAR-Camera Calibration0
Automatic Calibration of a Multi-Camera System with Limited Overlapping Fields of View for 3D Surgical Scene Reconstruction0
Deep-BrownConrady: Prediction of Camera Calibration and Distortion Parameters Using Deep Learning and Synthetic Data0
AnyMap: Learning a General Camera Model for Structure-from-Motion with Unknown Distortion in Dynamic Scenes0
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