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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 161170 of 343 papers

TitleStatusHype
Pose correction scheme for camera-scanning Fourier ptychography based on camera calibration and homography transform0
Open-VICO: An Open-Source Gazebo Toolkit for Vision-based Skeleton Tracking in Human-Robot Collaboration0
An Interactive Image-based Modeling System0
CenterLoc3D: Monocular 3D Vehicle Localization Network for Roadside Surveillance Cameras0
Creating Realistic Ground Truth Data for the Evaluation of Calibration Methods for Plenoptic and Conventional CamerasCode0
Comprehensive Analysis of the Object Detection Pipeline on UAVsCode0
TEScalib: Targetless Extrinsic Self-Calibration of LiDAR and Stereo Camera for Automated Driving Vehicles with Uncertainty Analysis0
Spatio-Temporal Outdoor Lighting Aggregation on Image Sequences using Transformer Networks0
Learning-Based Framework for Camera Calibration with Distortion Correction and High Precision Feature DetectionCode1
MC-Calib: A generic and robust calibration toolbox for multi-camera systemsCode2
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