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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
Enhancing Soccer Camera Calibration Through Keypoint ExploitationCode2
Deep Learning for Camera Calibration and Beyond: A SurveyCode2
Dynamic Multi-Person Mesh Recovery From Uncalibrated Multi-View CamerasCode1
AcinoSet: A 3D Pose Estimation Dataset and Baseline Models for Cheetahs in the WildCode1
E-3DGS: Gaussian Splatting with Exposure and Motion EventsCode1
Depth-Aware Multi-Grid Deep Homography Estimation with Contextual CorrelationCode1
Deep Learning for Vanishing Point Detection Using an Inverse Gnomonic ProjectionCode1
DeepSportradar-v1: Computer Vision Dataset for Sports Understanding with High Quality AnnotationsCode1
Dynamic Event Camera CalibrationCode1
EdgeCalib: Multi-Frame Weighted Edge Features for Automatic Targetless LiDAR-Camera CalibrationCode1
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