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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 7180 of 343 papers

TitleStatusHype
Instant Multi-View Head Capture through Learnable RegistrationCode1
EdgeCalib: Multi-Frame Weighted Edge Features for Automatic Targetless LiDAR-Camera CalibrationCode1
MVP-Human Dataset for 3D Human Avatar Reconstruction from Unconstrained FramesCode1
Depth-Aware Multi-Grid Deep Homography Estimation with Contextual CorrelationCode1
3D Surface Reconstruction From Multi-Date Satellite ImagesCode1
Camera Distortion-aware 3D Human Pose Estimation in Video with Optimization-based Meta-LearningCode1
Camera Calibration through Camera Projection LossCode1
Camera Calibration through Geometric Constraints from Rotation and Projection MatricesCode1
Neural Geometric Parser for Single Image Camera CalibrationCode1
Online Marker-free Extrinsic Camera Calibration using Person Keypoint DetectionsCode1
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