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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 8190 of 343 papers

TitleStatusHype
“Look Ma, no landmarks!” – Unsupervised, Model-based Dense Face AlignmentCode1
Deep Learning for Vanishing Point Detection Using an Inverse Gnomonic ProjectionCode1
Camera Distortion-aware 3D Human Pose Estimation in Video with Optimization-based Meta-LearningCode1
Multi-task Learning for Camera CalibrationCode1
EdgeCalib: Multi-Frame Weighted Edge Features for Automatic Targetless LiDAR-Camera CalibrationCode1
Learning-Based Framework for Camera Calibration with Distortion Correction and High Precision Feature DetectionCode1
Neuromorphic Synergy for Video BinarizationCode1
RGB-D-E: Event Camera Calibration for Fast 6-DOF Object TrackingCode1
Online Marker-free Extrinsic Camera Calibration using Person Keypoint DetectionsCode1
Calibration of depth cameras using denoised depth images0
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