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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 5160 of 343 papers

TitleStatusHype
“Look Ma, no landmarks!” – Unsupervised, Model-based Dense Face AlignmentCode1
Instant Multi-View Head Capture through Learnable RegistrationCode1
DeepSportradar-v1: Computer Vision Dataset for Sports Understanding with High Quality AnnotationsCode1
BroadTrack: Broadcast Camera Tracking for SoccerCode1
Deep Learning for Vanishing Point Detection Using an Inverse Gnomonic ProjectionCode1
Depth-Aware Multi-Grid Deep Homography Estimation with Contextual CorrelationCode1
CTRL-C: Camera calibration TRansformer with Line-ClassificationCode1
Context-Aware 3D Object Localization from Single Calibrated Images: A Study of BasketballsCode1
A Reliable Online Method for Joint Estimation of Focal Length and Camera RotationCode1
Camera Calibration using a Collimator SystemCode1
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