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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 4150 of 343 papers

TitleStatusHype
Dynamic Multi-Person Mesh Recovery From Uncalibrated Multi-View CamerasCode1
CTRL-C: Camera calibration TRansformer with Line-ClassificationCode1
Deep Learning for Vanishing Point Detection Using an Inverse Gnomonic ProjectionCode1
E-3DGS: Gaussian Splatting with Exposure and Motion EventsCode1
Camera Distortion-aware 3D Human Pose Estimation in Video with Optimization-based Meta-LearningCode1
Event Camera Calibration of Per-pixel Biased Contrast ThresholdCode1
Context-Aware 3D Object Localization from Single Calibrated Images: A Study of BasketballsCode1
BabelCalib: A Universal Approach to Calibrating Central CamerasCode1
Infrastructure-based Multi-Camera Calibration using Radial ProjectionsCode1
DeepSportradar-v1: Computer Vision Dataset for Sports Understanding with High Quality AnnotationsCode1
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