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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
Camera Distortion-aware 3D Human Pose Estimation in Video with Optimization-based Meta-LearningCode1
How to Calibrate Your Event CameraCode1
Improvements to Target-Based 3D LiDAR to Camera CalibrationCode1
L2E: Lasers to Events for 6-DoF Extrinsic Calibration of Lidars and Event CamerasCode1
Leveraging blur information for plenoptic camera calibrationCode1
Context-Aware 3D Object Localization from Single Calibrated Images: A Study of BasketballsCode1
Extrinsic Camera Calibration with Semantic SegmentationCode1
CalibRefine: Deep Learning-Based Online Automatic Targetless LiDAR-Camera Calibration with Iterative and Attention-Driven Post-RefinementCode1
Deep Learning for Vanishing Point Detection Using an Inverse Gnomonic ProjectionCode1
From a Bird's Eye View to See: Joint Camera and Subject Registration without the Camera CalibrationCode1
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