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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
EdgeCalib: Multi-Frame Weighted Edge Features for Automatic Targetless LiDAR-Camera CalibrationCode1
Event Camera Calibration of Per-pixel Biased Contrast ThresholdCode1
Camera Distortion-aware 3D Human Pose Estimation in Video with Optimization-based Meta-LearningCode1
Kornia: an Open Source Differentiable Computer Vision Library for PyTorchCode1
Camera Calibration using a Collimator SystemCode1
I see you: A Vehicle-Pedestrian Interaction Dataset from Traffic Surveillance CamerasCode1
L2E: Lasers to Events for 6-DoF Extrinsic Calibration of Lidars and Event CamerasCode1
From a Bird's Eye View to See: Joint Camera and Subject Registration without the Camera CalibrationCode1
A Reliable Online Method for Joint Estimation of Focal Length and Camera RotationCode1
CalibRefine: Deep Learning-Based Online Automatic Targetless LiDAR-Camera Calibration with Iterative and Attention-Driven Post-RefinementCode1
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