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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 3140 of 343 papers

TitleStatusHype
Depth-Aware Multi-Grid Deep Homography Estimation with Contextual CorrelationCode1
Infrastructure-based Multi-Camera Calibration using Radial ProjectionsCode1
I see you: A Vehicle-Pedestrian Interaction Dataset from Traffic Surveillance CamerasCode1
Camera Calibration using a Collimator SystemCode1
Camera Calibration through Geometric Constraints from Rotation and Projection MatricesCode1
CalibRefine: Deep Learning-Based Online Automatic Targetless LiDAR-Camera Calibration with Iterative and Attention-Driven Post-RefinementCode1
Camera Calibration through Camera Projection LossCode1
Camera Distortion-aware 3D Human Pose Estimation in Video with Optimization-based Meta-LearningCode1
Event Camera Calibration of Per-pixel Biased Contrast ThresholdCode1
Extrinsic Camera Calibration with Semantic SegmentationCode1
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