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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 261270 of 343 papers

TitleStatusHype
RoGUENeRF: A Robust Geometry-Consistent Universal Enhancer for NeRF0
Rolling Shutter Camera Calibration0
RoMo: Robust Motion Segmentation Improves Structure from Motion0
SAMA-VTOL: A new unmanned aircraft system for remotely sensed data collection0
Self-Calibration Supported Robust Projective Structure-from-Motion0
Self-Supervised Camera Self-Calibration from Video0
Self-Supervised Object-in-Gripper Segmentation from Robotic Motions0
Self-Supervised Online Camera Calibration for Automated Driving and Parking Applications0
SemCal: Semantic LiDAR-Camera Calibration using Neural MutualInformation Estimator0
Shape from Silhouette Probability Maps: Reconstruction of Thin Objects in the Presence of Silhouette Extraction and Calibration Error0
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