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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 131140 of 343 papers

TitleStatusHype
From a Bird's Eye View to See: Joint Camera and Subject Registration without the Camera CalibrationCode1
Learning Markerless Robot-Depth Camera Calibration and End-Effector Pose Estimation0
Perspective Fields for Single Image Camera CalibrationCode2
Single image calibration using knowledge distillation approaches0
Motion estimation for fisheye video sequences combining perspective projection with camera calibration information0
Multi-task Learning for Camera CalibrationCode1
PLIKS: A Pseudo-Linear Inverse Kinematic Solver for 3D Human Body EstimationCode0
Astrometric Calibration and Source Characterisation of the Latest Generation Neuromorphic Event-based Cameras for Space ImagingCode0
AligNeRF: High-Fidelity Neural Radiance Fields via Alignment-Aware Training0
I see you: A Vehicle-Pedestrian Interaction Dataset from Traffic Surveillance CamerasCode1
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