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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 251260 of 343 papers

TitleStatusHype
A Two-step Calibration Method for Unfocused Light Field Camera Based on Projection Model Analysis0
Perspective-consistent multifocus multiview 3D reconstruction of small objects0
Why Having 10,000 Parameters in Your Camera Model is Better Than TwelveCode1
Probabilistic Inference for Camera Calibration in Light Microscopy under Circular MotionCode0
NeurVPS: Neural Vanishing Point Scanning via Conic ConvolutionCode0
Improvements to Target-Based 3D LiDAR to Camera CalibrationCode1
Kornia: an Open Source Differentiable Computer Vision Library for PyTorchCode1
TagSLAM: Robust SLAM with Fiducial Markers0
PST900: RGB-Thermal Calibration, Dataset and Segmentation NetworkCode0
UprightNet: Geometry-Aware Camera Orientation Estimation from Single Images0
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