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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 91100 of 343 papers

TitleStatusHype
Multi-camera calibration with pattern rigs, including for non-overlapping cameras: CALICOCode0
Probabilistic Inference for Camera Calibration in Light Microscopy under Circular MotionCode0
CalibNet: Geometrically Supervised Extrinsic Calibration using 3D Spatial Transformer NetworksCode0
PST900: RGB-Thermal Calibration, Dataset and Segmentation NetworkCode0
calibDB: enabling web based computer vision through on-the-fly camera calibrationCode0
Photometric Bundle Adjustment for Dense Multi-View 3D ModelingCode0
Blind Augmentation: Calibration-free Camera Distortion Model Estimation for Real-time Mixed-reality ConsistencyCode0
Comprehensive Data Set for Automatic Single Camera Visual Speed MeasurementCode0
MVOR: A Multi-view RGB-D Operating Room Dataset for 2D and 3D Human Pose EstimationCode0
NeurVPS: Neural Vanishing Point Scanning via Conic ConvolutionCode0
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