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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
PuzzleBoard: A New Camera Calibration Pattern with Position EncodingCode1
Multi-View People Detection in Large Scenes via Supervised View-Wise Contribution WeightingCode1
MUC: Mixture of Uncalibrated Cameras for Robust 3D Human Body ReconstructionCode1
Neuromorphic Synergy for Video BinarizationCode1
Camera Calibration through Geometric Constraints from Rotation and Projection MatricesCode1
W-HMR: Monocular Human Mesh Recovery in World Space with Weak-Supervised CalibrationCode1
EdgeCalib: Multi-Frame Weighted Edge Features for Automatic Targetless LiDAR-Camera CalibrationCode1
SoccerNet 2023 Challenges ResultsCode1
Context-Aware 3D Object Localization from Single Calibrated Images: A Study of BasketballsCode1
SyMFM6D: Symmetry-aware Multi-directional Fusion for Multi-View 6D Object Pose EstimationCode1
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