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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 2130 of 343 papers

TitleStatusHype
DiffCalib: Reformulating Monocular Camera Calibration as Diffusion-Based Dense Incident Map GenerationCode2
Calib-Anything: Zero-training LiDAR-Camera Extrinsic Calibration Method Using Segment AnythingCode2
Dynamic Multi-Person Mesh Recovery From Uncalibrated Multi-View CamerasCode1
Camera Distortion-aware 3D Human Pose Estimation in Video with Optimization-based Meta-LearningCode1
E-3DGS: Gaussian Splatting with Exposure and Motion EventsCode1
Camera Calibration through Geometric Constraints from Rotation and Projection MatricesCode1
AcinoSet: A 3D Pose Estimation Dataset and Baseline Models for Cheetahs in the WildCode1
Camera Calibration through Camera Projection LossCode1
Dynamic Event Camera CalibrationCode1
Camera Calibration using a Collimator SystemCode1
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