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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
SoccerTrack: A Dataset and Tracking Algorithm for Soccer With Fish-Eye and Drone VideosCode2
MC-Calib: A generic and robust calibration toolbox for multi-camera systemsCode2
SoccerNet-v3D: Leveraging Sports Broadcast Replays for 3D Scene UnderstandingCode1
Robust LiDAR-Camera Calibration with 2D Gaussian SplattingCode1
CalibRefine: Deep Learning-Based Online Automatic Targetless LiDAR-Camera Calibration with Iterative and Attention-Driven Post-RefinementCode1
PTZ-Calib: Robust Pan-Tilt-Zoom Camera CalibrationCode1
BroadTrack: Broadcast Camera Tracking for SoccerCode1
E-3DGS: Gaussian Splatting with Exposure and Motion EventsCode1
Triplet: Triangle Patchlet for Mesh-Based Inverse Rendering and Scene Parameters ApproximationCode1
PuzzleBoard: A New Camera Calibration Pattern with Position EncodingCode1
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