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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 8190 of 343 papers

TitleStatusHype
Extrinsic Camera Calibration with Semantic SegmentationCode1
From a Bird's Eye View to See: Joint Camera and Subject Registration without the Camera CalibrationCode1
Camera Distortion-aware 3D Human Pose Estimation in Video with Optimization-based Meta-LearningCode1
Improvements to Target-Based 3D LiDAR to Camera CalibrationCode1
Tame a Wild Camera: In-the-Wild Monocular Camera CalibrationCode1
SoccerNet 2023 Challenges ResultsCode1
Instant Multi-View Head Capture through Learnable RegistrationCode1
I see you: A Vehicle-Pedestrian Interaction Dataset from Traffic Surveillance CamerasCode1
Kornia: an Open Source Differentiable Computer Vision Library for PyTorchCode1
Multi-camera calibration with pattern rigs, including for non-overlapping cameras: CALICOCode0
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