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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 141150 of 343 papers

TitleStatusHype
A Universal Protocol to Benchmark Camera Calibration for Sports0
CaMuViD: Calibration-Free Multi-View Detection0
3D Object Localization Using 2D Estimates for Computer Vision Applications0
Camera Pose Estimation Using Implicit Distortion Models0
AlignDiff: Learning Physically-Grounded Camera Alignment via Diffusion0
Hybrid Focal Stereo Networks for Pattern Analysis in Homogeneous Scenes0
Camera Calibration with Pose Guidance0
Camera Calibration without Camera Access -- A Robust Validation Technique for Extended PnP Methods0
A unified approach for multi-object triangulation, tracking and camera calibration0
A Two-step Calibration Method for Unfocused Light Field Camera Based on Projection Model Analysis0
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