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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 111120 of 343 papers

TitleStatusHype
MVOR: A Multi-view RGB-D Operating Room Dataset for 2D and 3D Human Pose EstimationCode0
ChESS - Quick and Robust Detection of Chess-board FeaturesCode0
Multi-Channel Auto-Calibration for the Atmospheric Imaging Assembly using Machine LearningCode0
NeurVPS: Neural Vanishing Point Scanning via Conic ConvolutionCode0
CasCalib: Cascaded Calibration for Motion Capture from Sparse Unsynchronized CamerasCode0
MARIO: Modular and Extensible Architecture for Computing Visual Statistics in RoboCup SPLCode0
A Unified Model for Line Projections in Catadioptric Cameras With Rotationally Symmetric MirrorsCode0
Lens Distortion Rectification using Triangulation based InterpolationCode0
A Two-point Method for PTZ Camera Calibration in SportsCode0
LiDAR-Camera Calibration using 3D-3D Point correspondencesCode0
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