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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 171180 of 343 papers

TitleStatusHype
Camera Pose Estimation Using Implicit Distortion Models0
A Unified Model for Line Projections in Catadioptric Cameras With Rotationally Symmetric MirrorsCode0
Video-Based Reconstruction of the Trajectories Performed by Skiers0
Long-Range Thermal 3D Perception in Low Contrast Environments0
Self-Supervised Camera Self-Calibration from Video0
Camera Distortion-aware 3D Human Pose Estimation in Video with Optimization-based Meta-LearningCode1
PlantStereo: A Stereo Matching Benchmark for Plant Surface Dense ReconstructionCode1
Rethinking Generic Camera Models for Deep Single Image Camera Calibration to Recover Rotation and Fisheye Distortion0
Leveraging blur information for plenoptic camera calibrationCode1
Learning Eye-in-Hand Camera Calibration from a Single Image0
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