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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 110 of 343 papers

TitleStatusHype
Monocular One-Shot Metric-Depth Alignment for RGB-Based Robot Grasping0
Camera Calibration via Circular Patterns: A Comprehensive Framework with Measurement Uncertainty and Unbiased Projection ModelCode3
ZeroVO: Visual Odometry with Minimal Assumptions0
BEVCALIB: LiDAR-Camera Calibration via Geometry-Guided Bird's-Eye View Representations0
Multi-Spectral Gaussian Splatting with Neural Color Representation0
Bi-Manual Joint Camera Calibration and Scene Representation0
RC-AutoCalib: An End-to-End Radar-Camera Automatic Calibration NetworkCode0
VolE: A Point-cloud Framework for Food 3D Reconstruction and Volume Estimation0
ClearLines - Camera Calibration from Straight Lines0
Zebrafish Counting Using Event Stream Data0
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