SOTAVerified

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
Deep-BrownConrady: Prediction of Camera Calibration and Distortion Parameters Using Deep Learning and Synthetic Data0
AnyMap: Learning a General Camera Model for Structure-from-Motion with Unknown Distortion in Dynamic Scenes0
CaMuViD: Calibration-Free Multi-View Detection0
LUCES-MV: A Multi-View Dataset for Near-Field Point Light Source Photometric Stereo0
Data Fusion of Semantic and Depth Information in the Context of Object Detection0
MCBLT: Multi-Camera Multi-Object 3D Tracking in Long Videos0
RoMo: Robust Motion Segmentation Improves Structure from Motion0
PreF3R: Pose-Free Feed-Forward 3D Gaussian Splatting from Variable-length Image Sequence0
Rotating-star Pattern for Camera Calibration0
Lane Detection System for Driver Assistance in Vehicles0
Show:102550
← PrevPage 12 of 35Next →

No leaderboard results yet.