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 321330 of 343 papers

TitleStatusHype
PST900: RGB-Thermal Calibration, Dataset and Segmentation NetworkCode0
Motor Focus: Fast Ego-Motion Prediction for Assistive Visual NavigationCode0
MARIO: Modular and Extensible Architecture for Computing Visual Statistics in RoboCup SPLCode0
Blind Augmentation: Calibration-free Camera Distortion Model Estimation for Real-time Mixed-reality ConsistencyCode0
Calibration Wizard: A Guidance System for Camera Calibration Based on Modelling Geometric and Corner UncertaintyCode0
RC-AutoCalib: An End-to-End Radar-Camera Automatic Calibration NetworkCode0
High-Quality Depth From Uncalibrated Small Motion ClipCode0
Targetless Rotational Auto-Calibration of Radar and Camera for Intelligent Transportation SystemsCode0
Multi-camera calibration with pattern rigs, including for non-overlapping cameras: CALICOCode0
Fast Feature Extraction with CNNs with Pooling LayersCode0
Show:102550
← PrevPage 33 of 35Next →

No leaderboard results yet.