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 3140 of 343 papers

TitleStatusHype
EdgeCalib: Multi-Frame Weighted Edge Features for Automatic Targetless LiDAR-Camera CalibrationCode1
From a Bird's Eye View to See: Joint Camera and Subject Registration without the Camera CalibrationCode1
I see you: A Vehicle-Pedestrian Interaction Dataset from Traffic Surveillance CamerasCode1
Depth-Aware Multi-Grid Deep Homography Estimation with Contextual CorrelationCode1
Deep Learning for Vanishing Point Detection Using an Inverse Gnomonic ProjectionCode1
DeepSportradar-v1: Computer Vision Dataset for Sports Understanding with High Quality AnnotationsCode1
Dynamic Event Camera CalibrationCode1
Camera Distortion-aware 3D Human Pose Estimation in Video with Optimization-based Meta-LearningCode1
Context-Aware 3D Object Localization from Single Calibrated Images: A Study of BasketballsCode1
Camera Calibration through Geometric Constraints from Rotation and Projection MatricesCode1
Show:102550
← PrevPage 4 of 35Next →

No leaderboard results yet.