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 2130 of 343 papers

TitleStatusHype
Boost 3D Reconstruction using Diffusion-based Monocular Camera CalibrationCode2
Calib-Anything: Zero-training LiDAR-Camera Extrinsic Calibration Method Using Segment AnythingCode2
Dynamic Multi-Person Mesh Recovery From Uncalibrated Multi-View CamerasCode1
AcinoSet: A 3D Pose Estimation Dataset and Baseline Models for Cheetahs in the WildCode1
E-3DGS: Gaussian Splatting with Exposure and Motion EventsCode1
Camera Calibration through Camera Projection LossCode1
CalibRefine: Deep Learning-Based Online Automatic Targetless LiDAR-Camera Calibration with Iterative and Attention-Driven Post-RefinementCode1
Camera Calibration through Geometric Constraints from Rotation and Projection MatricesCode1
Camera Distortion-aware 3D Human Pose Estimation in Video with Optimization-based Meta-LearningCode1
Camera Calibration using a Collimator SystemCode1
Show:102550
← PrevPage 3 of 35Next →

No leaderboard results yet.