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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 251260 of 343 papers

TitleStatusHype
Unsupervised Vanishing Point Detection and Camera Calibration From a Single Manhattan Image With Radial Distortion0
UprightNet: Geometry-Aware Camera Orientation Estimation from Single Images0
Using a single RGB frame for real time 3D hand pose estimation in the wild0
Validation & Exploration of Multimodal Deep-Learning Camera-Lidar Calibration models0
VaPiD: A Rapid Vanishing Point Detector via Learned Optimizers0
Variation of Camera Parameters due to Common Physical Changes in Focal Length and Camera Pose0
Video-Based Reconstruction of the Trajectories Performed by Skiers0
Vision-based system identification and 3D keypoint discovery using dynamics constraints0
Visualizing and Alleviating the Effect of Radial Distortion on Camera Calibration Using Principal Lines0
VolE: A Point-cloud Framework for Food 3D Reconstruction and Volume Estimation0
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