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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 301310 of 343 papers

TitleStatusHype
Single View Physical Distance Estimation using Human Pose0
Smile Like You Mean It: Driving Animatronic Robotic Face with Learned Models0
Soccer line mark segmentation and classification with stochastic watershed transform0
Spatiotemporal Multi-Camera Calibration using Freely Moving People0
Panoramic Depth Estimation via Supervised and Unsupervised Learning in Indoor ScenesCode0
Sports Camera Calibration via Synthetic DataCode0
NeurVPS: Neural Vanishing Point Scanning via Conic ConvolutionCode0
Photometric Bundle Adjustment for Dense Multi-View 3D ModelingCode0
MVOR: A Multi-view RGB-D Operating Room Dataset for 2D and 3D Human Pose EstimationCode0
Multi-Channel Auto-Calibration for the Atmospheric Imaging Assembly using Machine LearningCode0
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