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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 181190 of 343 papers

TitleStatusHype
Astrometric Calibration and Source Characterisation of the Latest Generation Neuromorphic Event-based Cameras for Space ImagingCode0
AligNeRF: High-Fidelity Neural Radiance Fields via Alignment-Aware Training0
Enhanced Low-resolution LiDAR-Camera Calibration Via Depth Interpolation and Supervised Contrastive Learning0
Multi-Camera Calibration Free BEV Representation for 3D Object Detection0
Non-learning Stereo-aided Depth Completion under Mis-projection via Selective Stereo Matching0
Neural Implicit Surface Reconstruction from Noisy Camera Observations0
MARIO: Modular and Extensible Architecture for Computing Visual Statistics in RoboCup SPLCode0
KaliCalib: A Framework for Basketball Court Registration0
A Deep Perceptual Measure for Lens and Camera Calibration0
Multi-View Object Pose Refinement With Differentiable Renderer0
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