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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 281290 of 343 papers

TitleStatusHype
A New Technique of Camera Calibration: A Geometric Approach Based on Principal Lines0
A Linear Generalized Camera Calibration From Three Intersecting Reference Planes0
AligNeRF: High-Fidelity Neural Radiance Fields via Alignment-Aware Training0
AlignDiff: Learning Physically-Grounded Camera Alignment via Diffusion0
A Two-step Calibration Method for Unfocused Light Field Camera Based on Projection Model Analysis0
Wide-Baseline Multi-Camera Calibration using Person Re-Identification0
Spatiotemporal Multi-Camera Calibration using Freely Moving People0
Spatio-Temporal Outdoor Lighting Aggregation on Image Sequences using Transformer Networks0
A fast horizon detector and a new annotated dataset for maritime video processing0
Zebrafish Counting Using Event Stream Data0
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