Camera Calibration
80 papers with code • 0 benchmarks • 3 datasets
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.
Benchmarks
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Libraries
Use these libraries to find Camera Calibration models and implementations
Cross-View Cross-Scene Multi-View Crowd Counting Dataset
DeepSportRadar-v1
CVGL
Most implemented papers
Improvements to Target-Based 3D LiDAR to Camera Calibration
The homogeneous transformation between a LiDAR and monocular camera is required for sensor fusion tasks, such as SLAM.
SoccerNet 2022 Challenges Results
The SoccerNet 2022 challenges were the second annual video understanding challenges organized by the SoccerNet team.
LiDAR-Camera Calibration using 3D-3D Point correspondences
With the advent of autonomous vehicles, LiDAR and cameras have become an indispensable combination of sensors.
Kornia: an Open Source Differentiable Computer Vision Library for PyTorch
kornia/kornia
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This work presents Kornia -- an open source computer vision library which consists of a set of differentiable routines and modules to solve generic computer vision problems.
DeepSportradar-v1: Computer Vision Dataset for Sports Understanding with High Quality Annotations
deepsportradar/player-reidentification-challenge
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With the recent development of Deep Learning applied to Computer Vision, sport video understanding has gained a lot of attention, providing much richer information for both sport consumers and leagues.
Sports Camera Calibration via Synthetic Data
lood339/SCCvSD
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Here we propose a highly automatic method for calibrating sports cameras from a single image using synthetic data.
Leveraging blur information for plenoptic camera calibration
This paper presents a novel calibration algorithm for plenoptic cameras, especially the multi-focus configuration, where several types of micro-lenses are used, using raw images only.
Deep Learning for Vanishing Point Detection Using an Inverse Gnomonic Projection
yanconglin/vanishingpoint_houghtransform_gaussiansphere
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We present a novel approach for vanishing point detection from uncalibrated monocular images.
Why Having 10,000 Parameters in Your Camera Model is Better Than Twelve
In contrast, generic camera models allow for very accurate calibration due to their flexibility.
PlenoptiCam v1.0: A light-field imaging framework
Light-field cameras play a vital role for rich 3-D information retrieval in narrow range depth sensing applications.
