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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 110 of 343 papers

TitleStatusHype
3D Gaussian Splatting for Real-Time Radiance Field RenderingCode6
DUSt3R: Geometric 3D Vision Made EasyCode5
VGGSfM: Visual Geometry Grounded Deep Structure From MotionCode5
MV-DUSt3R+: Single-Stage Scene Reconstruction from Sparse Views In 2 SecondsCode4
Generalizable Humanoid Manipulation with 3D Diffusion PoliciesCode4
DROID-Splat: Combining end-to-end SLAM with 3D Gaussian SplattingCode3
Unbiased Estimator for Distorted Conics in Camera CalibrationCode3
MUSt3R: Multi-view Network for Stereo 3D ReconstructionCode3
Camera Calibration via Circular Patterns: A Comprehensive Framework with Measurement Uncertainty and Unbiased Projection ModelCode3
SoccerNet Game State Reconstruction: End-to-End Athlete Tracking and Identification on a MinimapCode3
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