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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 61–70 of 343 papers

TitleStatusHype
An Online Approach and Evaluation Method for Tracking People Across Cameras in Extremely Long Video Sequence—0
Multi-View People Detection in Large Scenes via Supervised View-Wise Contribution WeightingCode1
A Calibration Tool for Refractive Underwater Vision—0
DiffCalib: Reformulating Monocular Camera Calibration as Diffusion-Based Dense Incident Map GenerationCode2
CasCalib: Cascaded Calibration for Motion Capture from Sparse Unsynchronized CamerasCode0
Reviewing Intelligent Cinematography: AI research for camera-based video production—0
Motor Focus: Fast Ego-Motion Prediction for Assistive Visual NavigationCode0
ESC: Evolutionary Stitched Camera Calibration in the Wild—0
SoccerNet Game State Reconstruction: End-to-End Athlete Tracking and Identification on a MinimapCode3
A Universal Protocol to Benchmark Camera Calibration for Sports—0
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