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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 3140 of 343 papers

TitleStatusHype
CaMuViD: Calibration-Free Multi-View Detection0
Simultaneously Recovering Multi-Person Meshes and Multi-View Cameras with Human SemanticsCode2
LUCES-MV: A Multi-View Dataset for Near-Field Point Light Source Photometric Stereo0
MV-DUSt3R+: Single-Stage Scene Reconstruction from Sparse Views In 2 SecondsCode4
Data Fusion of Semantic and Depth Information in the Context of Object Detection0
BroadTrack: Broadcast Camera Tracking for SoccerCode1
MCBLT: Multi-Camera Multi-Object 3D Tracking in Long Videos0
RoMo: Robust Motion Segmentation Improves Structure from Motion0
Boost 3D Reconstruction using Diffusion-based Monocular Camera CalibrationCode2
DROID-Splat: Combining end-to-end SLAM with 3D Gaussian SplattingCode3
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