https://github.com/smbonilla/gaussianpancakes
3D Gaussian Splatting for Real-Time Radiance Field Rendering
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
3D Gaussian Splatting for Real-Time Radiance Field Rendering
EdgeCalib: Multi-Frame Weighted Edge Features for Automatic Targetless LiDAR-Camera Calibration
MVOR: A Multi-view RGB-D Operating Room Dataset for 2D and 3D Human Pose Estimation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.