Spacecraft Pose Estimation
7 papers with code • 0 benchmarks • 0 datasets
Benchmarks
These leaderboards are used to track progress in Spacecraft Pose Estimation
Most implemented papers
SPEED+: Next-Generation Dataset for Spacecraft Pose Estimation across Domain Gap
Autonomous vision-based spaceborne navigation is an enabling technology for future on-orbit servicing and space logistics missions.
Pose Estimation for Non-Cooperative Rendezvous Using Neural Networks
The SPN method then uses a novel Gauss-Newton algorithm to estimate the position by using the constraints imposed by the detected 2D bounding box and the estimated attitude.
Deep Learning for Spacecraft Pose Estimation from Photorealistic Rendering
pedropro/UrsoNet
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On-orbit proximity operations in space rendezvous, docking and debris removal require precise and robust 6D pose estimation under a wide range of lighting conditions and against highly textured background, i. e., the Earth.
Robust Multi-Task Learning and Online Refinement for Spacecraft Pose Estimation across Domain Gap
tpark94/spnv2
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These tasks are all related to detection and pose estimation of a target spacecraft from an image, such as prediction of pre-defined satellite keypoints, direct pose regression, and binary segmentation of the satellite foreground.
Mobile-URSONet: an Embeddable Neural Network for Onboard Spacecraft Pose Estimation
Spacecraft pose estimation is an essential computer vision application that can improve the autonomy of in-orbit operations.
Spacecraft Pose Estimation Based on Unsupervised Domain Adaptation and on a 3D-Guided Loss Combination
Spacecraft pose estimation is a key task to enable space missions in which two spacecrafts must navigate around each other.
SU-Net: Pose estimation network for non-cooperative spacecraft on-orbit
Tombs98/SU-Net
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In this way, the feature loss and the complexity of the model is reduced, and the degradation of deep neural network during training is avoided.
