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Deep Learning for Spacecraft Pose Estimation from Photorealistic Rendering.

, и . ICRA, стр. 6007-6013. IEEE, (2020)

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José Aleixo Sousa Proença

Benno Pedrotti

Mario Pedroso

Luicy Pedroza Espinoza

Claudia Pedroni

 

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TACO: Trash Annotations in Context for Litter Detection., и . CoRR, (2020)Probabilistic RGB-D Odometry based on Points, Lines and Planes Under Depth Uncertainty., и . CoRR, (2017)Good Appearance and 3D Shape Descriptors for Object Category Recognition., , и . Int. J. Artif. Intell. Tools, 24 (4): 1540017:1-1540017:16 (2015)Retrieval of Objects Captured with Kinect One Camera., , , , , , , , , и 1 other автор(ы). 3DOR@Eurographics, стр. 145-151. Eurographics Association, (2015)Probabilistic Combination of Noisy Points and Planes for RGB-D Odometry., и . TAROS, том 10454 из Lecture Notes in Computer Science, стр. 340-350. Springer, (2017)Deep Learning for Spacecraft Pose Estimation from Photorealistic Rendering., и . ICRA, стр. 6007-6013. IEEE, (2020)SPLODE: Semi-probabilistic point and line odometry with depth estimation from RGB-D camera motion., и . IROS, стр. 1594-1601. IEEE, (2017)Fast Cylinder and Plane Extraction from Depth Cameras for Visual Odometry., и . IROS, стр. 6813-6820. IEEE, (2018)Optimizing Terrain Mapping and Landing Site Detection for Autonomous UAVs., , и . ICRA, стр. 9668-9674. IEEE, (2022)Multi-Resolution Elevation Mapping and Safe Landing Site Detection with Applications to Planetary Rotorcraft., , , , , , , и . IROS, стр. 1990-1997. IEEE, (2021)