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Found 7 papers, 3 papers with code
Multiple View Geometry Transformers for 3D Human Pose Estimation
In this work, we aim to improve the 3D reasoning ability of Transformers in multi-view 3D human pose estimation.
Uncertainty-aware 3D Object-Level Mapping with Deep Shape Priors
Unlike current state-of-the-art approaches, we explicitly model the uncertainty of the object shapes and poses during our optimization, resulting in a high-quality object-level mapping system.
Multi-view 3D Object Reconstruction and Uncertainty Modelling with Neural Shape Prior
We propose a method to model uncertainty as part of the representation and define an uncertainty-aware encoder which generates latent codes with uncertainty directly from individual input images.
SO-SLAM: Semantic Object SLAM with Scale Proportional and Symmetrical Texture Constraints
Object SLAM introduces the concept of objects into Simultaneous Localization and Mapping (SLAM) and helps understand indoor scenes for mobile robots and object-level interactive applications.
Stereo Plane SLAM Based on Intersecting Lines
Adding such plane features in stereo SLAM system reduces the drift error and refines the performance.
Object-oriented SLAM using Quadrics and Symmetry Properties for Indoor Environments
As objects are often observed locally, the proposed algorithm uses the symmetrical properties of indoor artificial objects to estimate the occluded parts to obtain more accurate quadric parameters.
Coarse-To-Fine Visual Localization Using Semantic Compact Map
Robust visual localization for urban vehicles remains challenging and unsolved.
