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Found 8 papers, 0 papers with code
Modular Framework for Visuomotor Language Grounding
Natural language instruction following tasks serve as a valuable test-bed for grounded language and robotics research.
Predicting Camera Viewpoint Improves Cross-dataset Generalization for 3D Human Pose Estimation
Monocular estimation of 3d human pose has attracted increased attention with the availability of large ground-truth motion capture datasets.
Ranked #1 on
3D Human Pose Estimation
on Geometric Pose Affordance
(MPJPE metric)
Domain Decluttering: Simplifying Images to Mitigate Synthetic-Real Domain Shift and Improve Depth Estimation
In this setting, we find that existing domain translation approaches are difficult to train and offer little advantage over simple baselines that use a mix of real and synthetic data.
Geometric Pose Affordance: 3D Human Pose with Scene Constraints
Full 3D estimation of human pose from a single image remains a challenging task despite many recent advances.
3D Scene Reconstruction with Multi-layer Depth and Epipolar Transformers
We tackle the problem of automatically reconstructing a complete 3D model of a scene from a single RGB image.
Pixels, voxels, and views: A study of shape representations for single view 3D object shape prediction
The goal of this paper is to compare surface-based and volumetric 3D object shape representations, as well as viewer-centered and object-centered reference frames for single-view 3D shape prediction.
3DFS: Deformable Dense Depth Fusion and Segmentation for Object Reconstruction from a Handheld Camera
The resulting depth maps are then fused using a proposed implicit surface function that is robust to estimation error, producing a smooth surface reconstruction of the entire scene.
Completing 3D Object Shape From One Depth Image
Our goal is to recover a complete 3D model from a depth image of an object.
