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Cross-attention of disentangled modalities for 3d human mesh recovery with transformers
Transformer encoder architectures have recently achieved state-of-the-art results on
monocular 3D human mesh reconstruction, but they require a substantial number of …
monocular 3D human mesh reconstruction, but they require a substantial number of …
Convolutional mesh regression for single-image human shape reconstruction
This paper addresses the problem of 3D human pose and shape estimation from a single
image. Previous approaches consider a parametric model of the human body, SMPL, and …
image. Previous approaches consider a parametric model of the human body, SMPL, and …
Implicit-pdf: Non-parametric representation of probability distributions on the rotation manifold
Pose from shape: Deep pose estimation for arbitrary 3d objects
Most deep pose estimation methods need to be trained for specific object instances or
categories. In this work we propose a completely generic deep pose estimation approach …
categories. In this work we propose a completely generic deep pose estimation approach …
Spherical regression: Learning viewpoints, surface normals and 3d rotations on n-spheres
Many computer vision challenges require continuous outputs, but tend to be solved by
discrete classification. The reason is classification's natural containment within a probability …
discrete classification. The reason is classification's natural containment within a probability …
[HTML][HTML] Vision-based spacecraft pose estimation via a deep convolutional neural network for noncooperative docking operations
The capture of a target spacecraft by a chaser is an on-orbit docking operation that requires
an accurate, reliable, and robust object recognition algorithm. Vision-based guided …
an accurate, reliable, and robust object recognition algorithm. Vision-based guided …