This is challenging, as it requires the avatar to walk towards the object with foot-ground contact, orient the head towards it, reach out, and grasp it with a realistic hand pose and hand-object contact.
Second, human shape is highly correlated with gender, but existing work ignores this.
Ranked #1 on 3D Multi-Person Mesh Recovery on AGORA
To understand how people look, interact, or perform tasks, we need to quickly and accurately capture their 3D body, face, and hands together from an RGB image.
To motivate this, we show that current 3D human pose estimation methods produce results that are not consistent with the 3D scene.
We use the new method, SMPLify-X, to fit SMPL-X to both controlled images and images in the wild.
Ranked #3 on 3D Human Reconstruction on AGORA
We use the human joints as these keypoints and term our Pose moTion representation PoTion.
Ranked #1 on Skeleton Based Action Recognition on J-HMDB