While the voxel-based methods have achieved promising results for multi-person 3D pose
estimation from multi-cameras, they suffer from heavy computation burdens, especially for …

Existing volumetric methods for predicting 3D human pose estimation are accurate, but
computationally expensive and optimized for single time-step prediction. We present …

Abstract 3D human pose estimation has been a long-standing challenge in computer vision
and graphics, where multi-view methods have significantly progressed but are limited by the …

Abstract 3D pose estimation is an invaluable task in computer vision with various practical
applications. Especially, 3D pose estimation for multi-person from a monocular video …

We address the problem of generalizability for multi-view 3D human pose estimation. The
standard approach is to first detect 2D keypoints in images and then apply triangulation from …

Computing at the edge is important in remote settings, however, conventional hardware is
not optimized for utilizing deep neural networks. The Google Edge TPU is an emerging …

We present an approach for estimating a mobile robot's pose wrt the allocentric coordinates
of a network of static cameras using multi-view RGB images. The images are processed …

Multi-view 3D human pose estimation (HPE) currently faces several key challenges.
Information from different viewpoints exhibits high variability due to complex environmental …

In multi-view 3D human pose estimation (HPE), information from different viewpoints is
highly variable due to complex factors such as background and occlusion, making cross …

In multi-view 3D human pose estimation (HPE), viewpoint images have large variability due
to factors like camera angles and occlusion, making feature extraction and fusion across …