3 accepted papers
Cross-task generalization is a core challenge in open-world robotic manipulation, and the key lies in extracting transferable manipulation knowledge from seen tasks. Recent in-context learning approaches leverage seen task demonstrations to generate actions for unseen tasks without parameter updates…
The existing monocular methods face huge challenges in reconstructing credible details of non-visible areas in large pose images. Due to the fact that facial details are lost in non-visible areas of large pose images, existing methods lose basis when reconstructing details, resulting in unreliable r…
Despite significant advances in 3D human pose estimation from a single-view video, existing methods often struggle to produce reasonable human poses when the human is heavily occluded or blurred. To address this issue, we propose a Mixed Spectral and Attention Network (MSANet) that stacks spectral a…