Search Results for author:
Found 4 papers, 3 papers with code
Quo Vadis, Skeleton Action Recognition ?
To study skeleton-action recognition in the wild, we introduce Skeletics-152, a curated and 3-D pose-annotated subset of RGB videos sourced from Kinetics-700, a large-scale action dataset.
Ranked #1 on
Skeleton Based Action Recognition
on Skeletics-152
MUGL: Large Scale Multi Person Conditional Action Generation with Locomotion
We introduce MUGL, a novel deep neural model for large-scale, diverse generation of single and multi-person pose-based action sequences with locomotion.
Transfer4D: A Framework for Frugal Motion Capture and Deformation Transfer
Animating a virtual character based on a real performance of an actor is a challenging task that currently requires expensive motion capture setups and additional effort by expert animators, rendering it accessible only to large production houses.
Action-GPT: Leveraging Large-scale Language Models for Improved and Generalized Action Generation
We show that utilizing these detailed descriptions instead of the original action phrases leads to better alignment of text and motion spaces.
