Actor-agnostic Multi-label Action Recognition with Multi-modal Query. (arXiv:2307.10763v2 [cs.CV] UPDATED)

Existing action recognition methods are typically actor-specific due to the
intrinsic topological and apparent differences among the actors. This requires
actor-specific pose estimation (e.g., humans vs. animals), leading to
cumbersome model design complexity and high maintenance costs. Moreover, they
often focus on learning the visual modality alone and single-label
classification whilst neglecting other available information sources (e.g.,
class name text) and the concurrent occurrence of multiple actions. To overcome
these limitations, we propose a new approach called 'actor-agnostic multi-modal
multi-label …

action recognition actors animals arxiv classification complexity costs design differences focus humans intrinsic maintenance model design query recognition